Fall 2021 - Mensa Research Journal

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Published by the Mensa Foundation

The Experiential Learning Theory of Dr. David Kolb and Dr. Alice Kolb

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Volume 52 No. 3 • MensaFoundation.org

Staff: Editor-In-Chief • Jeff Papa MRJeditor@mensafoundation.org Editor Emeritus • Phyllis Miller, phyllis.miller@gmail.com Circulation Manager • Jill Beckham jillb@mensafoundation.org, (817) 607-0060, ext. 5509 Production Manager • Hilary Moore artdirector@americanmensa.org, (817) 607-0060, ext. 5544

Mensa Research Journal Editorial Advisory Board Ryan Donlan, Ed.D. Chair Erin L. Albert, Pharm.D. James H. Dobbins, Ph.D. Keri M. Guilbault, Ed.D. Mary Jacobsen, Psy.D. Frank Lawlis, Ph.D. Ken Martin, Ph.D. Martha Merrill, Ed.D.

Mensa Foundation Board of Trustees Charlie Steinhice • President Deb Stone • Vice President Vicki Herd • Treasurer Jenny Wise • Secretary Nguyen Pham Michelle Rakshys Björn Liljeqvist • Chair, Mensa International — Ex-Officio Timmy King • Chair, American Mensa — Ex-Officio

The Mensa Foundation Mensa, the high-IQ society, provides a meeting of the minds for people who score in the top 2 percent on standardized IQ tests. As an international organization with thousands of members worldwide, Mensa seeks to identify and foster human intelligence; encourage research in the nature, characteristics, and uses of intelligence; and provide a stimulating intellectual and social environment for its members.

The first two of these purposes are largely carried out by the Mensa Foundation. The Foundation is a philanthropic, nonprofit, tax-exempt organization funded primarily by gifts from Mensa members and others. The Foundation awards scholarships and research awards, publishes the Mensa Research Journal, and funds other projects consistent with its mission.

For more information about the Foundation, visit mensafoundation.org.

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The Journal is published at least three times a year. Subscribers will receive all issues for which they have paid, even if frequency of publication varies. Membership in Mensa is not required. To order back issues or report address changes, write to Mensa Research Journal, 1315 Brookside Drive, Hurst, Texas 76053.

The Editorial Board of the Mensa Research Journal selects articles to show most sides of an issue. Publication of a research article in the Mensa Research Journal does not indicate agreement on the part of the Editorial Board of the Mensa Research Journal or the Mensa Foundation with the contents of any particular article or any conclusions stated therein. All articles are reprints from selected journals and are printed as is. The MRJ has made no style or grammar corrections, though we do make minor formatting changes to fit our pages and layout.

The Mensa and Mensa Foundation logos are trademarks and service marks of American Mensa, Ltd., used by the Mensa Foundation under license. Mensa is a registered trademark of American Mensa, Ltd. Each article reprinted in MRJ is reprinted with permission of the copyright holder.

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Mensa Research Journal (ISSN 0025-9551) is published at least three times per year by the Mensa Education & Research Foundation, 1315 Brookside Drive, Hurst, Texas 76053. © 2021 Mensa Foundation

MRJ Mensa Research Journal

Fall 2021 Volume 52 Issue 3

Editorial

From the Editor-In-Chief

by Jeff Papa ������������������������������������������������������������������������������������ 5

Featured Articles

Meet the MRJ Editorial Advisory Board �����������������������������������������������������������������������������������6 Experiential Learning Theory as a Guide for Experiential Educators in Higher Education

Alice Y. Kolb and David A. Kolb ���������������������������������������������������������������������������������������������������������������������������������8

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

Andrea Micheaux and Birgit Bosio �������������������������������������������������������������������������������������������������������������������������25

The Use of Kolb’s Model in Science Teaching Methodology

Snježana Močinić, Nevenka Tatković, and Sanja Tatković �����������������������������������������������������������������������������������39

Entrepreneurial Learning From Failure. A Systematic Review

Wolfgang Lattacher and Malgorzata Anna Wdowiak �������������������������������������������������������������������������������������������54

Eight Important Things To Know About the Experiential Learning Cycle

Alice Kolb and David Kolb ���������������������������������������������������������������������������������������������������������������������������������������84

A Few Thousand Words, on ‘A Thousand Brains’: A Book Review on Jeff Hawkins’ New Theory of Intelligence

By Ryan Donlan �������������������������������������������������������������������������������������������������������������������������������������������������������90

From Phonetics to Sci Fi: Dr. Francis Cartier

by Tomiko Breland ���������������������������������������������������������������������������������������������������������������������������������������������������94

Random Samples and Standard Deviations

Jeff Papa and Ryan Donlan. �����������������������������������������������������������������������������������������������������������������������������������96

2021 Mensa Foundation Award Recipients �������������������������������������� 100

F O U N D AT I O N

Cover: Experiencing the marvels of space may be a more effective way to learn than just reading about them in a textbook. Drs. Alice and David Kolb’s Experiential Learning Theory explains the benefits of learning through exploration.

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MRJ

From the Editor-in-Chief ON BEHALF OF the Editorial Board, staff, and contributors to the Mensa Research Journal (MRJ), I would like to take this opportunity to thank you for your interest in reading and continued sponsorship.

Our Fall 2021 issue of the MRJ begins with background information regarding the MRJ Editorial Advisory Board (EAB) members. Members of the EAB are subject-matter experts who work hard to analyze, review, and produce content for the MRJ and are rarely recognized outside of their listing on our masthead. We would like to take this opportunity to share their backgrounds with you and to recognize their contributions. Of course, the MRJ would also like to thank Marie Mayer for her dedicated service.

Marie recently completed her service on the Mensa Foundation Board of Trustees (the Mensa Foundation is the MRJ’s parent organization), where she previously served as Trustee, Secretary, Vice-President, and President. Marie stepped in as Interim Editor of the MRJ and spent two years of dedicated service in that role.

The articles in this issue focus on the experiential learning theories of Dr. David Kolb and Dr. Alice Kolb (i.e., the Kolbs). The Experiential Learning Cycle, as described by the authors, is a four-step cycle of learning that applies experiencing, reflecting, thinking, and acting in a recursive loop. In other words, learning is aided when the learner has an actual experience and then reflects upon that experience, thinks about the experience and reflection in an abstract manner to form new or improved concepts, and then takes action to experiment with or confirm these ideas. The process then begins anew with a fresh, concrete experience, and the cycle repeats. This cycle can occur in different ways, depending on the individual learner. This depends to some extent on the preferred learning methods of the student: Imagining, Experiencing, Analyzing, Reflecting, Deciding, Thinking, Initiating, Acting, and Balancing are all possible avenues for learning within this recursive cycle.

We begin with an article from the Kolbs on utilizing experiential learning theory in higher education. This article explains the concept and its application in higher education.

The next three articles examine the use of experiential learning theory in different fields: customer journey mapping, science teaching methodology, and entrepreneurial learning from failure. We then conclude with an additional short article by the Kolbs, entitled Eight Important Things to Know About the Experiential Learning Cycle. By reading these articles, one can learn the foundational concepts in great detail, learn about their application in various fields, and then refresh with the highlights of the theory in a more condensed format.

For those readers who may wish to learn more about the work of Drs. Kolb and Kolb, they offer video content explaining these concepts in great detail at bit.ly/learning-video-series. Another interesting article building on the Kolbs’ work that you may wish to read is Reverse Bloom: A New Hybrid Approach to Experiential Learning for a New World, which can be found in the December 2020 issue of the Journal of Education, Innovation, and Communication.

You may also enjoy reading Understanding the Onset of Hot Streaks Across Artistic, Cultural, and Scientific Careers, which can be found online in the journal Nature Communications.

This issue of the MRJ also includes an in-depth review by our EAB Chair, Dr. Ryan Donlan, of the 2021 book A Thousand Brains: A New Theory of Intelligence. Longtime contributor Dr. Fran Cartier recently retired from contributing his entertaining and informative Notes, Quotes, and Anecdotes column in the MRJ. In this issue, we share a tribute to Dr. Cartier and his many career accomplishments with our appreciation for his longtime service. This issue also includes the latest Mensa Foundation news, as well as the new Random Samples and Standard Deviations column. This new column will pass along interesting information and short references to groundbreaking research.

This is the first issue of the MRJ produced with direction from my new role as Editor-in-Chief, alongside new EAB Chair Ryan Donlan, Ed.D. In preparation for these roles, we spent a great deal of time reviewing past issues, asking questions of professionals who have been involved with the MRJ, observing and discussing the MRJ with Past Interim Editor Marie Mayer, and reviewing past reader input and suggestions. Our goal is to continue to produce an interesting, informative, quality journal, building upon its foundation of thought excellence and continually working to enhance the MRJ with your input.

We invite you to enjoy the Fall 2021 MRJ. Thank you for reading, and please contact us with any feedback or suggestions you may have – including topics that you might find interesting or impactful!

Jeff Papa, Ph.D. Editor-in-Chief MRJEditor@mensafoundation.org

Correction: The Summer 2021 issue (Volume 52 No. 2) contained a misspelling on the cover. Apologies to Dr. Simon Baron-Cohen for the error, which was due to my oversight. – Marie Mayer, Past Interim Editor

Articles in this publication have been reprinted from peer-reviewed journals and other copyrighted publications.

We do not modify the text.

Volume 52, Issue 3 • 5

MRJ

Meet the MRJ Editorial Advisory Board THE MENSA RESEARCH JOURNAL (MRJ) is the product of collaboration among several dedicated professional staff members and volunteers. The MRJ Editorial Advisory Board (EAB) is composed of several leading authors, researchers, scientists, and thinkers. This group, while rarely recognized, contributes valuable input and assistance to the MRJ. Recently, several members of the EAB completed their service, and three new members joined the EAB. The MRJ would like to take this opportunity to introduce the current members of the EAB and to thank those departing EAB members for their many contributions.

Ryan Donlan, Ed.D., Professor in the Department of Educational Leadership at the Bayh College of Education of Indiana State University, has served for 20 years in K–12 education—in teaching, in school building leadership, and in the superintendency. He has served in a variety of university leadership roles by request, including as Interim Department Chairperson, Department Chairperson, Director of Assessment and Accreditation, Acting Associate Dean, Vice-Chair of the Institutional Review Board (IRB), and Chair of the Institutional Review Board. Dr. Donlan provides educational program reviews, training, and organizational consulting; enjoys ambitious scholarship and research; chairs numerous dissertations; and is a Master Trainer in the Process Communication Model® (PCM). Once a frequent skydiver, Dr. Donlan today enjoys more conservative, contemporary pursuits, such as cooking, reading, and camping. He has written/co-written a number of articles and books, including Gamesmanship for Teachers: Uncommon Sense is Half the Work, The Secret Solution: How One Principal Discovered the Path to Success, Minds Unleashed: How Principals Can Lead the RightBrained Way, The Hero Maker: How Superintendents Can Get Their Boards to Do the Right Thing, and The School Board Member Guidebook: Becoming a Difference Maker in Your District. Dr. Donlan is currently readying a book for production, titled All Other Duties as Assigned: The Assistant Principal’s Critical Role in Supporting Schools Inside and Out and is involved in research and scholarship in organizational health, performance enhancement, and leadership development. You can follow Dr. Donlan on Twitter at twitter/ryandonlan, or visit him at ryandonlan.com and mindsunleashed.net.

Erin L. Albert, M.B.A., Pharm.D., J.D., is the Kinetiq Health Pharmacy Benefits Practice Leader at Apex Benefits, a contract writer for GoodRx, an author, and a podcaster. Dr. Albert is both a pharmacist and an attorney. Prior to joining Kinetiq and

6 • Mensa Research Journal

Apex, she taught pharmacy students at Butler University College of Pharmacy and Health Sciences for more than a decade—several courses including pharmacy law, ethics, writing and publishing, leadership, entrepreneurship, self-care, and community practice pharmacy courses and content. She also served as a director of content for two different accredited continuing pharmacy education programs, worked in both fee-for-service and managed-care Medicaid, in the pharmaceutical industry in a variety of roles—(including pharmacovigilance, clinical trials, medical affairs, and medical marketing)—and in community practice pharmacy. The author of more than a dozen of her own books, Dr. Albert also currently writes freelance for the peer-to-peer blog at GoodRx and has written for other pharmacy publications.

Her most recent writing experiment is an ongoing subscription/book, Punk Rock Pharmacy: DIY Your Healthcare Career.

Lastly, her podcast is The Edutainer, where she explores the intersection of education and entertainment. She lives in the Midwest and is a graduate of Butler University, Shenandoah University, Concordia University Wisconsin, and the Indiana University Robert H. McKinney School of Law. James H. Dobbins, Ph.D., J.D., was a contractor with IBM and was on the Apollo Flight Support Team in Houston.

He also was Program Chairman for Gulf Coast Mensa. Dr. Dobbins then worked on Air Force satellite programs and Navy antisubmarine warfare programs. He started and ran a Gifted Children program at a parochial school in Manassas. He earned his bachelor’s degree in physics from Loyola University-New Orleans and both his master’s degree in information systems and his Ph.D. in program management from George Washington University. His dissertation was titled Critical Success Factors for DoD Program Management.

Dr. Dobbins was active in software engineering and software reliability and was the IEEE Working Group Chair for development of IEEE Std 982.1 and the Guide 982.2.

He participated in the Exchange of Distinguished Engineers and Scientists Program between the U.S. and France in 1985 and again in 1986. During this time, Dr. Dobbins completed his law studies and was admitted to the Virginia Bar in 1982.

In 1989 Dr. Dobbins entered government service at the Defense Acquisition University as a Professor of Acquisition Management as well as Director of Consulting and Acquisition Research. He served a term on the Board of Examiners of the National Malcolm Baldrige Award. Dr. Dobbins retired from Government service in 2003. He then joined The MITRE Corporation supporting DoD and the intelligence community and retired in 2015.

Meet the MRJ Editorial Advisory Board

Keri M. Guilbault, Ed.D., is an Assistant Professor and Director of the gifted education graduate programs at Johns Hopkins University. In 2019 she was recognized by the National Association for Gifted Children as the Early Leader Award recipient and by American Mensa with the National Service Award.

Dr. Guilbault has worked as a district supervisor of gifted and talented programs in Maryland and as a teacher of the gifted in both Florida and Maryland. Her recent leadership experience includes service on the Board of Directors of the National Association for Gifted Children and the Board of Trustees of the Mensa Education and Research Foundation. She previously served American Mensa as the national Gifted Children’s Program Chair and as the Director of Science and Education. Dr. Guilbault received her master’s degree in gifted education from the University of South Florida and her doctoral degree in educational leadership with specialization in gifted education program administration from the University of Central Florida. Her research interests include highly to profoundly gifted learners, parenting the gifted, and academic acceleration.

Mary Jacobsen, Psy.D., is Professor and Chair of the Department of Psychological Science at Salem College in North Carolina. Her ongoing international research focuses on high ability, top performance in organizations, and identifying barriers to innovation and success. She is a contributing editor for the Roeper Review. In recent years she founded a public forum, Leading Innovation: Inventing the Future with Science, bringing together cutting-edge researchers and scientists to promote interest in STEM careers and support pioneering advancements.

Previously, she served as Chief Psychologist for the Amherst Wilder Foundation, where she established a multicultural testing center and continues her private practice in support of gifted children and adults. Dr. Jacobsen also provides coaching and talent management advice for global organizations. In addition, she serves as a visiting Research Fellow for Ashridge Business School in the UK, advising coaches, instructors, students, and organizational leaders. Her first book, The Gifted Adult, explores the lives and issues of gifted adults and remains a seminal book on the subject.

Dr. Frank Lawlis received his Ph.D. from Texas Tech University with an emphasis on rehabilitation counseling psychology and psychometrics after receiving his master’s in counseling psychology and a B.S. in education and mathematics from

the University of North Texas. He has pioneered research and clinical methods in research methodology and statistics, imagery techniques (cancer), pain perception and rehabilitation, biofeedback, transpersonal psychology, and, most recently, psycho-neuroplasticity. He has published 18 bestselling books incorporating these concepts and published more than 100 articles in research journals. Some of his classic books include The ADD Answer, The IQ Answer, and Transpersonal Medicine. He has held professorships at five major medical schools, including University of Texas Health Science Center at both Dallas and San Antonio, Texas Tech University Medical School, and Stanford Medical School. He has earned board certification in both clinical and counseling psychology from the American Board of Professional Psychology Inc. and has been awarded Fellow status by the APA for his scientific contributions to clinical psychology. He also has served as Chief of Oversite Production and Resources on The Dr. Phil show for 16 years and has gained international fame for his participation on the show. He has joined Dr. Phil in Congressional Hearings on such topics as Foster Care and Addiction issues. He has also been Supervisor of the Testing Program for American Mensa. The Texas Psychological Association awarded him the 2018 Outstanding Media Coverage Award. Dr. Lawlis is now serving as President of the Mental Health Resilience Foundation.

Martha Merrill is an Administrator and Professor at Pellissippi State Community College in Knoxville, Tenn. She teaches advanced courses in web and graphic design. She has degrees in English, psychology, technological and adult education, and collaborative learning and has worked as a social worker, information systems manager, and online course designer. She looks forward to retiring in a couple of years and devoting more time to her extensive list of hobbies, including gardening, swimming, writing, painting, reading, and traveling. She has enjoyed her time as a Mensa Research Journal EAB member.

A profile for EAB member Dr. Ken Martin was not available at time of publication. The MRJ would also like to thank EAB members who recently completed their service: former Chair Charles Rawlings, Ph.D., Bonnie Brinton Anderson, Ph.D., Caroline Mossip, Ph.D., and Don Platine, Ph.D. We appreciate their dedication and long-standing service.

Volume 52, Issue 3 • 7

MRJ

Experiential Learning Theory as a Guide for Experiential Educators in Higher Education Alice Y. Kolb and David A. Kolb

Abstract Core concepts of Experiential Learning Theory—the learning cycle, learning style, and learning space—have been widely used by experiential educators in higher education for nearly half a century. We examine the latest thinking about these three concepts and highlight some exemplary applications from the many disciplinary applications of experiential learning in higher education.

I think that only slight acquaintance with the history of education is needed to prove that educational reformers and innovators alone have felt the need for a philosophy of education. Those who adhered to the established system needed merely a few fine-sounding words to justify existing practices. The real work was done by habits which were so fixed as to be institutional. The lesson for progressive education is that it requires in an urgent degree, a degree more pressing than was incumbent upon former innovators, a philosophy of education based on a philosophy of experience.

John Dewey, Experience and Education THIS INAUGURAL ISSUE of Experiential Learning & Teaching in Higher Education marks a milestone in the growing awareness and use of experiential learning as a learning platform in education. Since the early 1970s, the principles and practices of experiential learning have been widely adopted to create curricula and conduct educational courses and programs. Many of the non-traditional educational innovations that have flowered during this period, such as competency-based undergraduate education (Mentkowski 2000), professional education (Boyatzis, Cowan & Kolb 1995), college programs for adult learners, and prior learning assessment (Keeton & Tate 1978; Simosko 1988) have used experiential learning as their educational platform. As experiential, learner-centered education has gained widespread acceptance in the twenty-first century (Prince & Felder 2006; Slavich & Zimbardo 2012), more and more educators are experimenting with experiential learning practices such as service learning (Bielefeldt et al.

2011; Brower 2011), problem based learning (Gurpinar, Bati & Tetik 2011; Bethell & Morgan 2011), action learning (Revans 1980; Keys 1994; Foy 1977), adventure education (Fuller 2012; Timken & McNamee 2012), and simulation and gaming (Taylor, Backlund & Niklasson 2012; Shields, Zawadzki & Johnson 2011; Schaefer et al. 2011).

In their formulation of transformational teaching, George M. Slavich and Philip G. Zimbardo (2012) describe the multidimensional importance of experience in learning: [E]xperiential lessons provide students with an opportunity to experience concepts first-hand and, as such,

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give students a richer, more meaningful understanding of course concepts and of how they operate in the real world.… They enhance the affective quality of the course content. This occurs both when students are engaged in solving problems that are part of the activities and when they are analyzing, sharing, discussing, and reflecting on their personal reactions.… It can significantly improve students’ memory for concepts insofar as the information gets stored in autobiographical memory.… Experiential lessons have the ability to shape students’ beliefs about learning and about the self.… They can lead to significant personal insights, including a greater awareness of one’s personally held perspectives—as well as an improved awareness of other people’s experience—with the possibility to enhance these attributes through critical reflection. (594)

In his study of student careers after college, Jeffrey J. Selingo (2016) argues that co-curricular experiential learning experiences are what distinguish successful careers from drifters: But it’s not just the college degree that separates the successful from the drifters these days. If that were the case, recent college graduates wouldn’t be standing in the unemployment line or settling for jobs that don’t require a bachelor’s degree. While some sort of degree after high Kolb, Alice Y. and Kolb, David A. (2017) “Experiential Learning Theory as a Guide for Experiential Educators in Higher Education,” Experiential Learning & Teaching in Higher Education: Vol. 1 : No. 1 , Article 7.

Available at: https://nsuworks.nova.edu/elthe/vol1/iss1/7

contributions to experiential learning. Their contributions span over one hundred years, beginning at the end of the nineteenth century with William James, John Dewey, and Mary Parker Follett, and ending at the end of the Experiential Learning Theory as a Guide for Experiential Educators in Higher Education twentieth century with the deaths of Carl Rogers and Paulo Freire. school remains the foundation of a successful life and career, other coming-ofage, real-world experiences in the late teens and early twenties—particularly apprenticeships, jobs, or internships— actually matter more nowadays in moving from college to a career. (8-9)

Figure 1. Foundational Scholars of ELT

Selingo found that 79% of the most successful college graduates had at least one college internship as well as other out of the classroom projects. Many educational institutions offer these co-curricular experiential education programs to add a direct experience component to their traditional academic studies.

In this essay we will examine these applications of experiential learning in higher education through the lens of Experiential Learning Theory (ELT) (Kolb 2015) by examining exemplary applications of experiential learning concepts in several of the many disciplines of higher education. From the countless numbers of college teachers around the world who have begun to define themselves as experiential educators, weELTHE: have selectscholars who gave experience a central role in their theories 10 A Journal for Engaged Educators ed a few documented examples of how ELT concepts are of human learning and development. We have come to call used in their work. We begin with the central ELT concept them the “foundational scholars of experiential learning”: of the learning cycle and how it can be used to teach William James, John Dewey, Kurt Lewin, Jean Piaget, Lev around the learning cycle. Two applications of the concept Vygotsky, Carl Jung, Mary Parker Follett, Carl Rogers, and in management education are described. Next, the ELT Paulo Freire. Figure 1 depicts these foundational scholars concept of learning style is addressed, emphasizing how its of ELT and a summary of their contributions to experienstatus as a dynamic state as opposed to a fixed trait is unique tial learning. Their contributions span over one hundred among the many learning style approaches. Trait learning years, beginning at the end of the nineteenth century with style approaches emphasize matching style to instructional William James, John Dewey, and Mary Parker Follett, and method while ELT learning styles emphasize learning flex- ending at the end of the twentieth century with the deaths of Carl Rogers and Paulo Freire. ibility and expanding one’s preferred style to encompass all ELT is a dynamic, holistic theory of the process of learnlearning modes for full cycle learning. The application of ing from experience and a multi-dimensional model of this learning style concept to develop law students’ metaadult development. The dynamic view of learning is based learning capabilities is described, and current research on on a learning cycle driven by the resolution of the dual adaptive learning systems in digital education is examined. dialectics of action/reflection and experience/abstraction Finally, we turn to the concept of learning space and exam(see Figure 2).

It is a holistic theory that defines learning as ine two applications. One examines how a positive learning the major process of human adaptation involving the whole identity can be developed in a hospitable learning space. person.

As such, ELT is applicable not only in the formal This study addressed remedial mathematics education in a community college. The second example shows the power education classroom but in all arenas of life. The process of of conversational learning spaces in a (college-level), gener- learning from experience is ubiquitous, present in human activity everywhere all the time. The holistic nature of the al-education freshman seminar. learning process means that it operates at all levels of human society from the individual, to the group, to organizations, Experiential Learning Theory ELT was created to provide an intellectual foundation for and to society as a whole.

To appreciate the holistic and dynamic nature of the the practice of experiential learning responding to John Dewey’s call for a theory of experience to guide education- learning cycle it is useful to examine its philosophical founal innovation. ELT is a synthesis of the works of those great dations in the radical empiricism of William James. James

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experience is ubiquitous, present in human activity everywhere all the time.

The holistic nature of the learning process means that it operates at all levels Experiential Learningfrom Theory as individual, a Guide for Experiential Educators in Higher Education of human society the to the group, to organizations, and to society as a whole.

Figure 2. The Experiential Learning Cycle

experiences that break out of conservative experiencing, such as when we are “stuck” with a problem or difficulty or “struck” by the strangeness of something outside of our usual experience (Dewey 1933).

The implication of the philosophy of radical empiricism for ELT and the experiential learning cycle is that it is not only the Concrete Experience mode of pure experiencing that is experiential; all modes of the learning cycle are experiences. Both modes of grasping experience—Concrete Experience (CE) and Abstract Conceptualization (AC)— and both modes of transforming experience—Reflective Observation (RO) and Active Experimentation (AE)—are part of the experiential learning process.

Many use the term experiential learning to refer to exercises and games used to involve students in the learning process.

However, a classroom lecture may be an abstract experience (1904) proposed radical empiricism as a new philosophy of but it is also a concrete one, when, for example, a learner reality and mind which resolved the conflicts between nineadmires and imitates the lecturer. Likewise, a learner may teenth-century rationalism and empiricism as expressed in 1, No. 1work (2017)hard to 11create an abstract model in order to make sense the philosophies of idealism and materialism. For Vol. James, everything begins and ends in the continuous flux and of an internship experience or experiential exercise. From the flow of experience. In short, experience is all there is: “We learner’s perspective, solitary reflection can be an intensely start with the supposition that there is only one primal emotional concrete experience and the action of programstuff or material in the world, a stuff of which everything ming a computer can be a highly abstract experience.

Since ELT is a holistic theory of learning that identifies is composed… we call that stuff ‘pure experience’” (1142). learning style differences among different academic specialHe goes on to write, ties, it is not surprising to see that ELT research is highly In this formulation the duality between the mind (thought) interdisciplinary, addressing learning and educational issues and physical world (thing) is resolved since both are experiin many fields. ELT is being used extensively by experienenced but with different characteristics, thought is the contial educators as a guide for practice in at least 30 fields crete here-and-now experience “redoubled” in reflection.… and academic disciplines (Kolb & Kolb 2013). Included If it be the self-same piece of pure experience taken twice are research studies from every region of the world, with over that serves now as thought and now as thing… how comes it that its attributes should differ so fundamentally many contributions coming from the U. S., Canada, Brazil, in the two takings? As thing, the experience is extended; as the U. K., China, India, Australia, Japan, Norway, Finland, thought, it occupies no space or place. As thing, it is red, Sweden, the Netherlands, and Thailand. Since its first statehard, and heavy; but who ever heard of a red, hard or heavy ment in 1971 (Kolb, Rubin & McIntyre 1971), there have thought? (1153) been many studies using Experiential Learning Theory to Dewey stressed the dynamic nature of pure experienc- advance the theory and practice of experiential learning. ing in the learning cycle, noting that ordinary experience Since 2000, ELT research in many fields around the world is conservative, tradition-bound, and prone to conformity has more than quadrupled. The current experiential learnand dogmatism, being culturally mediated by many previous ing theory bibliographies include over 4,100 entries dating trips around the learning cycle and saturated with previous between 1971 and 2016 (Kolb & Kolb 2016). A 2013 conclusions. He emphasized that this conservative experi- review of management education research (Arbaugh, DeArence must be interrupted to initiate reflection and learning. mond & Rau 2015) showed that 27% of the top-cited artiHe argued that it was necessary to reflect on experience in cles in management education journals were about expeorder to draw out the meaning in it and to use that mean- riential learning and learning styles. “Learning Styles and ing as a guide in future experiences; but he observed that Learning Spaces” (Kolb & Kolb 2005) ranked second in the reflective process seemed to be initiated only by pure a more extensive study of the 100 most-cited papers in

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Experiential Learning Theory as a Guide for Experiential Educators in Higher Education

management education research (Arbaugh & Hwang 2015), with papers about experiential learning and learning styles accounting for 9% of the total citations.

professors who teach them high status while experiential programs are seen as ancillary and staffed by lower status student development professionals.

Defining Experiential Learning

Teaching around the Learning Cycle

From the perspective of ELT there is a widespread idea of what experiential learning is that fails to capture the full potential of the process of learning from experience. A common usage of the term defines it as a particular form of learning from life experience, often contrasted with lecture and classroom learning. Morris T. Keeton and Pamela J. Tate (1978) offered this definition of experiential learning: “[L]earning in which the learner is directly in touch with the realities being studied. It is contrasted with the learner who only reads about, hears about, talks about, or writes about these realities but never comes into contact with them as part of the learning process”(2). Thus, many people think about experiential activities such as exercises, role plays, ropes courses, games, and field projects when they hear the term experiential learning. A similar limited definition of experiential learning is found in theoretical scholarship. In The Ambiguities of Experience, the great organizational theorist James March (2010) contrasts his definition of experiential knowledge, “lessons extracted from the ordinary course of life and work,” with academic knowledge “generated by systematic observation and analysis by experts and transmitted by authorities” (9). In this view of experiential learning, the emphasis is often on direct sense experience and in-context action as the primary source of learning, often downplaying a role for thinking, analysis, and academic knowledge. The definition of experiential learning as in-context experiencing and action is not the meaning of experiential learning as defined in ELT. Such a definition includes only half of the learning cycle, ignoring the holistic, dialectic nature of the process of learning from experience. The learning cycle is driven by the integration of action and reflection and experience and concept.

The failure to view experiential learning as encompassing all four modes of the learning cycle and as applicable in all learning situations both in the classroom and in life is, we believe, the source of many of the practical difficulties encountered by experiential learning advocates in higher education. Most notably, there is a chasm between academic courses and experiential activities that reduces the effectiveness of both. A service-learning program, for example, can bring students in contact with the realities of social conditions that a sociology course seeks to explicate.

Too often, however, the two activities are so separated that the benefits of classroom reflection and conceptual analysis are not integrated with the learners’ actions to bring change and improvement to the conditions they encounter in the service-learning project. The gulf is further expanded by the culture of higher education, which enshrines courses in the credit-hour time-block system, giving them and the

The cycle of learning from experience is perhaps the best known and widely used concept of ELT. A Google image search for the words “learning cycle” produces a seemingly endless array of reproductions and variations of the cycle from around the world. The learning cycle was first applied in the late 1960s as part of a curriculum development project to use experiential learning methods in a required organizational psychology course for MBAs at the Sloan School of Management at MIT. The original course, a lecture format with 150 students, was a way to structure learning experiences that would bring the fifteen topics covered in the lecture syllabus into the room. Concrete experiences generated by exercises, business games, role plays, and cases provided a common experiential starting point for participants and faculty to explore the relevance of behavioral concepts for their work. Topics like motivation, perception, and group decision-making were organized around the learning cycle providing the experience, structured reflection and conversation exercises, conceptual material, and a personal application assignment. The teacher’s role was to manage a learning process that was basically learner-directed. They helped students to experience in a personal and immediate way the phenomena in their field of specialization. They stood ready with alternative theories and concepts as students attempted to assimilate their observations into their own conception of the topic. They helped students to deduce the implications of their conclusions for their own life and work and to test these implications through practical, real-world experience. The new approach proved quite successful and resulted in the first management textbook based on experiential learning (Kolb, Rubin & McIntyre 1971), which is now in its eighth edition (Osland et al. 2007).

The most important aspect of the learning cycle is that it describes the learning process as a recursive circle or spiral as opposed to the linear, traditional information transmission model of learning used in most education, where information is transferred from the teacher to the learner to be stored in declarative memory for later recall. In the linear model, the learner is a passive recipient of information. Learners, having no direct contact with the subject, are unable to investigate, explore, and judge for themselves.

They are left one-down in a power relationship with only the choice of “taking the teacher’s word for it.” Teachers, for their part, are left in a one-way interaction that is ultimately deadening and boring. Learners’ engagement is rewarded and measured only by points for participation and not by their ability to inquire in depth.

For educators, the magic of experiential learning lies in the unique relationship that is created between the teacher,

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Figure 3. Subject Matter, Educator and Learner Relationships in the Discourse and Experiential Learning Models

beyond themselves to contend with— the power of a subject that transcends our self-absorption and refuses to be reduced to our claims about it. (117)

Recently, we have created a framework to assist educators in their application of the ELT concepts of the learning cycle and learning style in the dynamic matching model of teaching around the learning cycle (Kolb et al.

2014). In our interviews and observations of highly successful educators, we find that they tend to organize their educational activities in such a manner that they address all four learning cycle modes—experiencing, reflecting, thinking, and acting—using some form of the dynamic matching model in the roles they adopt. We developed a self-assessment instrument called the Kolb Educator Role Profile (KERP) to Recently, we have created a framework to assist educators in theirunderstand their own teaching approach help educators the learner, and the subject matter under study (see Figure application of the ELT concepts of the learning cycle and learning style in the of teaching around the learning cycle. from the perspective 3). The experiential approach places the subject to be learned dynamic matching model of teaching around the learning cycle (Kolbdescribes et al. four common educator roles: FacilitaThe KERP in the center to be experienced by both the educator and 2014). In our interviews and observations of highly successful we Standard-Setter/Evaluator, and Coach. tor,educators, Subject Expert, learner. Using the cycle of learning, all participants receive find that they tend to organize their educational activities inTosuch mannermove around the learning cycle, educators helpalearners information through concrete experience of the subject that they address all four learning cycle modes—experiencing, reflecting, must adapt their role, moving from Facilitator to Subject matter and transform it through reflection and conceptuthinking, and acting—using some form of the dynamic matching Matter model Expert in to Standard-Setter/Evaluator to Coach, as alization and then transform it again by acting to change the roles they adopt. We developed a self-assessment instrument the4. shown called in Figure the world including what information is attended to in Kolb Educator Role Profile (KERP) to help educators understand own • their The Facilitator Role. When facilitating, educators the new experience. They are both receivers of informateaching approach from the perspective of teaching around the learning helpcycle. learners get in touch with their personal expetion and creators of information. This has a leveling effect The KERP describes four common educator roles: Facilitator,rience Subject and reflect on it. They adopt a warm affirmon relationships, to the extent that all can directly experiExpert, Standard-Setter/Evaluator, and Coach. To help learners move around ing style to draw out learners’ interests, intrinsic ence the subject. Everyone has a perspective on the subject. the learning cycle, educators must adapt their role, moving from Facilitator motivation, and self-knowledge. They often do this Those with different learning styles, for example, will view to Subject Matter Expert to Standard-Setter/Evaluator to Coach, as by shown in facilitating conversation in small groups. They the subject experience through their own way of processFigure 4. create personal relationships with learners. ing experience. Questioning differences that arise from • The Subject Expert Role. In their role as subject these multiple perspectives is the fuel for learning and new expert, educators help learners organize and connect insights. Challenging the expert’s viewpoint even becomes their reflections to the knowledge base of the subject Vol. 1, No. 1 (2017) 17 possible. This can be quite unsettling to novice experienmatter.

They adopt an authoritative, reflective style. tial educators, but it also becomes a source of unpredictThey often teach by example, modeling and encourable new insight and learning for them. In becoming an aging critical thinking as they systematically orgaexperiential educator with this approach, the teacher also nize and analyze the subject matter knowledge. This becomes an experiential learner. Parker Palmer (1998), a knowledge is often communicated through lectures strong advocate for the subject-centered approach, put it and texts. this way: • The Standard-Setter/Evaluator Role. As a standard The subject-centered classroom is characterized by the fact setter and evaluator, educators help learners master that the third thing (the subject) has a presence so real, the application of knowledge and skill in order so vivid, so vocal, that it can hold teacher and students to meet performance requirements. They adopt alike accountable for what they say and do. In such a classan objective results-oriented style as they set the room there are no inert facts. The great thing is so alive knowledge requirements needed for quality perforthat teacher can turn to student or student to teacher, mance. They create performance activities for learnand either can make a claim on the other in the name of that great thing. Here teacher and students have a power ers to evaluate their learning.

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Experiential Learning Theory as a Guide for Experiential Educators in Higher Education Kolb & Kolb

keting advertising/promotion class.

They addressed the shortcomings they saw by emphasizing two principles. First, they created a teacher/ learner relationship that partnered with learners to facilitate their engagement with the learning cycle instead of the traditional information transfer approach as described above: “Educators have spent their time ‘parroting’ the instructional approaches of other teachers rather than ‘partnering’ experience and knowledge as intended by experiential learning models and the traditional laboratory method” (32).

Second, they created a laboratory experience in marketing classrooms that went beyond a single concrete application experience to create a course structure that spiraled through nine iterations around the learning • The Facilitator Role. When facilitating, educators help learners get in cycle. The text assignments and lectouch with their personal experience and reflect on it. They adopt a warm • The Coaching Role. In the coaching role, educa- tures were integrated with experiences generated from two affirming style to draw out learners’ interests, intrinsic motivation, and tors help learners apply knowledge to achieve their types of learning tasks, multiple group projects and mulself-knowledge. They often do this by facilitating conversation in small goals. They adopt a collaborative, encouraging style, tiple individual case studies. The traditional performance groups. They create personal relationships with learners. often working one-on-one with individuals to help evaluations (multiple choice and essay exams) were elim• The Subject Role. In their subject expert, educators help to give central focus on the recursive inated altogether them learnExpert from experiences in role theiraslife context. learners organize andcreation connect of their reflections to the knowledge base ofdiscussion, feedback, and hands-on expecycle of lecture, They assist in the personal developthe subject They adopt reflective style.At They riences. the ofcompletion of the course, students reported ment plansmatter. and provide waysan ofauthoritative, getting feedback ten by example, modeling and encouraging criticalincreased thinkinglevels as they of critical thinking abilities and the capaconteach performance. systematically organize and analyze the subject matter knowledge.

This ity to apply and connect theoretical knowledge with realMost of us adopt each of these roles to some extent knowledge is often communicated through lectures and texts. in our educational and teaching activities. This is in part life business application.

A. Lengnick-Hall and Martha M. Sanders because roles are determined by the As waya we resolvesetter Cynthia • Thethese Standard-Setter/Evaluator Role. standard and evaluator, (1997) designed fundamental dilemmas of education. we focus of onknowledge educators help learners master theDo application and skilla learning system for graduate and undergraduate-level management courses structured around the learner’s experience interest orrequirements. on subject matter in order to meet and performance They adopt an objective the learning cycle requirements?

Do westyle focus on effective performance results-oriented as they set the knowledge requirements needed for to give students with different learning styles variety of qualityorperformance.

They create performance activities for alearners toways to master each segment of the course and action on a deep understanding of the meaning evaluate their learning. of ideas?

All are required for maximally effective learn- material. Results indicate that despite wide variety in their ing. Individuals, however, tend to have a definite prefer- learning styles, experiences, academic levels, and interests, ence or Atwo rolesforover the others because of their students demonstrated consistently high levels of personal 18 for one ELTHE: Journal Engaged Educators educational philosophy, their personal teaching style, and effectiveness, organizational effectiveness, ability to apply the requirements of their particular educational setting, course materials, and satisfaction with both course results including administrative mandates and learner needs. The and the learning process. The study also showed learnKERP assessment instrument is designed to help educa- ing style differences in student ratings of various outcome tors sharpen their awareness of these preferences and to measures; divergent learners rated their personal effectivemake deliberate choices about what works best in a specif- ness higher than the non-divergent learners, while assimic situation. (The KERP is a free assessment available at ilating learners rated the lowest on the same outcome measure. Converging learners, on the other hand, rated survey.learningfromexperience.com). their ability to apply course material significantly higher Learning Cycle Applications in Higher Education than did the non-converging learners, an indication of their Dissatisfied with the application of experiential meth- tendency to seek out opportunities to apply what they have ods in the business classroom, Barbara Dyer and David learned. Looking at the positive learning outcomes generW. Schumann (1993) developed an experiential learning ated by the courses, the authors contend that high-quality laboratory classroom applied to their senior-level mar- learning systems are the ones in which extensive individFigure 4. Educator Roles and Teaching around the Learning Cycle.

Reflective Observation

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Experiential Learning Theory as a Guide for Experiential Educators in Higher Education

ual differences are matched with a variety of options in learning methods, thus creating opportunities for student behavioral, emotional, and intellectual transformation of lasting impact.

The Engineering and Technology College at Brigham Young University undertook a systematic change effort to introduce the ELT teaching around the learning cycle model to the faculty and conducted training sessions for the faculty in the use of the model (Harb et al. 1995). They developed sample curricula for teaching around the cycle that addressed questions posed by each quadrant of the learning cycle: Why, What, How, and What If. They followed a systematic change process for teacher development that involved 80% of the faculty for an introductory session and 35 faculty volunteers for the program. The program involved course development training and implementation of fall-semester course designs that were evaluated by videotaping and review sessions by the faculty support groups. One faculty member evaluated the program as follows: My effort as a faculty member to pass through the four types of learning activities has definitely increased.… The four-step process is definitely a practical and simple reference frame to use as a skeleton for any concept, technique or principle that needs to be taught. I believe that even though all of us as faculty and students may tend to have a dominant learning style, my experience has shown me that providing learning experiences in all four of the quadrants enhances learning for just about every person no matter what his dominant or preferred learning style quadrant may be. As a result, my effort in designing learning activities is much more diverse than it was previously. (64)

Learning Style

The ELT concept of learning style and the Kolb Learning Style Inventory (KLSI) are also widely known and used in higher education, although the unique message of the experiential learning concept of learning style has been diluted by the presence of the many trait-based learningstyle instruments that have emerged since the term and KLSI instrument were introduced in the late 1960s (Kolb, Rubin & McIntyre 1971). Since then, over one hundred other learning-style frameworks and assessments have been created, assessing a wide spectrum of human individuality—cognitive styles, preferences for sense modalities, Jungian personality types, study strategies, instructional preferences, preferences for learning alone, in groups, etc. While this is a testament to the multi-dimensional uniqueness of individual learners, the theory base and research evidence for these different learning-style frameworks vary widely. Consistent with the prevailing psychometric tradition, they describe learning styles as independent fixed traits or personality characteristics. Catherine Scott (2010), citing Carol Dweck (2007), argues that this

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trait approach is an “entity approach” to ability that promotes stereotyping and labeling rather than a “process approach” that emphasizes developmental potential and contextual adaptation. Trait-based learning-style frameworks advocate a matching model of education where it is hypothesized that instructional methods that match a student’s learning style will result in greater learning, an approach that is contrary to the ELT approach to teaching around the learning cycle described above. There has been substantial critique of this matching model with few empirical studies supporting it (Cuevas 2015; Pashler et al. 2008). Unfortunately, these critics do not recognize the uniqueness of the ELT learning-style model and lump all learning-style models together to argue that the concept of learning style in general is useless.

ELT posits that learning style is not a fixed psychological trait but a dynamic state resulting from synergistic transactions between the person and the environment.

This dynamic state arises from an individual’s preferential resolution of the dual dialectics of experiencing/ conceptualizing and acting/reflecting. Learning styles are, thus, different ways that individuals use the learning cycle. Experiencing, reflecting, thinking, and acting are not separate, independent entities but inextricably related to one another in their dialectic opposition. They are mutually determined and in dynamic flux. For the learning cycle, this means that there is not just one way to go through the learning modes but many different ways that vary for different individuals and their learning tasks.

For learning style, this means that an individual’s style of learning is not an independent personality trait but a habitual process of learning that emphasizes some learning modes over others. This recognition of a style preference as emphasizing strengths in some learning modes as well as some weaknesses in opposite modes opens development potentialities and the challenge of full-cycle learning to develop the ability to engage all modes of the learning cycle in a holistic and fluid manner.

The New Nine Learning Style Typology and Learning Flexibility in the KLSI 4.0

The latest version of the KLSI (Version 4.0—Kolb & Kolb 2011, 2013) was designed to clarify the dynamic relationship between the learning cycle and learning style through a refined definition of the different kite shapes that portray typical interdependent preferences for the four modes of the learning cycle. In addition, the concept of learning flexibility is introduced, allowing learners to assess their ability to engage all modes of the learning cycle as the situation dictates. The learning style types can be systematically arranged on a two-dimensional learning space defined by the Abstract Conceptualization-Concrete Experience and Active Experimentation-Reflective Observation dimensions of the learning cycle (see Figure 5).

Experiential Learning Theory as a Guide for Experiential Educators in Higher Education

Experiential Learning Theory in Higher Education

The Initiating style is characterized by the ability to initiate action in order to deal with experiences and situations. It involves active experimentation (AE) and concrete experience (CE).

Figure 5. The nine learning styles in the KLSI 4.0

The Experiencing style is characterized by the ability to find meaning from deep involvement in experience. It draws on concrete experience (CE) while balancing active experimentation (AE) and reflective observation (RO).

The Imagining style is characterized by the ability to imagine possibilities by observing and reflecting on experiences. It combines the learning modes of concrete experience (CE) and reflective observation (RO).

The Reflecting style is characterized by the ability to connect experience and ideas through sustained reflection. It draws on reflective observation (RO) while balancing concrete expe- learning style type accurately describes how they learn most The Initiating style of is characterized theconsistent ability toin initiate action in to order to the time. Theybyare their approach learnrience (CE) and abstract conceptualization (AC). deal with experiences and situations.

It involves active experimentation (AE) ing. Others, however, report that they tend to change their The Analyzing style is characterized by the and ability to inteconcrete experience (CE). learning approach depending on what they are learning or grate and systematize ideas through reflection. It combines the situation they are in. They may say, for example, that reflective observation (RO) and abstract The conceptualizaExperiencing style characterized ability toand findanother meaning from theyisuse one style inbythetheclassroom at home tion (AC). deep involvement in experience.

It draws on concrete while with their friends and family.

These experience are flexible (CE) learners. balancing active experimentation (AE) and reflective (RO).

The Thinking style is characterized by the capacity for disciSince a specialized learning styleobservation represents an individu-

plined involvement in abstract and logical reasoning. It al preference for only one or two of the four modes of the Imagining is characterized the ability istolimited imaginetopossibilities by draws on abstract conceptualization (AC)The while balanc-stylelearning cycle, itsby effectiveness those learning observing and reflecting on experiences.

It combines the learning modes of ing active experimentation (AE) and reflective observa- situations that require these strengths. Learning flexibility concrete experience (CE) and reflective observation (RO). tion (RO). indicates the development of a more holistic and sophislearning process. It is based on the theory that if The Deciding style is characterized by the ability use theo-style ticated The to Reflecting is characterized by the ability to connect experience and people show systematic variability in their response to ries and models to decide on problem solutions coursessustained ideasand through reflection. It draws on reflective observation (RO) different contextual learning demands, one could infer a of action. It combines abstract conceptualization and concrete while (AC) balancing experience (CE) and abstract conceptualization higher level of integrative development because systematic active experimentation (AE).

(AC). variation would imply higher order decision rules or metaThe Acting style is characterized by a strong motivation cognitive processes (Kolb & Kolb 2009) for guiding behavfor goal directed action that integrates people and tasks. ior. A number of researchers have found Vol. 1,evidence No. 1 (2017) 23 to support It draws on active experimentation (AE) while balanc- this link between learning flexibility and integrative develing concrete experience (CE) and abstract conceptualiza- opment (Kolb 2015). tion (AC).

Garima Sharma and David A. Kolb (2010) found that The Balancing style is characterized by the ability to adapt by individuals with an analyzing learning style tended to be weighing the pros and cons of acting versus reflecting and the least flexible, suggesting that it is the orientation toward experiencing versus thinking. It balances concrete experi- abstraction and reflection characteristic of the analyzing ence (CE), abstract conceptualization (AC), active experi- learning style that leads to inflexibility. Since this is the mentation (AE), and reflective observation (RO). style that is the most favored and most developed in formal education systems, one might ask if this abstract approach is producing the unintended negative consequence of learning Learning Flexibility The KLSI 4.0 also includes an assessment of learning flex- inflexibility. Emphasis on conceptual learning at the expense ibility by measuring how individuals change their learn- of contextual learning may lead to dogmatic adherence ing style in response to different situational demands. The to ideas without testing them in experience, what Alfred learning style types described above portray how one pre- North Whitehead (1997) called “the fallacy of misplaced fers to learn in general. Many individuals feel that their concreteness.” Contextual learning approaches like expe-

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Experiential Learning Theory as a Guide for Experiential Educators in Higher Education

Kolb & Kolb

Figure 6. Backup Learning Styles for a Low and a High Flexibility Learner

find hooks into content for struggling students. We’ve riential learning (Kolbmore 2015),backup and situated learning show styles and (Lave hence a ers greater ability to move around the also found benefits for differentiation: teachers who assess & Wenger 1991) may help education to nurture integratlearning cycle. their own and students’ styles are typically more willing and ed learners who are as sensitive to context as they are to able to implement a wide variety of instructional strategies abstract concepts. in their classrooms.… Along with Bernice McCarthy and Learning Education Learning flexibility is the Style ability toApplications use each of the fourin Higher David Kolb, and supported by Robert Sternberg’s research, learning modes to move freely around the learning cycle and we’ve long argued that teaching to the full range of styles bettersuccinctly and more consistently leads to higher to modify one’s approach to learning the learn-Silveris far Matthew Perinibased andonHarvey have summarized the achievement across grade and content levels than confining stuing situation. Experiencing, acting educationalreflecting, value ofthinking, learningandstyle assessments: dents to a single style of instruction.

(Cited in Varlas 2010, 2) each provide valuable perspectives on the learning task in a way that deepens and enriches knowledge. When one Educators in higher education have used ELT learning style In our experience, learning-style assessments have proven to be wonderful tools can engage all learning styles in their learning process, they information to increase teaching effectiveness and maxifor promoting conversations about learning, building teachers’ and students’ are using the most powerful form of learning that we call mize student learning in a number of different ways (see metacognitive capacities, and helping teachers the relafull cycle learning. Learning flexibility broadens increasing the learn- student Kolb &engagement, Kolb 2006). Studies have investigated find hooks into content for struggling students.

We’ve also found forthe learning ing comfort zone and allows us to operate comfortably and tionship between student learningbenefits styles and differentiation: teachers who assess their own and students’ styles are typically effectively in more regions of the learning space, promoting environment of their academic field, examining the implimore willing and able to implement cations a wideforvariety of and instructional deep learning and development. academic professionalstrategies development. Other in their classrooms.…

Along with Bernice McCarthy and David Kolb, and style differwork has examined student and faculty learning In addition to providing a measure of how flexible one ences and how this information can be used to implement supported by Robert Sternberg’s research, we’ve long argued that teaching to the is in their approach to learning, the KLSI 4.0 also provides curricula and instructional methods appropriate to individfull range of styles far better consistently leads to higher achievement an indication of which learning spaceis they move and to inmore style of learning. third work of has examined different learning contexts—their backup learning styles. across grade and content levels thanual’s confining studentsA to a body singleofstyle relationships between specific learning styles and academic Figure 6 shows theinstruction. backup styles(Cited of Initiating and Balancin Varlas 2010, 2) ing for an Experiencing type with a low flexibility score and performance and skill development.

For learners, knowledge of their learning style is a useful the backup styles of Experiencing, Imagining, Balancing, Educators in higher education have used ELT learning style information Reflecting and Thinking for an Initiating learning style with tool for developing meta-cognitive learning skills (Kolb to increase teaching effectiveness and maximize student learning in a numa high flexibility score. High flexibility individuals tend to & Kolb 2009). This information can help learners better ber of different (seeability Kolbto & Kolbunderstand 2006). Studies have process investigated the as learners the learning themselves show more backup styles and henceways a greater move relationship the learning environment and theand appropriate use of learning strategiesofbased on the around the learning cycle. between student learning styles learning task and environment. When individuals engage in the process of learning by reflective monitoring of the Learning Style Applications 26 ELTHE: A Journal for Engaged Educators learning process they are going through, they can begin to in Higher Education Matthew Perini and Harvey Silver have succinctly summa- understand important aspects of learning: how they move rized the educational value of learning style assessments: through each stage of the learning cycle, the way their unique learning style fits with how they are being taught, In our experience, learning-style assessments have proven to and the learning demands of what is being taught. This be wonderful tools for promoting conversations about learncomparison can result in strategies for action that can be ing, building teachers’ and students’ metacognitive capacities, increasing student engagement, and helping teachapplied in their ongoing learning process. For example,

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Experiential Learning Theory as a Guide for Experiential Educators in Higher Education

John and Tanya Reese (1998) created “Connecting with the Professor” workshops to help law students bridge the differences between the learning spaces created by law school professors and their own learning space preferences resulting from their individual learning style. Recognizing that law school professors were unlikely to change their course and learning style, they worked with students to develop the learning skills needed to succeed in the learning spaces created by their professors. Another strategy was to supplement the learning space that is given with other spaces that suit the student’s style. For example, a person who learns best by imagining may want to form a group of classmates to talk about the material in the course, or a thinking style person may want to prepare in advance by reading about material to be covered in the course.

The latest learning style research in virtual learning spaces is adaptive learning systems that integrate learning style information with online learning programs. Early adaptive learning systems used learning style questionnaires to assess a student’s style and then presented instruction information in a way that matched that style. More recent research on automatic detection of learning styles gathers information from the students’ interaction with the educational system on an ongoing basis, allowing the system to adapt to student learning style changes in real time. Automatic detection of learning style is harder to implement, requiring determination of observable behaviors to track in order to get reliable information to build a model of the student’s learning style. Juan Feldman, Ariel Monteserin, and Analia Amandi (2015), however, report several studies where the automatic detection system achieved 70% to 90% accuracy when compared to learning style questionnaire responses.

Studies of these automatic learning style systems have discovered that a substantial number of learners do not have a stable, consistent learning style but show learning style flexibility, adapting their learning approach in different contexts and times. For example, Mario Soflano, Thomas M. Connolly, and Thomas Hainey (2015), in an adaptive game-based learning activity, found that while participants generally adopt the same learning style in the game as that recorded in the pre-assessment questionnaire, a substantial number change their learning style as the game progresses, usually in response to mistakes made. This learning style flexibility has also been shown in other studies. A study

by Carol Griffiths and Görsev Inceçay (2016) of Turkish students found that performance on an English proficiency exam was related to what they called “style stretching,” with high performers using a more eclectic range of styles. Other studies have shown that students change their learning style depending of the course they are in. Cheryl Jones, Kouider Mokhtari, and Carla Reichard (2003) examined the extent to which community college students’ learning style preferences vary as a function of discipline. They found

significant differences in students’ learning style preference across four different subject-area disciplines: English, math, science, and social studies. The results indicate that 83% of the students switched learning styles for two or more disciplines, suggesting that students are capable of flexing their learning strategies to respond to the discipline-specific learning requirements. Similarly, Quintana Clark, James L. Mohler and Alejandra J. Magana (2015) studied engineering students and found that 36% of the students used a different learning style studying mathematics and English.

A drawback of many of the adaptive learning system approaches is their reliance on the questionable approach of matching learning style and instructional method, as opposed to teaching around the learning cycle to develop all styles. An exemplary study from Finland, where experiential learning has a long history in higher education, created a learning style module that was integrated into the multimedia platform course management system used to teach a Master of Information Technology degree program (Hakala & Laine 2016). The learning style module was available to both the student and the educator and designed not to change the students’ learning environment to match their learning styles but to make it more diversified and versatile to expand learning style capabilities. Since the instructor has learning style information for all students, and students have their own scores, it is possible to have conversations requesting more attention to “my style,” and the student can work to deliberately expand his or her style capabilities by practicing a less preferred learning approach.

The ELT dynamic matching model of teaching around the cycle offers the experiential educator a more complex but more realistic model for guiding educational practice than do simple prescriptions to match teaching and learning style. In addition to considering the relationship between educator and learner, one must also consider the match of learning approach with the subject matter. Daniel T. Willingham (2005), in fact, considers this more important than matching learning and teaching style. All of this must be determined in the light of the multiple performance, learning, and development objectives of most educational activities. Professions with precise performance requirements such as surgery or software development may make the standard-setter/evaluator role paramount and require development of thinking, deciding, and acting learning styles.

Art education, on the other hand, may make the facilitator role paramount and require development of experiencing, imagining, and reflecting learning styles (Eickmann, Kolb & Kolb 2003). In addition to specialized academic training, teachers often have objectives concerning the growth and creativity of their students. In making students more “well-rounded,” the aim is to develop the weaknesses in the students’ learning styles to stimulate growth in their ability to learn from a variety of learning perspectives.

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Experiential Learning Theory as a Guide for Experiential Educators in Higher Education Kolb & Kolb

Figure 7 shows the nine-style expeFigure 7. Dynamic Matching of Educator Roles and Learning Style riential learning cycle and the corresponding educator roles that match them; for example, the coach role is the most appropriate for the experiencing, initiating, and acting styles, while the facilitator role connects with the experiencing, imagining, reflecting styles.

The dynamic matching model suggests that matching style with role is important to connect with and engage learners. Michael Raschick, Donald E. Maypole, and Priscilla Day (1998) find that social work students whose learning styles were similar to their field supervisors along the active experimentation-reflective observation continuum would rate their field experience with them higher. We suggest that the finding is most relevant for the supervisors at the beginning point of the learning cycle, when matching their teaching techniques to learners’ preferences offers encouragement to move through they learn, finding thosethat withmatching concretestyle learning the rest of the learning cycle. Individual learning styles The can dynamic matching model that suggests with styles role is important to connect with and engage learners.

Michael Raschick, be an entry point through which learners enter a particular are more learner-centered, preferring the facilitator role, Donald E. Maypole, andthose Priscilla Day (1998) learning find that social students while with abstract styles work are more subjectlearning space, but most learning requires that they continwhose learning styles were similar to their field supervisors along the active ue to actively move around the learning cycle using other centered, preferring the expert and evaluator roles (Kolb et experimentation-reflective observation continuum would rate their field al. 2014). both learners andforeducalearning styles to acquire increasingly complexexperience knowledge with them higher.However, We suggestwith thatpractice, the finding is most relevant and skills and capacity to adapt to the wider the demands of tors can develop the flexibility to use all roles and styles to supervisors at the beginning point of the learning cycle, when matching a given learning environment. While Figure 7their depicts an techniques create a more powerful and effective process of teaching teaching to learners’ preferences offers encouragement to move through restlearning. of the learning cycle. Individual learning styles can idealized sequential progression through the educator roles the and be an design entry point through which learners enter a particular learning space, and learning styles, in most cases, a curriculum will be based on a sequence of activities and instructional Learning Spaces 30 ELTHE: A Journal for Engaged Educators techniques that fits the subject matter and learning objecMany factors contribute to the creation of a learning space. tives that may or may not fit such an orderly progression. A learning space can be either facilitative to learning or a In considering a design, it is useful to consider for each hindrance: the physical space, the constraints of time, the segment the teaching role to adopt, the learning style that learner’s psychological state, institutional constraints and you want to engage, and the choice of instructional tech- policies and so on. The ELT dimensions of learning space nique best suited to the learning style and role. The dynam- include physical, cultural, institutional, social and psychoic matching model recognizes that not only educators have logical aspects and they come together in the experience of individual role preferences, and learners have preferred the learner (Figure 8). learning styles, but also that both can develop the capacity This concept of learning space builds on Kurt Lewin’s to adapt their respective roles and styles to one another and field theory and his concept of life space (1951). For the learning situation at hand.

Lewin, the person and the environment are interdepenExperiential education is a complex relational process dent variables, a concept Lewin translated into a maththat involves balancing attention to the learner and to ematical formula, B=f (p,e), where behavior is a function the subject matter while also balancing reflection on the of person and environment. As Alfred J. Marrow puts it, deep meaning of ideas with the skill of applying them. The “the life space is the total psychological environment which dynamic matching model for “teaching around the learn- the person experiences subjectively” (1969, 35). Teachers ing cycle” describes four roles that educators can adopt to objectively create learning spaces by the information and do so: facilitator, subject expert, standard-setter/evalua- activities they offer in their course, but this space is also tor, and coach. Using the Educator Role Profile, we find interpreted in the students’ subjective experience through that to some extent educators do tend to teach the way the lens of their learning style, attitudes, beliefs, and life

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Experiential Learning Theory as a Guide for Experiential Educators in Higher Education

ings about the unknown that lies ahead.

While the child may be scarcely able to hide his terror, the mature executive is probably able to mask or even deny his fear. For both, however, not knowing is the doorway to knowing, and to open the door is an act of courage.

As educators, our challenge is to recognize the hopes and fears of learners and to create a learning space that respects, supports, and empowers them to overcome fear and take courageous action toward mastery. In defining our approach to the socio-emotional factors in the creation of learning spaces (Baker, Jensen, & Kolb 2002), we have been inspired by the concept of hospitality as articulated by Henri Nouwen This concept of learning space builds on Kurt Lewin’s field theory and experiences. One’s position in a learning space defines their (1975) and Parker Palmer (1983, 1998). Calling on numerhis concept of life space (1951). For Lewin, the person and the environment experience and thus defines their “reality.” Lewin stress- ous biblical stories that emphasize welcoming the stranger, are interdependent variables, a concept Lewin translated into a mathematical es the importance for education learning they describe this formula, B=f (p,e), where behaviorof is adefining functionthe of person and environment.

As challenging and supportive learning space space in terms of the learner’s experience, “in the way that as one that welcomes the stranger in a spirit of hospitalAlfred J. Marrow puts it, “the life space is the total psychological environment ity where “students and teachers can enter into a fearless itwhich existsthe for person that person at that time.…

A teacher will never experiences subjectively” (1969, 35). Teachers objectively communication with each other and allow their respecsucceed in giving proper guidance to a child if he does not create learning spaces by the information and activities they offer in their tive life experiences to be their primary and most valuable learn to understand the psychological world in which that course, but this space is also interpreted in the students’ subjective experience source of growth and maturation” (Nouwen 60). child lives.…

To substitute for thatstyle, world of the individuthrough the lens of their learning attitudes, beliefs, and life experiences. al the world of the the physicist, or of experience anybody andAs an defines educator who embodies this spirit of hospitaliOne’s position in ateacher, learningofspace defines their thus else to be, not objective, (quoted Cart- ty, the Associate Dean of Mathematics theiris“reality.”

Lewin stressesbut thewrong” importance forineducation of Samuel definingDeVries, the wright andthat Technology learning1951, space62). in terms of the learner’s experience, “in the way it exists at Cuyahoga Community College, created giving an experiential forInthat that time.… teacheron willthenever succeed in proper “learning to learn” course focused on ourperson recent at research we haveAfocused characterguidance to a child if he does not learn to understand the psychological world students’ math learning identity from one of istics of learning spaces that maximize learning from expe- transforming in which lives.…principles To substitute for that them world ofanxious the individual inferiority (“I don’t do math”) to one of confident rience andthat havechild developed for creating the world of the teacher, the physicist, or fully of anybody is to be, (“I not can totally do math”) as well as improvself-efficacy (Kolb & Kolb 2005).

For aoflearner to engage in the else objective,cycle, but wrong” Cartwright 1951, in 62). learning a space (quoted must beinprovided to engage the ing students’ math learning performance in developmental our recent research we have focused on the characteristics of learning courses (Hutt 2007). four In modes of the cycle—feeling, reflection, thinking, and mathematics spaces that maximize learning from experience and have developed principles action. It needs to be a hospitable, welcoming space that is It is estimated that over 60% of the general populacharacterized by respect for all. The space should welcome tion suffers from performance-inhibiting anxiety related genuine conversation among equals.

It needs to be safe and to math. Students in postsecondary education are failing 32 ELTHE: A Journal for Engaged Educators supportive, but also challenging. It must allow learners to college developmental math courses at an alarming rate, be in charge of their own learning and allow time for the often exceeding 50%, leading to a shortage of people with the requisite level of math credits to complete a two-year repetitive practice that develops expertise. college degree. The degree completion rate among the twenty thousand-plus students in one community college Learning Space Applications was reported as low as 9% over a six-year period. in Higher Education Engagement in learning is inevitably fraught with emotions This staggering math failure statistic did not deter of hope and fear. The hope is for mastery and understanding DeVries from creating a trusting learning space that was and the empowerment it brings. The fear has many faces: to safe and inviting enough for his students to take risks and make a mistake, to fail, to look stupid, to be embarrassed abandon habitual behaviors, and negative feelings and and humiliated in front of others, even to question one’s perceptions related to math anxieties. He created a converpersonal identity and self-worth. No one is immune from sational learning group where students were encouraged to the tugs and pulls of hope and fear. The young child on the actively engage in self-reflection about their learning pracfirst day of school and the executive beginning a coaching tices and beliefs about themselves. The teachers modeled relationship both experience this paradoxical blend of feel- transformation leadership behavior, involving students in Figure 8. Dimensions of Learning Space

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is reading—receiving feedback (CE) and formulating perceptions (RO)—the other person is flexing—creating intentions based on those perceptions (AC) Experiential Learning Theory as a Guide for Experiential Educators in Higher Educationalternate and acting on them (AE).

As the exchange continues, both parties between reading and flexing (see Figure 9). purpose of conversation is learning.

In conversation, individual cycles of learning merge in a mutual exchange of speaking and listening. In listening, we experience the other and reflect on what they are saying. In speaking, we think and formulate intentions about how to respond and act to express them. David E. Hunt (1987) suggests that this is a learning spiral shared between individuals in human interaction. People relate to one another in a pattern of alternating “reading” and “flexing” that mirrors the experiential learning process. When one person is reading—receiving feedback (CE) and formulating perceptions (RO)— the learning space by being authentically present themVol. 1, No. (2017)person 35is flexing—creating intentions based on the1other selves. Through self-directed learning, students began to those perceptions (AC) and acting on them (AE). As the use inquiry, self-disclosure, conversation, and reflection to exchange continues, both parties alternate between reading discover things about themselves as learners. Self-examina- and flexing (see Figure 9). tion allowed students to learn to manage the motivation Making space for conversation can take many forms: and volition necessary to persist through difficult courses. making physical space, such as when a manager moves from Self-directed learning behaviors (such as follow-through) behind his or her desk to join colleagues around a table; or self-defeating behaviors (such as procrastination or the making temporal space, such as when a family sets aside acting out of struggles with authority) were all topics of the weekly time for family conversation; or making emotioninquiry, with the students themselves being the subjects of al space through receptive listening. It is easy to become their discoveries. so focused on the conversation itself, on what is said, and Results from DeVries’s research (Hutt 2007) showed that how speech flows from one participant to another, that one the experiential course content, teachers’ conscious atten- fails to notice the bounded space that holds and shapes the tion to students’ learning processes and students’ reflec- conversation. Conversation cannot exist without a receptive tions on their learning experiences had a positive impact space to hold it. A conversational learning space has two on learning. Students’ mathematics anxiety was reduced, faces—boundaries that define and protect a conversational and they felt safer, more confident, and efficacious about space and the internal processes such as group composition, themselves as learners. Students in the “learning to learn” rituals and norms that shape the conversational interaction. course performed a letter grade better than controls in their As conversations progress, these processes shape the converdevelopmental math course. Students’ learning style prefer- sation and at the same time define boundaries that define ences played an interesting role in the findings. Typically in the space. These processes determine what can be said and mathematics courses, students with an abstract “thinking” not said, what and who is heard and not heard, who has learning style preference, which tends to match that of their voice and who does not have voice in the conversation. At instructor’s teaching style, perform better than students the same time, the processes create boundaries that define with other learning styles. This learning style difference was who is in and who is out of the conversation. There is a erased for students in the experiential course where students paradoxical quality to conversational boundaries. Converof all learning style preferences earned better grades than sation across boundaries is difficult, and boundaries can controls. DeVries maintained that to effect such change in block conversation, yet the space created inside the boundstudents’ belief about themselves as learners, teachers need aries can create enough safety for the open exploration of to create a safe learning space characterized by uncondi- differences across various dialectical continua. “From this tional positive regard toward the students (Rogers 1951). perspective, boundaries are not confines but ‘shape-givers’ Equally important is the creation of learning spaces that that can provide us with healthy space to grow.… [B] stimulate inquiry, open minds, and create good learning oundaries are not prisons, rather, they serve an essential conversations, enabling participants to move from the expe- function to make our existence more alive and vibrant” rience to deep reflection, conceptualization, and action. (Wyss-Flamm 2002, 315).

Conversation is the most ubiquitous and common form In Conversational Learning (Baker, Jensen & Kolb of experiential learning. Indeed, one could say that the 2002), we described the conversational learning space as Figure 9. The Conversational Learning Cycle

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defined by five dialectic dimensions. Good conversation is more likely to occur in spaces that integrate thinking and feeling, talking and listening, leadership and solidarity, recognition of individuality and relatedness, and discursive and recursive processes. When the conversational space is dominated by one extreme of these dimensions (for example, talking without listening), conversational learning is diminished. Dialectical inquiry aspires to holism through the embracing of differences and contradictions. It begins with contradictions, or literally “opposing speeches.” By taking the most opposite imaginable point of view, one increases the chance of encompassing the whole situation.

The dialectical dimensions of the conversational space can open a conversational process where opposing ideas can be explored, resolved, or embraced.

As an example of application of conversational learning in the educational practice, we cite the institution-wide introduction of an experiential seminar-based curriculum for undergraduates at Case Western Reserve University. Introduced as a pilot program in 2002, the program known as SAGES (Seminar Approach to General Education and Scholarship) was an ambitious undergraduate reform initiative based on the philosophy of experiential learning. The reform was not a radical change, but, for better or worse, was introduced within the confines of the traditional block scheduled course/credit-hour curricular system. Like most major curricular reform projects, it initially was met with resistance from various stakeholders of the university; that is, the expanded general education requirements of the SAGES Program cut into credit hours that professional schools and departmental majors wanted to keep in their control for their programs. The change process required major negotiation and compromise to gain approval but was eventually fully implemented to the universitywide undergraduate education curriculum at Case in the fall of 2005. Thanks to an inclusive and respectful planning process that stayed squarely focused on the SAGES vision, the curriculum has continued to evolve from the specifics of the pilot program and it continues in its basic outlines to this day.

CWRU President Hundert, in his address to the SAGES faculty in 2005, summarized the educational vision and philosophy embraced by core SAGES faculty reformers and their rationale for embracing an experiential learning approach to seminar education: Achieving higher-order intellectual skills is not easy to do alone or even in peer groups, whether in science or the humanities. Students need support and confidencebuilding to master and apply abstract concepts, to question familiar ideas, and to solve complex problems. Too often, traditional university teaching encourages students to “borrow” understanding from the professor or textbook long enough to pass an exam. At Case, we want the students to build understandings and cultivate skills

that they will retain for the rest of their lives. This kind of knowledge cannot be acquired passively, by listening to lectures.

Students create knowledge for themselves by building on what they already know. They each have their own personal ecology of learning, their individual toolkit of learning skills. But their continuing development as learners and thinkers requires active engagement in a supportive social setting; hence the seminar format. For most students, the traditional lecture format supplies answers too readily, short-circuiting their need to coordinate their own performance and cognition. Although students welcome it, traditional, authoritative, “professorial” intervention unwittingly undermines most students’ efforts to develop the patience, self-confidence, and persistence they need to create complex representations and abstractions. (Kolb et al. 2005)

From the very beginning, SAGES instructors aspired to create an opportunity where all seminar participants worked together to produce a collective team product through conversation. For such a teamwork experience to emerge, it required significant time and effort from all the seminar participants to engage in discussions with openness to diversity of views and willingness to critically re-examine their previously held world views. As the SAGES pilot case exemplifies, the ideal SAGES seminar learning space was kept alive and sustained by continuous back-and-forth movement of the principles of conversational learning as students and instructors committed themselves to creating knowledge together by building on each other’s ideas and perspectives.

Seminar sections that reported high levels of satisfaction at the end of the semester shared a common trait: students could point to the specific learning outcomes derived from their participation in the seminars. Those outcomes were broadly of three distinct levels: first, they became able to look at the world at large or at a particular phenomenon from different perspectives; second, the seminar experience helped them discover their own interests and feel inspired to pursue their line of inquiry on their own or continue to explore the topic in conversation with others; and third, learning was collective in nature and it was achieved when the entire class worked collaboratively to create knowledge together.

From the students’ perspective, the specific actions and behaviors instructors demonstrated in the seminars significantly contributed to the students’ positive learning experience. What follows are the summary of six critical actions seminar instructors exhibited in the seminars.

Not at the center of class. Participants reported having a positive experience in the seminars where instructors were not at the center of the class. Effective instructors were fully present in the class, skillfully deflected attention from themselves, and focused on opening and freeing the space for students’ expression of ideas and opinions.

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The instructor treats us as equals. In an engaging seminar, instructors maintained an egalitarian stance toward students. In students’ perception, equality was related to the degree to which their opinions and points of view were respected and valued on various decision-making processes of the course, such as defining the readings and assignments. Instructors who treated students as equals expressed genuine interest in students’ personal lives and ideas.

Challenging and supportive. During the seminar sessions, it was very common for students to withdraw their first attempt to introduce a controversial idea or diverging opinion. In an engaging seminar, students reported that the instructor challenged them and held them accountable for their statements or questions in a supportive manner. The challenge and support were expressed as question, demand, or encouragement for the students to dig deeper into an idea or think through their line of arguments.

The instructor knows me. A typical undergraduate class is conducted in large lecture halls. Such a learning environment makes it virtually impossible for the instructors and students to engage in a one-on-one interaction. In contrast, the small size SAGES seminars provided opportunities for instructors and students to relate in a much closer and intimate manner. Such a close instructor-student relationship was further enhanced by the intense advising process built into the SAGES curriculum. SAGES instructors not only could identify their students by their names, but they also came to know their students’ personal lives and aspirations at a much deeper level.

The instructor is knowledgeable. It mattered a lot to students that their teachers be knowledgeable. While the seminar format did not require instructors to give lectures or to deliver specific content on a regular basis, students greatly valued instructors’ command of areas of expertise that enhanced the quality of discussions.

Sustaining the seminar. It is not an easy task to maintain a high level of student engagement for a prolonged period of time in a seminar. Students’ energy level, interests, and attention span naturally tend to fluctuate over the life of the seminar. Seminar instructors played a fundamental role in sustaining a lively seminar atmosphere by providing a basic structure, guiding and sustaining students’ attention and focus by punctuating their experience, and finally by modeling an ideal seminar behavior.

Conclusion

We have described how experiential educators from many disciplines in higher education use core concepts of Experiential Learning Theory— the cycle of learning from experience, learning style, and learning space— to enhance their teaching effectiveness and increase student engagement and learning. Beyond these applications, we encourage educators to revisit the works of the foundational scholars of experiential learning described in Figure

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1. You will find that, far from being outdated relics of the last century, their insights offer great wisdom about all of the many problems that trouble higher education today.

As for the future, we believe that experiential learning will play a central role in transforming higher education in the face of the “creative destruction” of educational technology, providing a learning platform to rebuild the educational system to empower individual learners and build learning communities.

References

Arbaugh, J. B. and Alvin Hwang. 2015. “What Are the 100 Most Cited Articles in Business and Management Education Research, and What Do They Tell Us?” Organization Management Journal 12, no. 3: 154–75.

Arbaugh, J. B., Sarah DeArmond, and Barbara L. Rau. 2013. “New Uses for Existing Tools? A Call to Study Online Management Instruction and Instructors.” Academy of Management Learning & Education 12, no. 4: 635–55.

Baker, Ann C., Patricia J. Jensen, and David A. Kolb. 2002. Conversational Learning: An Experiential Approach to Knowledge Creation. Westport, CT: Quorum Books.

Bethell, Sally, and Kevin Morgan. 2011. “Problem-based and Experiential Learning: Engaging Students in an Undergraduate Physical Education Module.” Journal of Hospitality, Leisure, Sport and Tourism Education 10, no. 1: 128–34.

Bielefeldt, Angela R., Bruce W. Berdainer, Kevin M. Caves, Mandar M. Dewoolkar, and Kurtis G. Paterson. 2011. “Diverse Models for Incorporating Service Projects into Engineering Capstone Design Courses.” International Journal of Engineering Education 27, no. 6: 1206–20.

Boyatzis, Richard E., Scott S. Cowen, and David A. Kolb, eds.

1995. Innovation in Professional Education: Steps on a Journey from Teaching to Learning. San Francisco: Jossey-Bass.

Brower, Holly H. 2011. “Sustainable Development through Service-learning: A Pedagogical Framework and Case Example in a Third World Context.” Academy of Management Learning and Education 10, no. 1: 58–76.

Cartwright, Dorwin. 1951. Field Theory in Social Science: Selected Theoretical Papers. Chicago: University of Chicago Press.

Clark, Quintana, James L. Mohler, and Alejandra J. Magana. 2015.

“Learning Style Dynamics.” Presentation at the American Society for Engineering Education Conference, Seattle, WA. Cuevas, Joshua. 2015. “Is Learning Styles-based Instruction Effective? A Comprehensive Analysis of Recent Research on Learning Styles.” Theory and Research in Education 13, no.

3: 308–33.

Dewey, John. 1938. Experience and Education. New York: Simon and Schuster.

———. 1933. How We Think: A Restatement of the Relation of Reflective Thinking to the Educative Process. New York: D.C. Heath.

Dweck, Carol S. 2007. “The Perils and Promises of Praise.” Educational Leadership 65, no. 2: 34–39.

Dyer, Barbara, and David W. Schumann. 1993. “Partnering Knowledge and Experience: The Business Classroom as Laboratory.”

Marketing Education Review 3: 32–39.

Experiential Learning Theory as a Guide for Experiential Educators in Higher Education

Eickmann, Paul, Alice Kolb, and David A. Kolb. 2003. “Designing Learning.” In Managing as Designing: Creating a New Vocabulary for Management Education and Research, edited by Richard J. Boland and Fred Collopy, 241–247. Stanford, CA: Stanford University Press.

Feldman, Juan, Ariel Monteserin, and Analia Amandi. 2015. “Automatic Detection of Learning Styles: State of the Art.” Artificial Intelligence Review 44, no. 2: 157– 86.

Foy, Nancy. 1977. “Action Learning Comes to Industry.” Harvard Business Review 55, no. 5: 158–68.

Fuller, Ian C. 2012. “Taking Students Outdoors to Learn in High Places.” Area 44, no. 1: 7–13.

Griffiths, Carol, and Görsev İnceçay. 2016. “Styles and Style-Stretching: How are They Related to Successful Learning?” Journal of Psycholinguistic Research 45, no. 3: 1–15.

Gurpinar, Erol, Hilal Bati, and Cihat Tetik. 2011. “Learning Styles of Medical Students Change in Relation to Time.” Advances in Physiology Education 35, no. 3: 307–11.

Hakala, Ismo, and Sanna Laine. 2016. “Learning Styles Module as a Part of a Virtual Campus.” Conference paper, Kokkola Finland University.

Harb, John Naim, and Terry, R.E. 1995. Teaching through the Cycle: Application of Learning Style Theory to Engineering Education.

Provo: Brigham Young University Press.

Hunt, David E. 1987. Beginning with Ourselves in Practice, Theory and Human Affairs. Cambridge, MA: Brookline Books.

Hutt, Guy K. 2007. “Experiential Learning Spaces: Hermetic Transformational Leadership for Psychological Safety, Consciousness Development and Math Anxiety Related Inferiority Complex Depotentiation.” Ph.D. dissertation, Department of Organizational Behavior, Case Western Reserve University.

James, William. 1987. “Does ‘Consciousness’ Exist?” Writings 1902–1910. New York: Library of America. 1141–58.

Jones, Cheryl, Kouider Mokhtari, and Carla Reichard. 2002. “Are Students’ Learning Styles Discipline Specific?” Community College Journal of Research and Practice 27, no. 5: 363–75.

Keeton, Morris T., and Pamela J. Tate. 1978. Learning by Experience: What, Why, How? San Francisco: Jossey-Bass.

Keys, Louise. 1994. “Action Learning: Executive Development of Choice for the 1990s.” Journal of Management Development 13, no. 8: 50.

Kolb, Alice Y., and David A. Kolb. 2016. Experiential Learning Theory Bibliography: Volume 1-5 (1971–2016). Cleveland, OH: Experience Based Learning Systems, Inc. http://www.learningfromexperience.com ———. 2013. The Kolb Learning Style Inventory 4.0: A Comprehensive Guide to the Theory, Psychometrics, Research on Validity and Educational Applications. Boston: Hay Resources Direct. http:// www.haygroup.com/leadershipandtalentondemand ———. 2011. Learning Style Inventory Version 4.0. Boston: Hay Resources Direct.

———. 2009. “The Learning Way: Meta-Cognitive Aspects of Experiential Learning.” Simulation and Gaming 40, no. 3: 297–327.

———. 2006. “Learning Styles and Learning Spaces: A Review of the Multidisciplinary Application of Experiential Learning in Higher Education.” In Learning Styles and Learning: A Key

to Meeting the Accountability Demands in Education, edited by Ronald R. Sims and Serbrenia J. Sims, 45–91. New York: Nova Publishers.

———. 2005. “Learning Styles and Learning Spaces: Enhancing Experiential Learning in Higher Education.” Academy of Management Learning and Education 4, no. 2: 193–212.

Kolb, Alice Y., David A. Kolb, Angela Passarelli, and Garima Sharma.

2014. “On Becoming an Experiential Educator: The Educator Role Profile.” Simulation and Gaming 45, no. 2: 204–34.

Kolb, Alice Y., et al. 2005. Leading a SAGES Seminar: An Instructor’s Guide. Unpublished document, Case Western Reserve University.

Kolb, David A. 2015. Experiential Learning: Experience as the Source of Learning and Development. Upper Saddle River, NJ: Pearson Education.

Kolb, David A., Irwin M. Rubin, and James M. McIntyre, eds. 1971.

Organizational Psychology: An Experiential Approach. Englewood Cliffs, NJ: Prentice Hall.

Lave, Jean, and Etienne Wenger. 1991. Situated Learning: Legitimate Peripheral Participation. Cambridge: Cambridge University Press.

Lengnick-Hall, Cynthia A., and Martha M. Sanders. 1997. “Designing Effective Learning Systems for Management Education: Student Roles, Requisite Variety, and Practicing What We Preach.”

Academy of Management Journal 40, no. 6: 1334–68.

Lewin, Kurt. 1951. Field Theory in Social Sciences. New York: Harper & Row. March, James. 2010. The Ambiguities of Experience. Ithaca: Cornell University Press.

Marrow, Alfred Jay. 1969. The Practical Theorist: The Life and Work of Kurt Lewin. New York: Basic Books.

Mentkowski, Marcia. 2000. Learning that Lasts: Integrating Learning, Development, and Performance in College and Beyond. San Francisco: Jossey-Bass.

Nouwen, Henri J. M. 1975. Reaching Out: The Three Movements of the Spiritual Life. Garden City: Image Books.

Osland, Joyce S., David A. Kolb, Irwin M. Rubin, and Marlene E. Turner. 2007. Organizational Behavior: An Experiential Approach.

8th ed. Upper Saddle River: Pearson Prentice-Hall.

Palmer, Parker J. 1998. The Courage to Teach: Exploring the Inner Landscape of a Teacher’s Life. San Francisco: Jossey-Bass.

———. 1983. To Know as We Are Known: Education as a Spiritual Journey. San Francisco: Harper & Row. Pashler, Harold, Mark McDaniel, Doug Rohrer, and Robert Bjork.

2008. “Learning Styles: Concepts and Evidence.” Psychological Science in the Public Interest 9, no. 3: 106–19.

Prince, Michael J., and Richard M. Felder. 2006. “Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases.” Journal of Engineering Education 95, no. 2: 123–38.

Raschick, Michael, Donald E. Maypole and Priscilla Day. 1998.

“Improving Field Education through Kolb Learning Theory.”

Journal of Social Work Education 34, no. 1: 31–43.

Reese, John H. and Tanya Reese. 1998. Enhancing Law Students’ Performance: Learning Style Interventions. Saratoga Springs, NY: The National Center on Adult Learning, Empire State College.

Revans, Reginald W. 1980. Action Learning: New Techniques for Management. London: Blond & Briggs.

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THE COPPER BLACK AWARD Win cash for inventions, innovations, or unique improvements The Copper Black Award recognizes outstanding creative achievement by a member of American Mensa.

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Deadline for nominations is March 1 MensaFoundation.org/CopperBlack

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Rogers, Carl. 1951. Client-centered Therapy: Its Current Practice, Implications and Theory. London: Constable.

Schaefer, John J., Allison Vanderbilt, Carolyn L. Cason, and Deborah Navedo. 2011. “Literature Review: Instructional Design and Pedagogy Science in Healthcare Simulation.” Simulation in Healthcare 6, no. 7: S30–S41.

Scott, Catherine. 2010. “The Enduring Appeal of ‘Learning Styles.’” Australian Journal of Education 54, no. 1: 5–17.

Selingo, Jeffrey J. 2016. There Is Life After College: What Parents and Students Should Know About Navigating School to Prepare for the Jobs of Tomorrow. New York: HarperCollins. Kindle edition.

Sharma, Garima, and David A. Kolb. 2011. “The Learning Flexibility Index: Assessing Contextual Flexibility in Learning Style.” In Style Differences in Cognition, Learning and Management: Theory, Research and Practice, edited by Stephen Rayner and Eva Cools, 60–77. New York: Routledge.

Shields, Stephanie A., Matthew J. Zawadzki, and R. Neill Johnson. 2011. “The Impact of Workshop Activity for Gender Equity Simulation in the Academy (WAGESAcademic) in Demonstrating Cumulative Effects of Gender Bias.” Journal of Diversity in Higher Education 4, no. 2: 120–29.

Simosko, Susan A. 1988. Assessing Learning: A CAEL Handbook for Faculty. Chicago: Council for Adult & Experiential Learning.

Slavich, George M., and Philip G. Zimbardo. 2012. “Transformational Teaching: Theoretical Underpinnings, Basic Principles, and Core Methods.” Educational Psychology Review 24, no. 4: 569–608.

Soflano, Mario, Thomas M. Connolly, and Thomas Hainey.

2015. “An Application of Adaptive Games-based Learning Based on Learning Style to Teach SQL.” Computers & Education 86: 192–211.

Taylor, Anna-Sofia Alklind, Per Backlund, and Lars Niklasson. 2012. “The Coaching Cycle: A Coaching-byGaming Approach in Serious Games.” Simulation and Gaming 43, no. 5: 648–72.

Timken, Gay L., and Jeff McNamee. 2012. “New Perspectives for Teaching Physical Education: Preservice Teachers’ Reflections on Outdoor and Adventure Education.” Journal of Teaching in Physical Education 31, no.

1: 21–38.

Varlas, Laura. 2010. “Responding to the Research: Harvey Silver and Matthew Perini Address Learning Styles.”

Education Update 52, no. 5: 1–3.

Whitehead, Alfred North. 1997. Science and the Modern World. New York: Simon & Schuster.

Willingham, Daniel T. 2005. “Do Visual, Auditory, and Kinesthetic Learners Need Visual, Auditory, and Kinesthetic Instruction?” American Educator 29, no. 2: 31–35.

Wyss-Flamm, Esther Dorothea. 2002. “Conversational Learning and Psychological Safety in Multicultural Teams.” Ph.D. dissertation, Department of Organizational Behavior, Case Western Reserve University.

MRJ

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service Andrea Micheaux1 and Birgit Bosio2

Abstract As firms gather increasing amounts of data, the question of how future marketers can use these data to make their marketing more relevant and to make a strategic difference remains. However, students may feel uncomfortable about information systems and database technology, which they may perceive as complex and dry. This case describes how the development of a course on data-driven marketing makes use of service design methods. The experiential learning innovation is based on the optimization of customer journey mapping, which encompasses theoretical marketing concepts, modern database architecture and practical digital marketing knowledge. As a visualization of individual interactions with a product, service, or brand, customer journey mapping helps explain the way an interaction occurs in one moment and how it influences all other moments. By taking the “data as a service” perspective on the customer journey, students benefit from a more innovative and creative approach to data-driven marketing, which helps improve their attention and motivation.

CUSTOMER JOURNEY MAPPING is positioned in the American Marketing Association’s leading marketing publications as paving the way to the future of the customer experience (Lemon & Verhoef, 2016; Qaqish, 2018). Because the customer journey has always been central to data-driven marketing, this renewed focus confirms the importance of this discipline at the forefront of the marketing curriculum.

Since the late 1980s and early 1990s, marketing databases were created from customer data collected at the points of contact between the customer and the firm. At the time, only billing and some sparse customer data, such as the customer’s gender and postal code, but often not even his or her age, were available. Currently, data sources are vastly more abundant, largely due to the proliferation of digital channels and the touch points they generate. However, data are now considered a service, which is new.

Data provide a service to the customer. Using customer data to help the customer while making a profit represents a service for both the customer and the company and society. The use of data to produce relevant and timely marketing proposals is a service to the customer. The data serve the company through the revenues they generate and serve society through the employment they create. Datadriven marketing not only pays marketers’ salaries but also contributes to the salaries of all of the company’s employees. Thus, data should be a primary concern of marketers and all members of a company. However, they are not the focus of marketing students.

Teaching database marketing is difficult for two main reasons. On one hand, students, especially digital marketing students, are interested mainly in the creative and social media aspects of marketing. They are often more enthusias-

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tic about learning SEO (search engine optimization) than about how to integrate customer data into a database or how to organize data in the most operational form to drive personalized marketing and analytics, even if they soon discover during their internships that SEO involves a great deal of writing code on web pages. The second difficulty is teaching the subject of marketing technology (Martech) when it is evolving so rapidly. New acronyms are released almost weekly. There is a lively debate on whether the data management platform (DMP) should instead be called the customer management platform or whether a data lake should be included in the operational marketing database (OMDB). It is difficult for academic teachers to follow every new development. However, professionals, although they can distinguish between what is Martech hype and the fundamentals of data-driven marketing, which have remained unchanged for 30 years, may lack knowledge of marketing theory. In this regard, the challenges of datadriven marketing education are as follows: first, how to interest students in OMDBs; second, how to ensure that students can also learn the subject despite their different backgrounds, many of whom are not engineers or statisticians; and third, how to help academic professors cope with the changes brought about by Martech technologies.

Educators must teach the fundamental theory behind data1

IAE–University of Lille, Lille, France MCI Management Center Innsbruck, Innsbruck, Austria

2

Journal of Marketing Education 1–14 © The Author(s) 2018 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0273475318812551 journals.sagepub.com/home/jmd

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

driven marketing principles. Marketing students need to understand the relationship between marketing and data to contribute value and not lose their jobs to statisticians and mathematicians with no previous marketing education.

This article presents a course designed by a teacher with a hybrid background as a practitioner and an academic.

The professor, the lead author of this article, was in a privileged position to combine data-driven marketing practice with theory and to understand the difficulties encountered by educators in this area. The course focuses on the customer journey touch points. Each touch point is independent of the others regarding the data collected and the database processes entailed, which allows teachers to update the touch points as technology evolves. As the customer’s story unfolds, the accumulated data are enhanced and leveraged to improve the customer experience, which is achieved through the educators’ marketing knowledge and the skills acquired by the students.

In designing the course, the professor looked for customer journey engineering software. Smaply was chosen from the customer journey mapping tools reviewed by Ramshaw (2016). From a data service perspective, the service engineering software was the natural choice. Through two case studies detailed in this article, students developed personas and customer journey and stakeholder maps. The persona represents the customer, and the journey mapping represents the capture, ingestion and organization of data in the OMDB. Marketing theory and practice related to engagement and customer experience are associated with the customer journey (see Lemon & Verhoef, 2016, for a review of the theory). Stakeholder mapping provides an overview of how the different entities in the database are interconnected and how the different people and departments in the organization work together on the data.

The aim of this article is to present the course and offer it to other marketing educators on the creative commons principle. The course has been developed and taught to 344 students since 2016. Although there was no formal measure of program success, student feedback at the pedagogical meetings was positive, and the classroom experience was transformed. We show that the students’ learning path is in line with D. A. Kolb’s (1984) experiential learning theory (ELT). On one hand, students in data-driven marketing courses tend to have heterogeneous learning style profiles (D. A. Kolb, Boyatzis, & Mainemelis, 2001); on the other hand, the case steps we present are consistent with Kolb’s experiential learning spiral (A. Y. Kolb & Kolb, 2017), which could explain the success of the course and why it is interesting to share it.

The rest of this article is structured as follows. Borrowing from Crittenden and Crittenden (2015), we first explain what is taught in the data-driven marketing curriculum.

Then, we describe how the subject is taught. In the next

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two sections, we present the substance of the data-driven marketing course, first from a value perspective and then by addressing the role of data in the customer journey.

The service design method links the what and the how, as it provides the model for course design. We therefore explain the fundamentals of service engineering methods by reviewing the literature. Next, we detail how the course is taught by presenting each of the two case studies that provide the instructional material foundation. In the results section, we discuss how ELT supports the validity of this course. We conclude with how the course addresses managerial concerns and those expressed in the literature on digital marketing education. A service-oriented vision of data-driven marketing education is proposed.

The Value of Data-Driven Marketing in Times of Digital Disruption

The course presented in this article emphasizes the value of data-driven marketing in several ways. The value lies in the subject itself as an essential field of study for future entrepreneurs. The program aims to show students the value of their marketing knowledge to enrich the data. It aims to involve students in the data as an essential asset. Data are used to engage with the customer and, as a shared resource, with colleagues in their own department and other departments within the company.

Although the field of data-driven marketing is not new (Stephenson, 1989), companies are increasingly requiring marketers to analyze and interpret the large amount of data generated by digital conversations with customers (Gartner, n.d.). Database skills are among the most frequently required analytical skills for marketing graduates and are associated with higher salaries (Schlee & Karns, 2017).

However, students may feel uncomfortable with the technology they consider complex. They are not necessarily interested in the subject and may perceive it as dry. This attitude may mask a lack of self-confidence when compared with qualified statisticians who have spent 5 years of their curriculum analyzing data. Students learn to contribute to the value of the data in a meaningful way. This value lies in the student’s learned ability to apply his or her marketing knowledge to data use. Students can enhance the raw data by creating relevant marketing indicators from them and can find ways to use data to improve the customer experience. Additionally, they can contribute to improving the performance of the entire value chain by working with other colleagues on a common operational database (ODB).

Digital channels allow companies to collect a large amount of data on customer interactions with the company, its agents and products, as well as interactions between customers and other prospects or customers. However, the customer journey cannot be considered solely through the prism of digital marketing. Contact points can involve any

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

agent in the company, computer-tracked interactions with objects, interactions with points of sale and systems, and digital and direct contacts through the media. As all departments of the company are involved, the data are a common ground for collaboration. The course aims to provide students with the skills and tools they need for effective enterprise-wide collaboration on the optimal use of data, which includes working with data and systems specialists and managers at all levels and in all departments.

Recently, managers have moved away from using pure customer interaction data to using a corporate database that includes interconnected data from upstream and downstream value chain touch points and stakeholders (Fink, 2017). This company database becomes the basis for the functioning of the entire firm (Vergne & Blanc, 2016). For example, artificial intelligence is used by airlines for preventive maintenance. As a result, marketing managers are working increasingly closely with colleagues in other divisions of the company. They work together on a common real-time ODB, with the joint aim of optimizing the entire value chain.

each moment. Data-driven marketing is currently focused on the sequential nature of data collection, such as time series modeling. Time series modeling follows the approach that data have meaning only within a context and thus attaches contextual or geographic attributes using artificial intelligence or machine learning (Aoga, Guns, & Schaus, 2017; Tong, She, Ding, Wang, & Chen, 2016).

The concept of data contextualization is one of the main topics of the course. In terms of data capture and flow, this concept means attaching geographical and temporal attributes to the data.

Contextualizing data adds meaning, relevance, and value.

For example, a rail company’s text message is enhanced in value when placed in the context of place and time. The message “Would you like to change your ticket for the next train?” is valuable only if the customer is too far from the station to be able to take his train. If he is already at the station 15 minutes early, it still has meaning, but it is less important for the customer. If the customer has already changed his reservation, the message is no longer relevant.

The next day, it lacks meaning.

The Customer Journey as a Data Value Chain

Service Design as a Model for Developing a Data-Driven Marketing Course

Instead of teaching database logic and linking it to strategic and operational marketing, the approach adopts the customer journey perspective as a data value chain (Crié & Micheaux, 2006). For marketing professionals, the customer journey is based on the concept of “Moments of Truth” (Carlzon, 1987). These are key moments when the customer experience is decisive for the future of the relationship. Carlzon, then CEO of SAS Airlines, defined “50 million moments of truth” as the annual sum of the moments when an SAS agent is in direct contact with a customer. By empowering agents and refocusing the company on customer service, Carlzon significantly improved the company’s results, reducing costs while increasing customer and employee satisfaction.

Lafley (2005) subdivided the moments of truth into the first and second (FMOT, SMOT), representing the moment when the customer chooses a product in store and the moment when the customer tries the product at home, respectively. Lecinski (2011) preceded FMOT and SMOT by the “Zero Moment of Truth,” when, following an advertising stimulus, the consumer searches several channels for information on a product or service. These moments are again fragmented in the customer’s digital journey, which is composed of a chain of experiential “moments” made tangible by computer-tracked interactions. These moments now involve not only interactions with customers but also those with all stakeholders and processes along the value chain. Data can therefore be considered links that close the value chain.

The touch points on the customer journey maps are sequential and provide a context for what is occurring at

Service design thinking has helped marketers place the customer at the center of attention. Because customers are cocreators of their own experiences and of customer value (Teixeira et al., 2012; Vargo & Lusch, 2004), a customercentric marketing approach is crucial to delivering an optimal customer experience. Service design tools such as personas and customer journey and stakeholder maps (Stickdorn, Lawrence, Hormess, & Schneider, 2018) help marketers better understand customer behaviors, feelings, and needs.

Data-driven marketing is customer-centric because it is based on customer data. It was therefore appropriate to base the course on service design methods. The objective was to provide students with a practical experience of value creation opportunities based on data related to customer journey mapping. At the same time, students needed to understand the theoretical concepts that underlie the success of data-driven marketing, including digital engagement, involvement, behavioral and attitudinal forms of commitment, and the concept of consumer relationship quality (Fournier, 1998). By stimulating students in a holistic way with real tasks and tools, as part of a unifying customer journey project that can be implemented in a company, the class would be more dynamic.

Persona Development Personas, as used in marketing, embody a user-centered approach (Schäfer, Zinke, Künzer, Hofinger, & Koch, 2014). They were initiated by Cooper (1999) as a new way to create a hypothetical user. Personas provide a means

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Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

Micheaux and Bosio

5

Figure 1.

Figure 1. AAPersona’s Persona’scustomer customerjourney. journey.Note. The numbers represent the successive touch points associated with the persona in the service designrepresent software. a journeytouchpoints map, there may be with one the or several in each stage. Above, themay search Note.

The numbers theInsuccessive associated persona successive in the serviceinteractions design software.

In a journey map, there one or (in bold) is the only touch point represented atthe thesearch prepurchase While there are multiple at touch points within the While purchase several successive interactions in each stage. Above, (in bold) stage. is the only touchpoint represented the pre purchase stage. there(2a, are multiple within the purchase (2a, 2b,(3a, and3b, 2c) 3c, and and the post (3a, with 3b, 3c, and 3d). from Lemon and Verhoef (2016).

2b, andtouchpoints 2c) and the postpurchase stages 3d).purchase Source.stages Adapted permission Source. Adapted with permission from Lemon and Verhoef (2016).

interactions between different groups involved of and conveying a wide range the of qualitative and quantitative (Stickdorn & Schneider, 2011). data.

They draw attention to aspects of design and use, of stakeholders is created through desk research betterFirst, thana set other methods (Pruitt & Grudin, 2003). Some and interviews. Second, the interests and motivations of authors criticize personas andincorporated say that their can stakeholders are analyzed and into creation the map by lead to stereotypes (Turner & Turner, 2011).

However, establishing relationships between them and determining the Stickdorn al. (2018) propose persona is more nature of etthese relationships.

Thethat mapa can be drawn on aof background of embedded circles visualize the a research-based archetype.

Theto benefits of importance, using persoandhighlighted hierarchies ofinthe different relationship groups nasinfluence, have been the literature (Cooper, 1999; (van Oosterom, 2011). Stakeholder maps2011). help cluster the a Goodwin, 2008; Miaskiewicz & Kozar, Creating internal and external stakeholder groups involved by imporcharacter with a fictional name and background informatance and influence and make their interconnections visible tion can help&marketers designers develop greater empa(Stickdorn Schneider, or 2011). thy and a more intimate relationship with the customer (Schäfer al., 2014).

Members the marketing ServiceetDesign Models to HelpofStudents Learn team are easily engaged with these target consumers (Miaskiewicz Data-driven Marketing & Kozar, 2011). In addition, personas provide a common For for the collaboration design of the course, Smaply communication was used to simulate basis and internal at all the implementation of data-driven marketing in the retail levels of the company. Shared representation induces a clisector. The tool was chosen from the customer journey ent-centered perspective.

Although personaThe forprofesmarketmapping tools reviewed by Ramshawa (2016). ingsorpurposes may have different attributes than that chose Smaply because of its educational license andfor product development (Pruitt Grudin, 2003), all the academic background of its & founders.

In addition, as anthe SaaS (software a service), Smaplycombine required to only Internet attributes createdasby contributors form a sinstudents and was easy for the teacher to configgleaccess view for of the customer. ure. Two cases were produced with personas: the customer Since Cooper’s first raw sketches, personas have evolved into much more detailed characters that help make the needs of customers salient and intelligible. Personas are created from data collected from customer databases and through ethnographic methods such as interviews or observations (Pruitt & Grudin, 2003). Although the early persona data were mainly ethnographic, recent studies also use other methods, such as factor analysis (McGinn & Kotamraju, 2008) or grounded theory (Dupree, Lank,

28 • Mensa Research Journal

journey and 2018). stakeholder maps.typically The pedagogical is & Berry, Personas includeconcept demographic based on the story variables, of “Susie,”as who is taking her first steps and behavioral well as general information, as a new customer at a local bookstore. The data generated such as the user environment, current frustrations, releby Susie’s interactions with the brand initialize and enrich vant relationships, and goals (Goodwin, 2008;underStickdorn the OMDB. The data allow students to gain a better et al., 2018).

Datapersonality analysis can persona standing of Susie’s and identify tastes asdifferent her journey progresses. profiles (Cooper, 1999). The data collected throughout the The course designis was anchored in Lev Vygotsky’s customer journey therefore an integral part of persona Proximal Development Zone, one of the founding theories building. Personas thus provide a bridge between what from which ELT was developed (see A. Y. Kolb & Kolb, may appear to students a dry database technology 2017).

The service designastemplates were designed as and what interests them, that is, creative ideas in marketing. scaffolding to allow students to move from their native understanding the client’sofjourney, they hadcollecTherefore, theofenrichment personaswhich through data acquired during their digital marketing or consumer expetion and processing is a key part of the course. rience, to a higher level of skills. ELT defines learning as “the process whereby knowledge is created through the Customer Journey Mapping transformation of experience. Knowledge results from the Customer of journeys developed from a combination graspingare andgenerally transforming experience” persona (D. A. Kolb(Stickdorn 1984, p. 41).& Schneider, 2011). A customer journey is a (1971) sequence of a Style customer’s direct D. A. Kolb’s Learning Inventory (LSI)and was indideveloped from awith two-axis matrix: aservice verticalor “experiencerect contacts a product, brand (Meyer thinking” axis as2007), a grasping process a horizontal & Schwager, each of whichandconstitutes a posi“reflecting-acting” axis as a transformative process. With tive, negative or neutral experience (Berry, Carbone, & the abundance of literature and pedagogical practice, the Haeckel, 2002). The value of the customer experience at four basic learning styles (see McLeod, 2017, for a sumeach have touch pointinto influences relationship mary) evolved the KLSIthe 4.0,perceived which is based on

quality (Fournier, 1998), which in turn affects commitment (Palmatier, Dant, Grewal, & Evans, 2006). Contact points can occur in both online and offline channels (Meyer & Schwager, 2007). A customer journey map is structured as a sequence of phases. The customer experience at each of the preservice, service and after-service periods is influenced by past experiences and by one or more touch points during each phase, which influences the future experience (see Figure 1).

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Journal of Marketing Education 00(0)

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

Figure 2. The students’ journey follows the experiential learning spiral.

Note. The educator accompanies the students as they progress through the cases.

Source. Adapted with permission from A. Y. Kolb and Kolb (2017).

The customer journey varyform in scope. can be based nine learning styles, eachmay in kite (A. Y.ItKolb & Kolb, on hypotheses or research, can reflect the current or future 2017). In Figure 2, the learning styles are positioned in a state, be antooverview detailed, product-or expespiraland withcan respect the stepsor students take in the completion of the case TheetELT posits that a complete rience-based viewstudies.

(Stickdorn al., 2018).

Customer jourlearning process can begin from any point in a clockwise ney mapping thus follows the principles of service design by direction butthe that it must cover all from pointsservice at leastconsumponce. In sequencing encounters arising the following sections, we explain in detail how the tion, ranging from the first contact with the customerdatato a driven marketing course is taught in the two case studies. description of the service in its entirety. A customer journey Learning styles are indicated (in italics) in the description, map can include different types of information from the lead where they are most appropriate in relation to Figure 2. agent, a general description of touch points, storyboards, and graphic depictions of emotional journeys. Emotions are Case 1: Susie Begins Her Customer important for understanding where the customer is having Journey difficulties, for identifying gaps in the customer experience At first, the students know nothing about Susie,attributes except that and for exploring potential solutions.

Other of she has just moved to a new neighborhood and that the case the journey map may include information on the channels in point is herpoints neighborhood bookstore.

Students have arcs, two where contact are located, stakeholders, dramatic sources of data from which they can gain an idea of Susie’s backstage organizational processes, related tasks, and convercharacteristics and needs, as well as aspects of her personalsion funnels (Stickdorn al., 2018).

Customer journeys ity. The first source is an et extract from the bookseller’s sales have been applied mainly to marketing and service design system. The second source is a form that Susie only partially (Asbjørn & Knut, Rawson, Duncan, & Jones, 2013; fills out when she2018; logs in to activate her loyalty program Zomerdijk & Voss, 2011). However, journey mapping is membership. first glance, the data incomplete and scarce. notAtlimited to mapping the seem customer experience; it can However, as students connectorthe datastakeholders to Susie’s journey, also be applied to employees other (Bosio, they focus more on the2017; booksStickdorn Susie buys, she buys Rainer, & Stickdorn, et when al., 2018; van them and the online or physical store where she buys them.

Oosterom, 2011).

Stakeholder Maps Stakeholder maps are often used in addition to personas and customer journeys. A stakeholder map is a visual representation of the different individuals or groups involved in a service, as well as the relationships between these stakeholders.

Stakeholders may progresses, include staff,the customers, partner As the journey insight into the organizacharacter tions, company departments, or database entities.

By chartgrows. At the end of the first case, students understand the ing the and service environment in which the customer experipower potential of customer data. Ultimately, they know ence occurs, stakeholder map helps analyze theand respective much more aabout Susie through her purchases interactionsand with the brandbetween than through the information in her roles interactions the different groups involved member profile.

(Stickdorn & Schneider, 2011).

First,a set students align their own consumer experiences First, of stakeholders is created through desk research with Susie’s. After imagining the steps involved in her first and interviews. Second, the interests and motivations of purchase and joining the loyalty program, they build Susie’s stakeholders are students analyzedreflect and incorporated into the and maphow by journey. Then, on the data sources establishing relationships between them and determining they could be merged. With the help of the educator, they the naturethe of raw thesedata relationships.

The map be drawnthem on analyze and think about how can to organize the OMDB.ofThey decide circles which to aggregated to ainbackground embedded visualize variables the imporcreateinfluence, at the level of purchasing and customer database tance, and hierarchies of the different relationship entities.

They act on their ideas by writing the help data clusfrom groups (van Oosterom, 2011).

Stakeholder maps each step of Susie’s journey into the backstage process ter the internal and external stakeholder groups involved by lanes of the Smaply tool, which represents the BDMO. importance and influence and make their interconnections Finally, students describe how they plan to use the variables visible (Stickdorn & Schneider, 2011).marketing operations they create to initiate personalized that will enhance Susie’s experience. As illustrated in

Service Modelsprogress to Help Students Learncase one folFigure Design 2, the students’ in completing Data-driven Marketing lows the ELT learning spiral.

For By the completing design of the Smaply was(Figure used to thecourse, customer journey 3),simulate students learn the principles ofofODB architecture: the primary the the implementation data-driven marketing in thekey, retail levels The of aggregation and the between raw, sector. tool was chosen fromdifference the customer journey dummy, tools aggregated, andbycalculated They learn mapping reviewed Ramshawvariables.

(2016). The profeshow the data take on a different meaning depending on the sor chose Smaply because of its educational license and the academic background of its founders. In addition, as an SaaS (software as a service), Smaply required only Internet access for students and was easy for the teacher to configure. Two cases were produced with personas: the customer journey and stakeholder maps. The pedagogical concept is based on the story of “Susie,” who is taking her first steps Volume 52, Issue 3 • 29

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service Micheaux and Bosio

7

Figure 3. Students complete the customer journey by writing the data flowing from the touch points into the marketing database.

Figure 3. Students complete the customer journey by writing the data flowing from the touchpoints into the marketing database.

as a new customer atThey a local bookstore.

Thewith datadatabase generlevel of aggregation. become familiar ated by Susie’s interactions with the brand and processes that occur behind the scenes but thatinitialize are invisible to the customer.

By analyzing data, they gain a vision of enrich the OMDB. The data the allow students to gain a betthe customer experience.

Theypersonality also learn some purelyastechter understanding of Susie’s and tastes her nical aspects of databases, such as the solutions provided by journey progresses.

NoSql databases, to solve some of the difficulties associated The course design was anchored in Lev Vygotsky’s Proxiwith merging data of different formats into different levels of mal Development of the founding theories from aggregation.

The Zone, Smaplyoneweb application, a MongoDB which ELT was developed (see A. Y. Kolb & Kolb, 2017).

NoSql database, gives additional weight to these arguments.

The service design templates designed as scaffolding In this way, students can begin were to measure the impact of marto allow students to move from their native understandketing issues on technological decisions and consider their technical as theirwhich allies.they had acquired during ing of thecolleagues client’s journey, Next, students are asked to think about how Susie is contheir digital marketing or consumer experience, to a higher nected the bookstore’s backstage Which whereby database level oftoskills.

ELT defines learning systems. as “the process systems are isinvolved Susie’sthe customer journey? of How do knowledge created in through transformation expethese entities interact to enhance the customer knowledge rience. Knowledge results from the combination of graspthat marketers need to ensure optimal customer relationship ing and transforming experience” (D. A. Kolb 1984, p. 41). quality? These relationships are visualized and analyzed in a D. A. Kolb’s stakeholder map. (1971) Learning Style Inventory (LSI) wasUsing developed from a two-axis matrix:can a vertical “experithe stakeholder map, students take an architecence-thinking” axis as a grasping process and tural database perspective and collaborate witha horizontal their computer scientist counterparts a common process. representation. “reflecting-acting” axis as through a transformative With Students reflect of on literature the stakeholders that are provided. the abundance and pedagogical practice,They the analyze the potential relationships between stakeholders and four basic learning styles (see McLeod, 2017, for a summathink about how they linked to which each other.

Theyondecide ry) have evolved intocan thebe KLSI 4.0, is based nine on the type of relationship they should choose to describe learning styles, each in kite form (A. Y. Kolb & Kolb, each connection. They act by positioning stakeholder groups 2017). In Figure 2, the learning styles are positioned in a using the concentric circles on the map. This step initiates spiral with respect to the steps students take in the completion of the case studies. The ELT posits that a complete learning process can begin from any point in a clockwise direction but that it must cover all points at least once. In the following sections, we explain in detail how the data-

30 • Mensa Research Journal

driven marketing is taught in the two studies.the discussions.

For course the group of students whocase produced stakeholder map Figure 4,(in theitalics) customer database entity is Learning styles areinindicated in the description, the priority, information systems to colleague where they arewhile mostthe appropriate in relation Figure 2.might think that the administrative system is more important. This experience of comparing different points of view on database Case 1: Susie Begins Her Customer Journey and system priorities prepares students to collaborate with At first, the students know nothing about Susie, except that colleagues in the IT systems department. she has just moved to a new neighborhood and that the case in point is her neighborhood bookstore. Students Case A New Investor Takes Control have two 2: sources of data from which they can gain an idea of the Bookstore of Susie’s characteristics and needs, as well as aspects of her personality.

Thecase, first source is an extract from over the bookIn the second a new investor has taken Susie’s seller’s sales system.

The second source is a form that Susie local bookstore. Suddenly, direct and digital marketing takes only fills out Students when sheplay logsthe in role to activate her loy-of on apartially new dimension. of the manager theprogram bookstore.

To secure their position in the new company, alty membership. they must demonstrate the marketing value of and the data from At first glance, the data seem incomplete scarce. the customer journey.

To calculate the variables that will However, as students connect the data to Susie’s journey, make a difference in their data-driven marketing initiatives, they focus more on the books Susie buys, when she buys students must merge customer journey data from different them and the online physical store she champions buys them.of channels.

From thisorperspective, theywhere become Asthethe journey progresses, thearchitecture insight into(Gruhn, the character cause of modern database 2016). grows. the end ofofthe case, students understand TheAtarchitecture thefirst target OMDB includes a DMP to the power and potential of customer data.

Ultimately, they merge customers’ online and offline marketing interaction data. much The model, to students Case 2, reflectsand how know more provided about Susie throughinher purchases the data arewith derived from Susie’s journeythe to feed the target interactions the brand than through information The profile. customer journey represents Susie’s succesindatabase. her member sive interactions with eight channels (e-mail, customer First, students align their own consumer experiences forum, text messaging, call center, Facebook page, Facebook with Susie’s. After imagining the steps involved in her first purchase and joining the loyalty program, they build Susie’s journey. Then, students reflect on the data sources and how they could be merged. With the help of the educator, they analyze the raw data and think about how to organize them

8

Journal of Marketing Education 00(0)

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

Figure 4. Completing the stakeholder map for Case 1.

Figure 4. Completing the stakeholder map for Case 1.

Note.

Studentsdefine definethe therelationships relationships between stakeholders position atcenter the center Note. Students between thethe stakeholders and and position at the of the map the database entities which they feel are most of the map the database entities which they feel are most important. important.

application, mobile application, and aggregated web customer service). in the OMDB. They decide which variables to The data captured, processed, merged, and stored from these create at the level of purchasing and customer database interactions areact displayed the simulation as the backstage proentities.

They on theirinideas by writing data from cess lanes. each step of Susie’s journey into the backstage process lanes Students face a double challenge. First, they must enrich of the Smaply tool, which represents the BDMO. Finally, the database with the intelligent marketing variables they students describe howtechnical they plan to of useview, the they variables will create.

From this point must they concreate to chief initiate personalized marketing that vince the information officer that theseoperations variables are of will enhance Susie’s As illustrated in Figure 2, cross-channel origin,experience. which requires, on the one hand, the release of data from existing silos via DMP and the the the students’ progress in completing casetheone follows unique customer record and, on the other hand, the provision ELT learning spiral. of data as a servicethe in the synchronous they By completing customer journeyBDMO. (FigureSecond, 3), students must convince senior management that investment in the learn the principles of ODB architecture: the primary key, new architecture will be profitable. They must demonstrate the of aggregation and service the difference between howlevels marketing and customer operations, whichraw, are dummy, aggregated, and calculated variables.

They learn driven by the new variables, will increase Susie’s level of how data take on different meaning on digitaltheengagement anda commitment.

Only depending then can they the leveltheir of aggregation.

They promoted become familiar with datasecure careers by being to the position of chief processes data officer. base that occur behind the scenes but that are Susie’stointeractions withBy theanalyzing channels the are data, captured the invisible the customer. theybygain various digital marketing and customer service applications. a vision of the customer experience. They also learn some Platforms such asaspects the campaign management mobile purely technical of databases, such assystem, the solutions application platform, or call center system generate data in provided by NoSql databases, to solve some of the difficulsilos. Data from digital and Customer relationship manageties with merging data ofand different formats mentassociated (CRM) sources are merged integrated viainto the different levels of aggregation.

The Smaply web application, unique customer record and the DMP to the OMDB entities. aUnstructured MongoDB data, NoSql database, gives additional weight to such as the review Susie left on the custhese this way, students measure tomerarguments. forum, areInintegrated into the can databegin lake to along with semistructured data, such issues as webon browsing logs, and mirror the impact of marketing technological decisions copies of structured data, such as interaction events (clicks, and consider their technical colleagues as their allies.

Next, students are asked to think about how Susie is connected to the bookstore’s backstage systems. Which database systems are involved in Susie’s customer journey?

How do these entities interact to enhance the customer knowledge that marketers need to ensure optimal customer

openings, etc.).

The These way data are collected, andand interelationship quality? relationships are merged visualized grated is written into the model.

The data appear in the varianalyzed in a stakeholder map. ous entities of the BDMO. Color coding allows students Using the stakeholder map, students can take an archi- to see how the processes interact with Susie and with each tectural database perspective and collaborate with their other. Facebook is presented as an external platform. Figure computer scientist counterparts through a common repre5 shows how students click on the interactive customer joursentation. reflect on the that are ney modelStudents to visualize the data and stakeholders processes resulting from provided.

They interactions analyze the potential relationships the personas’ with the direct, digital, between and social stakeholders and think about how they can be linked to marketing channels. mustdecide examine when pereachStudents other. They on the the data typetoofdetermine relationship they sonal choose information is collected consider They personal data should to describe each and connection. act by protection stakeholder and explicitgroups consent.

For the example, Susiecircles cannot positioning using concentric geolocated has given her permission, that is, onbethe map. Thisuntil stepshe initiates discussions.

For the group she downloads the mobile application. interacofwhen students who produced the stakeholder mapSusie’s in Figure 4, tions with the Facebook page are recorded only once Susie the customer database entity is the priority, while the inforaccepts Facebook login access to the “Harry Potter game.” mation systems colleague mighttothink thatdid thenot administraSusie calls customer service say she receive the tive system is more important.

This experience of book she ordered. The call center agent then comparing searches the different points of view and system priorities catalogue for the book on anddatabase sends another one. In this way, prepares to collaborate with marketing colleaguescannot in the funcIT studentsstudents understand that data-driven tion indepartment. isolation from other internal processes. The ODB systems involves the entire company, just as all departments contribute to2: theAperceived quality ofTakes Susie’s journey.

Case New Investor Students are assigned tasks Control of the Bookstore through which they develop defend their business case has for the investment in the Inand thethen second case, a new investor taken over Susie’s new database architecture.

The learning path in case two local bookstore. Suddenly, direct and digital marketing begins with Susie’s journey experience. Students simulate a takes on a new dimension. Students play the role of the customer survey by imagining Susie’s perceptions at each manager of the bookstore. To secure their position in the point of contact if only silo data can be used to customize new company, they must demonstrate the marketing valSusie’s experience. The perceptions are reported by adding ue of the data from the customer journey. To calculate the variables that will make a difference in their data-driven marketing initiatives, students must merge customer journey data from different channels. From this perspective, they become champions of the cause of modern database architecture (Gruhn, 2016).

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Micheaux and Bosio

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

9

Figure 5. Students click on the interactive customer journey template to visualize the data and the processes flowing from the persona’s interaction with the direct, digital, and social marketing channels.

anThe emotional journey to the existing journey map.

Students architecture of the target OMDB includes a DMP to spend time reflecting on how aremarketing generated from Susie’s merge customers’ online and data offline interaction interactions and analyzing they flow the sysdata.

The model, provided how to students in through Case 2, reflects tem.

For example, they can see how, at Contact Point how the data are derived from Susie’s journey to feed the1 (Figure 5), the campaign management platform interacts target database. The customer journey represents Susie’s with the digital asset management platform to show the successive interactions with eight channels (e-mail, customimages in the newsletter. At Contact Point 2 (Figure 6), stuer forum, text messaging, callintegrates center, Facebook dents can learn how the DMP the clickpage, eventFaceof the book application, mobile application, and web customer CRM campaign into the CRM history database entity, while service).

The to data processed, merged, and stored Susie’s visit thecaptured, online store is recorded in a different forfrom interactions are displayed in the simulation as mat inthese the e-store visits entity.

As they think lanes. about the data, students gain additional backstage process insights intoface Susie, who now clearly First, appears to must be a working Students a double challenge. they enrich “digital mom.”

Although she is an enthusiastic reader, Susie the database with the intelligent marketing variables they does not seem to be committed to her relationship with the will create. From this technical point of view, they must bookstore. She is more involved with the authors of the convince the chief information officer that these variables books she reads. Students use this knowledge to decide are of cross-channel whichfrom requires, on the one which variables they origin, can calculate the contextualized hand, thecould releasetrigger of data from existing via the Susie’s DMP data that marketing actionssilos to improve and the uniquelevel. customer record and, ongroup the other hand, the commitment For example, one imagined that provision of data a service inthe themobile synchronous BDMO. once Susie had as downloaded application and acceptedthey the must geolocation, ansenior alert could be created.

This alert Second, convince management that investtriggers on Facebook to have coffeeThey at themust nearment in an theinvitation new architecture will be profitable. est bookstorehow withmarketing other readers share her interests and demonstrate andwho customer service operawho are in the area thenew same time. Students act by tions, which aresame driven byatthe variables, will increase writing the variables into the OMDB customer data entity.

Susie’s level of digital engagement and commitment. Only They adopt a syntax close to JSON (JavaScript Object then can they secure their careers by being promoted to the Notation), which is used for NoSQL databases, including position of chief officer.

MongoDB. Theydata specify the variables in such a way that a Susie’s interactions with the channels arethem. captured by data scientist or an IT colleague can encode Students the various digital marketing and customer service applications. Platforms such as the campaign management system, mobile application platform, or call center system generate data in silos. Data from digital and Customer relationship management (CRM) sources are merged and integrated via

32 • Mensa Research Journal

maximum forand inventing cross-channel indicatheobtain unique customerpoints record the DMP to the OMDB tors that require integrating various data systems that usually entities.

Unstructured data, such as the review Susie left on remain in silos. the customer forum, are integrated into the data lake along studentsdata, must such justify investment in the with Finally, semistructured as the webfirm’s browsing logs, and new database architecture. They demonstrate the value of the mirror copies of structured data, such as interaction events enhanced data through which marketing operations can be (clicks, openings, etc.). The way data are collected, merged launched to generate new revenue. Students describe what and integrated into not thebe model.

Thewithout data appear marketing canisdowritten that would possible this new in data the various entities of the BDMO. Color coding allows architecture. Students draw Susie’s commitment graph students to see howwhich the processes interact with Susiespecifiand again, explaining of the calculated variables with each other.

Facebook is presented as an external plat- If cally helped them improve her commitment to the brand. the case is well defended, Susie’s commitment graduform.

Figure 5 shows how students click on the should interactive ally increase. space the data graphs at the customer journeyThe model to between visualize the anddrawn processes beginning and end of the case could be articulated with resulting from the personas’ interactions with the direct, an empirical modelmarketing to simulatechannels. financial gain. digital, and social As Susie progresses along her journey, data from the difStudents must examine the data to determine when ferent touch points can be combined to obtain a behavioral personal information is other collected and consider personal commitment score and composite indicators.

With the data andspecialist explicit consent.

Formarketing example, students Susie helpprotection of their data colleagues, cannot geolocated until the she shape has given her permission, shouldbestrive to identify of Susie’s relationship that is, the when she downloads the mobilealternative application.

Susie’s with brand.

Similar to Fournier’s brand relationship trajectories (Fournier,page 1998), the system could recinteractions with the Facebook are recorded only once ognize Susie’s engagement a typology Susie accepts Facebook login curve access as to one the of “Harry Potter of relational They would beshe able game.”

Susie forms. calls customer servicethen to say didtonotpredict receivethe of theThe relationship act to shift Susie’s thelikely bookoutcome she ordered. call centerand agent then searchrelationship toward a more positive trajectory. By using es the catalogue for the book and sends another one. In composite indicators to determine the timing and content of this way, students understand that data-driven marketing marketing and service initiatives, marketers can increase relcannot function incustomer isolation experience, from other and internal processes. evance, improve reduce perceived The ODB involves the entire company, just as all departpressure (Micheaux, 2011). ments contribute to the perceived quality of Susie’s journey.

Students are assigned tasks through which they develop and then defend their business case for the investment in the new database architecture. The learning path in case two begins with Susie’s journey experience. Students simulate a

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

customer survey by imagining Susie’s perceptions at each point of contact if only silo data can be used to customize Susie’s experience. The perceptions are reported by adding an emotional journey to the existing journey map. Students spend time reflecting on how data are generated from Susie’s interactions and analyzing how they flow through the system. For example, they can see how, at Contact Point 1 (Figure 5), the campaign management platform interacts with the digital asset management platform to show the images in the newsletter. At Contact Point 2 (Figure 6), students can learn how the DMP integrates the click event of the CRM campaign into the CRM history database entity, while Susie’s visit to the online store is recorded in a different format in the e-store visits entity.

As they think about the data, students gain additional insights into Susie, who now clearly appears to be a working “digital mom.” Although she is an enthusiastic reader, Susie does not seem to be committed to her relationship with the bookstore. She is more involved with the authors of the books she reads. Students use this knowledge to decide which variables they can calculate from the contextualized data that could trigger marketing actions to improve Susie’s commitment level. For example, one group imagined that once Susie had downloaded the mobile application and accepted the geolocation, an alert could be created. This alert triggers an invitation on Facebook to have coffee at the nearest bookstore with other readers who share her interests and who are in the same area at the same time. Students act by writing the variables into the OMDB customer data entity. They adopt a syntax close to JSON (JavaScript Object Notation), which is used for NoSQL databases, including MongoDB. They specify the variables

in such a way that a data scientist or an IT colleague can encode them. Students obtain maximum points for inventing cross-channel indicators that require integrating various data systems that usually remain in silos.

Finally, students must justify the firm’s investment in the new database architecture. They demonstrate the value of the enhanced data through which marketing operations can be launched to generate new revenue. Students describe what marketing can do that would not be possible without this new data architecture. Students draw Susie’s commitment graph again, explaining which of the calculated variables specifically helped them improve her commitment to the brand. If the case is well defended, Susie’s commitment should gradually increase. The space between the graphs drawn at the beginning and end of the case could be articulated with an empirical model to simulate financial gain.

As Susie progresses along her journey, data from the different touch points can be combined to obtain a behavioral commitment score and other composite indicators.

With the help of their data specialist colleagues, marketing students should strive to identify the shape of Susie’s relationship with the brand. Similar to Fournier’s alternative brand relationship trajectories (Fournier, 1998), the system could recognize Susie’s engagement curve as one of a typology of relational forms. They would then be able to predict the likely outcome of the relationship and act to shift Susie’s relationship toward a more positive trajectory. By using composite indicators to determine the timing and content of marketing and service initiatives, marketers can increase relevance, improve customer experience, and reduce perceived pressure (Micheaux, 2011).

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Results and Limitations

The restructuring of the course has produced various results. Overall, the course successfully integrated students’ heterogeneous learning styles and skills into a collaborative approach to data-driven marketing. From 2016 to 2018, the new teaching method was implemented with 78 student groups and 344 students in eight separate courses at three institutions. The course was taught at the master’s degree level to students from different fields.

These were digital-native marketing students, students with professional experience and final-year business school students pursuing a specialization in digital marketing. A few had degrees in computer engineering, social sciences or mathematics.

Prior to the course redesign, some students had difficulty understanding the database and systems aspects of the datadriven marketing course, while those who were comfortable with this technology did not see how it supported digital marketing operations. These difficulties can be explained

by ELT theory. Student profiles cover Kolb’s basic learning styles: diverging, assimilating, converging and accommodating (D. A. Kolb et al., 2001; A. Y. Kolb & Kolb, 2017).

These styles correspond to the learning styles in each of the quadrants in Figure 2 in a clockwise direction.

According to this view, the dominant learning style of Marcom students is the divergent style. These students do well in “brainstorming” situations. Students in mathematics and social sciences tend to have assimilating learning abilities. They feel comfortable with data analysis and need time to reflect and appreciate concepts in a logical way (D.A. Kolb et al., 2001; A. Y. Kolb & Kolb, 2017).

Engineers and students from the IT world tend to have converging learning capabilities. They prefer technical tasks to social or interpersonal challenges and succeed in finding practical applications. Finally, the dominant learning style of business school students is the accommodating style, reflected in the “test and learn” paradigm of marketing practice. The new course format addresses all these basic learning styles. Students also benefit from each other’s learning styles when they collaborate on the case studies (Figure 2). Students with the diverging learning style generate ideas to engage Susie and increase her commitment. Students with assimilating learning abilities reflect well on data sources, and students with converging learning skills are in the best position to specify the variables to be implemented. Students with the accommodating learning style can see the value of these new indicators for marketing operations. Thus, the redesigned course allowed these heterogeneous students to combine and balance their skills to succeed in the digitally disruptive business world.

Because in the new course format, continuous monitoring has replaced some exams, it has not been possible to attribute the improvement in student grades to this method. In addition, too few students completed the feed-

34 • Mensa Research Journal

back questionnaire to formally measure their satisfaction, which is a limitation of this work. However, two doctoral students and three conversions to data-driven careers emerged from the courses, which were unprecedented among these predominantly Marcom student populations.

The course was well received by the education managers due to the positive feedback from students at the pedagogical meetings. Students liked the course and indicated that it allowed them to improve their perceived skills in datadriven marketing. In July 2018, two associate professors from Lille University were trained in teaching the method; one of them gave the course in the first 2018 semester, and the other is scheduled for the second semester.

Added Value for Students By using journey mapping tools in the classroom, the teacher was able to increase students’ enthusiasm for the database topic. The creation of a persona, enriched by the data collected on the touch points, allowed students to better understand the customer’s needs. By defining backstage Martech processes and the OMDB as stakeholders, it became clear that they also contribute to the value chain and influence the customer experience. The creation of stakeholder maps helped students understand how different data systems and colleagues who manage them interact to meet customer needs.

The use of classroom service design methods has brought together data, systems, theory, and practice in digital marketing. Students were able to observe how the various marketing channels and DMPs ingest, integrate, and add intelligence to the captured data. Students could discover how theoretical marketing concepts help justify investment in database architecture. They also learned how applied marketing theory can improve the customer experience and increase the revenue of marketers. The theoretical content was taught through presentations. Marketing theory and database concepts were introduced as students needed this knowledge to progress in the case studies. Additional documentation and support (e.g., instructional videos, documentation, and help) were provided through the Moodle learning management platform. Due to space constraints, this content is not described here.

A Deeper Learning Experience Through the creative process, students focused on action and learning based on emotions rather than knowledge alone. Their apparent motivation increased. Students also learned to distinguish between various closely related concepts. For example, the analysis of the emotional journey helped students understand the difference between the concepts of digital engagement, involvement, and commitment, which, although related (Beatty, Homer, & Kahle, 1988; Oh, Bellur, & Sundar, 2015), are often confused. Through this approach, the professor helped students consider the data as a service. Data as a service means

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

making data available to internal processes and other services through the OMD, as well as serving the customer through the data themselves.

Relevant direct and digital marketing benefits consumers and businesses. It reduces the commercial pressure perceived by consumers and increases corporate revenues (Micheaux, 2013). Each touch point in the customer’s journey determines the future development of the relationship. Relevant and timely messages can be perceived by the customer as a service and not as marketing. Finally, the students realized their own added value in relation to the data. They learned that databases are not the realm of technicians only. Marketers add value to the database through the variables they create, and they are in the best position to do so because they know how best to use these indicators to optimize their marketing programs and improve customer service (Moe & Ratchford, 2018).

Adaptable and Shared Teaching Model Any experiential learning method is time-consuming, and the development of the models took several weeks. However, through sharing, other marketing educators can benefit from this effort. One of the problems was that there were not enough classroom sessions to take full advantage of the teaching opportunities. Other academics could provide additional elements and links between theory and practice. For example, human resources educators could adapt the content to optimize the employee’s experience by using the data captured at the points of contact throughout the employee’s journey. Finance professors could calculate the financial return on investment in the new ODB architecture from the incremental commitment of the persona, extrapolated to the total client population. Legal professors could further develop aspects related to compliance with the General Data Protection Regulation (European Commission, 2016).

It is difficult for technology-based educators to survive in such a rapidly changing environment (Moe & Ratchford, 2018). However, it is simple to keep customer journey maps in step with technological change, as only backstage processes need to be updated. Each contact point can be upgraded, deleted or replaced, and new contact points can be added. This flexible system meets the requirements of Martech’s disruptive technology because the latest developments can be easily integrated into the course.

Conclusion

In conclusion, we propose the contribution of this work in response to ELT and the literature on marketing education and in terms of managerial implications. ELT has proven to be effective in the field of information technology. By 2000, computer science was the third most frequent source of ELT publications, after education and management, with 228 studies (D. A. Kolb et al., 2001). When applied to this course, the ELT interpretation framework

supports the perceived success of the teaching experience (Akella, 2010) and the learning experience and indicates additional improvements. The KLSI 4.0, summarized in A. Y. Kolb and Kolb (2017), provides a close match between the nine-style inventory and the students’ learning steps as the case studies are carried out. By mapping each of Susie’s journeys, students successively move through the eight learning styles shown in the outer circle in Figure 2. Balanced skills are required to identify stakeholders, set priorities and integrate database architecture, the business case and colleagues’ opinions. Thus, the stakeholder map is centered on Figure 2 in relation to the ninth style, which is the balancing style.

Although the expanded KLSI 4.0 accommodates the borderline cases of the basic typology (A. Y. Kolb & Kolb, 2017) because students find that four members represent the optimal size of a group, a mixture of four dialectically polarized learning styles should produce the most effective groups. Finally, it is useful to link the course steps to the educator’s role in supporting students throughout the learning cycle (A.Y. Kolb & Kolb, 2017, of which Figure 2 is adapted). For example, educators, at the appropriate stage of the learning spiral, provide students with subject matter expertise in the form of theoretical knowledge and provide feedback to help them meet the evaluator’s expectations.

Regarding the marketing education literature, this study follows previous studies on student engagement in social media in the classroom (Mostafa, 2015; West, Moore, & Barry, 2015). In the present case, the students were engaged in the use of technology, a customer journey mapping tool. The strategic use of technology to solve a problem had a positive impact on the teacher’s and students’ experience (Bitner, Ostrom, & Burkhard, 2012; Dowell & Small, 2011) and helped foster deeper learning (Canhoto & Murphy, 2016). As called for by these last authors, the class includes feedback mechanisms for students, invites them to discuss their decisions and reflects on the meaning of the data results.

In addition, future students could develop their own learning journeys. They could use the software to document and reflect on their personal learning experience, which would provide qualitative feedback from students.

Such feedback, often absent from traditional course evaluations, could help teachers redesign and adapt the course to meet students’ needs. Because digital disruption changes not only marketing but also the way marketing is taught, educators must develop innovative teaching methods, based on personal experiences, to change thinking patterns (Prensky, 2001). Existing educational models must be replaced by active learning (McLaughlin, 2014). This case shows that although transforming a data-driven marketing course requires significant investment, it is achievable.

From a management perspective, as future marketing professionals, students do not have to become data scien-

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Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

tists. However, they must learn to think like data scientists in order to work successfully with them and to ultimately manage them. They must master the fundamentals of data management systems to make the right decisions in their future marketing functions. To become effective chief data officers, students must have the ability to interact with the right people in their organization and bring these people together. The course develops interdisciplinary skills, as students experience a realistic business use case with financial, ethical, and managerial implications of datadriven marketing. The software used helped students realize the importance of collaboration between departments to break down functional silos within their organizations and improve the customer experience (Grewal, Roggeveen, & Shankaranarayanan, 2015).

In addition, the course is flexible enough to adapt to new Martech platforms and advances in database architecture, such as NoSql and operationalized data lakes. “Data as a service” is a technical term used in the context of modern database architecture (Gruhn, 2016), which is taught in the cases presented in this article. However, the vision of data as a service conveyed in this course transcends database technology to include service design methods applied to customer journey mapping, supported by service ethics.

From a technical point of view, data as a service provides valuable real-time data to employees who collaborate to provide products and services to customers. The broader vision of the concept puts data at the service of society through economic growth driven by their ethical and relevant use in the best interest of the customer.

Authors’ Note

The authors contributed equally to the publication of this article. The lead author of this article is the creator of the course. The course was taught at IAE–University of Lille, University Paris II Panthéon-Assas, IPAG Business School, France.

Acknowledgments

We would like to thank Mathilde Gollety, Teodorina Tibar, and the organizers of the IAE France–AUNEGE 2017 conference on digital innovation for reviewing early versions.

Declaration of Conflicting Interests

The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/ or publication of this article: The Smaply software used in this case is a product of More than Metrics. One of the authors works for More than Metrics.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

36 • Mensa Research Journal

ORCID iD

Andrea Micheaux https://orcid.rg/0000-0003-4845-3618

References

Akella, D. (2010). Learning together: Kolb’s experiential theory and its application. Journal of Management & Organization, 16, 100-112.

Aoga, J., Guns, T., & Schaus, P. (2017). Mining timeconstrained sequential patterns with constraint programming. Constraints, 22, 1-23.

Asbjørn, F., & Knut, K. (2018). Customer journeys: A systematic literature review. Journal of Service Theory and Practice, 8, 196-227.

Beatty, S. E., Homer, P., & Kahle, L. R. (1988). The involvement–commitment model: Theory and implications.

Journal of Business Research, 16, 149-167.

Berry, L. L., Carbone, L. P., & Haeckel, S. H. (2002).

Managing the total customer experience. MIT Sloan Management Review, 43, 85-89.

Bitner, M., Ostrom, A., & Burkhard, K. (2012). Service blueprinting: Transforming the student experience.

EDUCAUSE Review, 47, 38-50.

Bosio, B., Rainer, K., & Stickdorn, M. (2017). Customer experience research with mobile ethnography: A case study of the Alpine destination Serfaus-Fiss-Ladis. In R. W. Belk (Ed.), Qualitative consumer research (Vol. 14, pp.

111-137). Bingley, England: Emerald.

Canhoto, A. I., & Murphy, J. (2016). Learning from simulation design to develop better experiential learning initiatives: An integrative approach. Journal of Marketing Education, 38, 98-106.

Carlzon, J. (1987). Putting the customer first: The key to service strategy. McKinsey Quarterly, 3, 38-51.

Cooper, A. (1999). The inmates are running the asylum.

Indianapolis, IN: Macmillan.

Crié, D., & Micheaux, A. L. (2006). From customer data to value: What is lacking in the information chain? Journal of Database Marketing & Customer Strategy Management, 13, 282-299.

Crittenden, V., & Crittenden, W. (2015). Digital and social media marketing in business education: Implications for the marketing curriculum. Journal of Marketing Education, 37, 71-75.

Dowell, D. J., & Small, F. A. (2011). What is the impact of online resource materials on student self-learning strategies? Journal of Marketing Education, 33, 140-148.

Dupree, J.-L., Lank, E., & Berry, D. M. (2018). A case study of using grounded analysis as a requirement engineering method: Identifying personas that specify privacy and security tool users. Science of Computer Programming, 152, 1-37.

European Commission. (2016). Data protection in the EU. Retrieved from https://ec.europa.eu/info/law/law-topic/ data-protection/data-protection-eu_en

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

Fink, E. (2017). Pourquoi les responsables marketing doivent adopter une vision globale des données [Why marketers need to take a holistic view of data]. Retrieved from https://www.decideo.fr/Pourquoi-les-responsablesmarketing-doivent-adopter-une-vision-globale-desdonnees_a9526.html Fournier, S. (1998). Consumers and their brands: Developing relationship theory in consumer research. Journal of Consumer Research, 24, 343-373.

Gartner. (n.d.). Gartner Data and Analytics Summit 2019. Retrieved from https://www.gartner.com/en/ conferences/na/data-analytics-us Goodwin, K. (2008). Getting from research to personas: Harnessing the power of data.

Grewal, D., Roggeveen, A. L., & Shankaranarayanan, G. (2015). Marketing-ITS integration: Developing nextgeneration managers. In V. L. Crittenden, K. Esper, N. Karst, & R. Slegers (Eds.), Evolving entrepreneurial education: Innovation in the Babson classroom (pp. 139157). Bingley, England: Emerald.

Gruhn, R. (2016). Matinée Big Data. A modern enterprise architecture. Retrieved from https://www.mongodb. com/presentations-big-data-paris-a-modern-enterprisearchitecture Kolb, A. Y., & Kolb, D. A. (2017). The experiential educator: Principles and practices of experential learning. Kaunakakai, HI: EBLS Press.

Kolb, D. A. (1971). Individual learning styles and the learning process (Working Paper No. 535-71). Cambridge: Sloan School of Management, Massachusetts Institute of Technology.

Kolb, D. A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, NJ: Prentice Hall.

Kolb, D. A., Boyatzis, R., & Mainemelis, C. (2001). Experiential learning theory: Previous research and new directions. In R.J. Sternberg & L. F. Zhang (Eds.), Perspectives on thinking, learning, and cognitive styles (pp. 227-247).

Mahwah, NJ: Lawrence Erlbaum.

Lafley, A. G. (2005). Foreward. In K. Roberts (Ed.), Lovemarks: The future beyond brands (p. 9). New York, NY: PowerHouse Books.

Lecinski, J. (2011). Winning the zero moment of truth. Retrieved from https://www.thinkwithgoogle.com/marketingresources/ micro-moments/2011-winning-zmot-ebook/ Lemon, K. N., & Verhoef, P. C. (2016). Understanding customer experience throughout the customer journey.

Journal of Marketing, 80, 69-96.

McGinn, J., & Kotamraju, N. (2008, April). Data-driven persona development. In CHI 2008 Proceedings, ACM Conference on Human Factors in Computing Systems (pp.

1521-1524). New York, NY: ACM.

McLaughlin, L. (2014). Active learning challenges old education models. Retrieved from https:// www.extension.har vard.edu/inside-extension/ active-learning-challenges-old-education-models McLeod, S. (2017). Kolb’s learning styles and experiential learning cycle. Retrieved from https://www.simplypsychology.org/simplypsychology.org-Kolb-LearningStyles.pdf Meyer, C., & Schwager, A. (2007). Understanding customer experience. Harvard Business Review, 85(2), 116-126.

Miaskiewicz, T., & Kozar, K. A. (2011). Personas and usercentered design: How can personas benefit product design process? Design Studies, 32, 417-430.

Micheaux, A. L. (2011). Managing e-mail advertising frequency from the consumer perspective. Journal of Advertising, 40, 45-66.

Micheaux, A. L. (2013). Getting to the bottom of Pandora’s box. Journal of Direct, Data and Digital Marketing Practice, 14, 187-200.

Moe, W. W., & Ratchford, B. T. (2018). How the explosion of customer data has redefined interactive marketing.

Journal of Interactive Marketing, 42, A1-A2.

Mostafa, R. B. (2015). Engaging students via social media: Is it worth the effort? Journal of Marketing Education, 37, 144-159.

Oh, J., Bellur, S., & Sundar, S. S. (2015). Clicking, assessing, immersing, and sharing: An empirical model of user engagement with interactive media. Communication Research, 45, 737-763.

Palmatier, R. W., Dant, R. P., Grewal, D., & Evans, K. R. (2006). Factors influencing the effectiveness of relationship marketing: A meta-analysis. Journal of Marketing, 70, 136-153.

Prensky, M. (2001). Do they really think differently? On the Horizon, 9(6), 1-6.

Pruitt, J., & Grudin, J. (2003). Personas: Practice and theory. In Proceedings of the 2003 Conference on Designing for User Experiences (DUX’03). Retrieved from https://www.microsoft.com/en-us/research/wp-content/ uploads/2017/03/pruitt-grudinold.pdf Qaqish, D. (2018, September). Customer journey mapping in 3 steps. Marketing News. Retrieved from https://medium.com/ama-marketing-news/ customer-journey-mapping-in-3-steps-47f3aa4dc60b Ramshaw, A. (2016). Customer journey mapping software review. Retrieved from https://www.genroe.com/blog/ journey-mapping-software Rawson, A., Duncan, E., & Jones, C. (2013). The truth about customer experience. Harvard Business Review, 91(9), 90-98.

Schäfer, C., Zinke, R., Künzer, L., Hofinger, G., & Koch, R. (2014). Applying Persona method for describing users of escape routes. Transportation Research Procedia, 2, 636-641.

Volume 52, Issue 3 • 37

Customer Journey Mapping as a New Way to Teach Data-Driven Marketing as a Service

Schlee, R. P., & Karns, G. L. (2017). Job requirements for marketing graduates: Are there differences in the knowledge, skills, and personal attributes needed for different salary levels? Journal of Marketing Education, 39, 69-81.

Stephenson, B. Y. (1989). Critical marketing strategies for the 1990s: Databased marketing and multichannel marketing. Journal of Direct Marketing, 3(3), 34-41.

Stickdorn, M., Lawrence, A., Hormess, M., & Schneider, J. (2018). This is service design doing. Sebastopol, CA: O’Reilly.

Stickdorn, M., & Schneider, J. (2011). This is service design thinking. Amsterdam, Netherlands: BIS. Teixeira, J., Patrício, L., Nunes, N. J., Nóbrega, L., Fisk, R. P., & Constantine, L. (2012). Customer experience modeling: From customer experience to service design.

Journal of Service Management, 23, 362-376.

Tong, Y., She, J., Ding, B., Wang, L., & Chen, L. (2016, May). Online mobile micro-task allocation in spatial crowdsourcing. In 2016 IEEE 32nd International Conference on Data Engineering (ICDE) (pp. 49-60).

Piscataway, NJ: IEEE.

Turner, P., & Turner, S. (2011). Is stereotyping inevitable when designing with personas? Design Studies, 32, 34-44. van Oosterom, A. (2011). Design thinkers’ process. In M. Stickdorn & J. Schneider (Eds), This is service design thinking (pp. 224233). Amsterdam, Netherlands: BIS. Vargo, S. L., & Lusch, R. F. (2004). Evolving to a new dominant logic for marketing. Journal of Marketing, 68(1), 1-17.

Vergne, P., & Blanc, C. (2016). Matinée Big Data: Air France: Stratégie Big Data et use cases [Big data morning: Air France: Big Data strategy and use cases]. Retrieved from https://www.mongodb.com/presentations/ big-data-paris-air-france-strategie-bigdata-et-use-cases West, B., Moore, H., & Barry, B. (2015). Beyond the Tweet. Using Twitter to enhance engagement, learning, and success among first-year students. Journal of Marketing Education, 37, 160-170.

Zomerdijk, L. G., & Voss, C. A. (2011). NSD processes and practices in experiential services. Journal of Product Innovation Management, 28, 63-80.

Unleashing Intelligence for the Benefit of Humanity

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38 • Mensa Research Journal

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The Use of Kolb’s Model in Science Teaching Methodology Snježana Močinić, Nevenka Tatković, and Sanja Tatković

Abstract The relevance of this paper refers to the importance of Kolb’s model in developing future teachers’ professional competences and ability to integrate the theoretical and practical segment of their education. The aim of this paper is to examine what theoretical knowledge and practical experience is present in the Science Teaching Methodology regarding the initial teacher training in Croatia, in accordance with the Kolb’s model.

The research was based on quantitative (descriptive analysis and factor analysis) and qualitative research methodology, which included the analysis of relevant literature and a survey conducted among the students of teacher education studies at the universities of Pula, Rijeka, Zadar and Split (Croatia). The results have shown that, in the given context, the Science Teaching Methodology is dominated by the acquisition of theoretical knowledge, lacking concrete experience activities and reflections on the real-life experience. Furthermore, innovations are only rarely introduced into teaching, which means that Kolb’s experiential learning model is not implemented in practice. The paper materials may be useful in the initial teacher training for acquiring the theoretical and practical knowledge about the use of Kolb’s model in the Science Teaching Methodology, and for integrating this model into the initial teacher training curriculum.

Introduction

On a daily basis we are facing rather significant and quick changes in all segments of life, from social and cultural to socio-economic and political. One of the segments which has undergone significant changes is the education area, i.e. higher education, and those changes are reflected in the demand for high-quality, competitive study programs for younger generations and a high level of professional competences for their future employment. One of the key issues of education policy of any country which strives to improve the quality of its education system is teacher education and professional development, because the level of students’ learning outcomes largely depends on the quality of the teaching staff. Therefore, the importance of teacher competences, especially those acquired during their initial training, has become the topic of study at all levels of formal education, both in Croatia and worldwide. According to the recommended literature, it is advisable for initial teacher training to be based on a successful combination of theoretical and practical teaching with an appropriate amount of academic and pedagogical/psychological content knowledge, methodology exercises and student practice. To ensure high-quality professional work of prospective teachers it is important to raise awareness among students that theoretical knowledge does not offer prescriptions for dealing with different individual cases they might encounter in their practice.

However, theoretical knowledge is necessary for reflection on experience, and the results of the reflection should be systematized and generalized, allowing the gained knowledge to be applied in different situations. This opens a new perspective in which theory accompanies practice,

describing its processes and results and justifying its existence through concrete actions. It is our belief that the use of Kolb’s experiential learning model (Kolb, 1984; Kolb, 2015) during initial teacher training can prepare future teachers for the analysis of their practical work by means of theoretical knowledge and reflection.

The main objective of this research was to examine the extent to which theoretical knowledge and practical experience are present and integrated into the Science Teaching Methodology classes during teachers’ initial training, and hence also into the process of development of teachers’ competences according to Kolb’s (1984) experiential learning model. The following research tasks were derived from the general research objective: • to determine whether theoretical and practical components of Kolb’s experiential learning model can be found in the Science Teaching Methodology classes at teacher education studies in Croatia; • to determine whether theoretical and practical components of Kolb’s experiential learning model are integrated into the Science Teaching Methodology classes at teacher education studies in Croatia.

Propósitos y Representaciones, Aug. 2020, Vol. 8, SPE(2), e685 http://dx.doi.org/10.20511/pyr2020.v8nSPE2.685, ISSN 23077999, Special number: Educational Psychology Practices in Europe and the Middle East Močinić, S., Tatković, N., & Tatković, S. (2020). The Use of Kolb’s Model in Science Teaching Methodology. Propósitos y Representaciones, 8 (SPE2), e684. Doi: http://dx.doi.org/10.20511/pyr2020. v8nSPE2.685

Volume 52, Issue 3 • 39

The Use of Kolb’s Model in Science Teaching Methodology

Based on the defined research objective and research tasks, the following hypotheses have been formulated: (H1) Theoretical (reflective observation and abstract conceptualization) and practical (concrete experience and active experimentation) components of Kolb’s experiential learning model are not equally present in Science Teaching Methodology classes at teacher education studies in Croatia.

(H2) Theoretical (reflective observation and abstract conceptualization) and practical (concrete experience and active experimentation) components of Kolb’s experiential learning model are not integrated into the Science Teaching Methodology classes at teacher education studies in Croatia.

Theoretical overview

Characteristics of the course on Science Teaching Methodology and Science and Social Studies as a subject Science Teaching Methodology is an interdisciplinary scientific discipline which studies principles of education from the perspective of Science and Social Studies as a subject taught during primary education (De Zan, 2005).

The subject itself is interdisciplinary, integrating “scientific knowledge from the area of natural sciences, social sciences and humanities with technical and computer sciences” (MoSES, 2016). Science and Social Studies are an artificially created subject which is taught from the first to the fourth grade of primary school and which is closely connected with other subjects, cross-curricular topics and curriculum areas by means of the basic concepts it studies. In the delivery of the said subject, “experiential, research-oriented and problem-solving teaching” is recommended, “in which the student is at the center of the learning process, as it ensures his or her active role in learning and teaching” (MoSES, 2016).

Numerous authors believe that extra-classroom, i.e. outdoor teaching (school yard, playground, green areas, various places in which human activities are performed) is also useful, where research-based teaching techniques can be implemented (Szczepanski, 2001; Anđić, 2007; Borić, 2009; Borić et al., 2010; Letina, 2016). This type of teaching is based on observation and perception of various natural and social phenomena, hypothesizing, experimentation, autonomous data collection, analysis and interpretation of results, which help develop critical thinking skills and observe patterns and consequences, as well as other relationships between phenomena. In order to ensure that a future teacher is able to apply the research-based approach to learning and teaching in his/her professional work, it is advisable to practice the said approach during one’s own education and training. Seeing that Kolb’s (Kolb, 1984; Kolb, 2015) experiential learning model has numerous characteristics of research-based teaching, we believe that its use within Science Teaching Methodology might contrib-

40 • Mensa Research Journal

ute to teachers’ training for the implementation of researchbased approach in Science and social studies classes.

Kolb’s interpretation of the experiential learning model Kolb (1984) claims that experiential learning theory would be incomplete without an overview of theories of cognition, nature and organization of knowledge and processes by means of which individuals contribute to and participate in knowledge creation. In his overview of the history of epistemology Kolb draws on empirical, rationalist and interactionist perspectives of knowledge acquisition, believing that they are fundamental for epistemological debate in the western philosophy from the period of classical Greek philosophers up to the 20th century. Apart from the world-view characteristic for medieval scholasticism, the 17th century saw the emergence of the rational, and later empirical theory of cognition. Rationalists such as Descartes, Spinoza and Leibniz (Kolb, 1984) believed that the truth is discovered through logical thinking and reason, in which ideas exist a priori, and that the only thing that stems from senses is the reflection of ideal forms which make sense of the real world.

The 18th century gave rise to the antithesis to rationalism – empiricism. According to empirical philosophers, Locke, Hobbes and others, knowledge derives from sensory experience of the world around us. The mind is a tabula rasa; it receives and records a multitude of sensory experiences, but does not contribute to identifying the essence of things. The conception that truth can be gained through a careful observation of the world has inspired numerous scientific research studies in the 18th century. In the 19th century, rational and empirical views were synthesized in Kant’s critical idealism. According to Kant, the mind possesses a priori concepts which allow it to interpret experience, especially those which allow the understanding of time, space and order. The laws of geometry and logic were considered to be extra-experiential, but necessary for the interpretation of experience. In critical idealism, the truth is the product of interaction of the mind and material facts of sensory experience.

Kolb’s (1984) theory of experiential learning conquered the limitations of both rationalism and empiricism.

Namely, epistemology of experiential learning is based on the dual-knowledge theory: concrete empirical experience, which grasps reality through the process of direct cognition, and rationalist abstract conceptualization, which perceives reality through the abstract thinking mediation process.

Unlike Kant, Kolb (1984) argues that ideas are not fixed and unchangeable, but rather shaped and re-shaped on the basis of new experience. Furthermore, knowledge is created through a revised interpretation of the meaning of an experience, which guides subsequent action. Hence, the experiential learning theory defines learning as a “process in which knowledge is created through transformation

apprehension and comprehension. The former is based on concrete sensory experience, while the latter is based on mental concepts and theoretical interpretation of experience. Within the experience transformation process he distinguishes other twoThe forms – the act of extension (active Use of Kolb’s Model in Science Teaching Methodology manipulation of the outside world) and the act of intention (reflective thinking) (Figure 1).

Figure 1. Kolb’s cyclic model of experiential learning (Kolb, 1984) To Knowledge simplify, inresults the development of his model, Kolb Kolbsees (Kolb, 1984; Kolb, 2015) begins byin which of experience. from the combination the learning process as the context defining two crucial dimensions that the learning process depends on, which are: access to (CE), of grasping and transforming experience” (Kolb, 1984). individuals move between concrete experience information and transformation of information.

Access to information can occur through concrete Aware of the complexity of the process, Kolb (1984) tried abstract conceptualization (AC), reflective observation (RO) abstract while transformation of experience requires and active experimentation (AE). Hence, thetwo effectiveness to experience illustrate it byorusing specificconceptualization, descriptive and interpretamanners of processing information: reflective observation and active experimentation (Vizek tive categories. For this purpose he used two complemen- of learning depends on the ability to balance between these & Vlahović-Štetić, 2007).

These four represent Kolb’s (1984) stages of learning, which Kolbexperiential views as dialectically taryVidović dimensions: the act of grasping experience and theelements act fouralso learning model which consists of four stages: concrete experience, reflective observation, abstract linked activities, effective in promoting learning. In the of transforming experience. The act of grasping has two conceptualization and active experimentation. If none of thelearning stagesprocess, is omitted, an in-depth experiential two aspects can be regarded aspects: apprehension and comprehension. The former is approach to learning and understanding of the linkasbetween theoretical concepts and specific especially noteworthy: the use of the concrete, “here and based on concrete sensory experience, while the latter is practical issues can be achieved. now” experience to test ideas and the use of feedback to based on mental concepts and theoretical interpretation of change practices and theories (Kolb, 1984) (Table 1). experience. Within the experience transformation process Kolb sees the learning process as the context in D.A. which individuals concrete Kolb and R. Frymove (Kolbbetween & Fry, 1975) argue that the he distinguishes other two forms – the act of extension experience (CE), abstract conceptualization (AC),learning reflective observation (RO) and active cycle can begin at any of the four stages, and that (active manipulation of the outside world) and the act of experimentation (AE). Hence, the effectiveness of the learning depends the be ability to balance learning process on should approached as a continuintention (reflective thinking) 1). which Kolb views as dialectically between these four stages(Figure of learning, linked activities, effective ous spiral development. Also, all four stages of the process To promoting simplify, in learning. the development his model, learning Kolb in In the of experiential process, aspectstocan be regardedArising as from need to occurtwo for learning be accomplished.

(Kolb, 1984; Kolb, 2015) begins by defining two crucial especially noteworthy: the use of the concrete, “heretheand now” experience to test ideas and the belief that learning is a social process based on cumudimensions that the to learning depends on, which(Kolb, 1984) (Table 1). use of feedback changeprocess practices and theories lative experience and reflection on that experience, Kolb are: access to information and transformation of informa(Passarelli & Kolb, 2011; Kolb, 2015) has a rather broad tion. Access to information can occur through concrete understanding of the theory of experiential learning, i.e. experience or abstract conceptualization, while transforhe believes that it is applicable not only in formal educamation of experience requires two manners of processing tion, but in all life situations and all human activities. The information: reflective observation and active experimenta- holistic and dynamic nature of the learning process means tion (Vizek Vidović & Vlahović-Štetić, 2007). These four that it occurs at all levels of human society, from individuPropósitos y Representaciones Aug. 2020, Vol.represent 8, SPE(2), e685 elements also Kolb’s (1984) experiential learn- als to groups, from education institutions to the society as inghttp://dx.doi.org/10.20511/pyr2020.v8nSPE2.685 model which consists of four stages: concrete experi- a whole. ence, reflective observation, abstract conceptualization and active experimentation. If none of the stages is omitted, Materials and methods an in-depth approach to learning and understanding of This research was based on quantitative and qualitative of Kolb’s Model in Science Teaching Methodology theThe linkUse between theoretical concepts and specific practical research methodology which included a survey conducted among students of Teacher Education Studies at the issues can be achieved.

Table 1.

Stages and forms of experiential learning (Kolb & Kolb, 2005) Grasping reality Transforming reality

Abstract conceptualization Concrete experience Active experimentation Reflective observation

Thinking, formulating ideas Experience through the senses Acting, testing ideas in practice Reflecting on the experience and activity

D.A. Kolb and R. Fry (Kolb & Fry, 1975) argue that the learning cycle can begin at any 52, Issue 3 • 41 of the four stages, and that the learning process should be approached as aVolume continuous spiral development. Also, all four stages of the process need to occur for learning to be accomplished.

from 0.863 to 0.932. Data obtained by means of the survey has been processed by means of descriptive statistics and factor analysis. This research encompassed a total of 109 4th- and 5thyear students of Teacher Education Studies of the Universities of Pula, Rijeka, Zadar and Split The Use of Kolb’s Model in Science Teaching Methodology (Table 2).

Table 2.

Number of students who completed the Science Teaching Methodology questionnaire with regard to the university and the year of study Measuring instrument Science Teaching Methodology questionnaire

Place of study (University) Pula Rijeka 20 25 Year of study 2nd year 3rd year -

Zadar 30

Split 36

Total 109

4th year 35

5th year 76

Total 109

Universities In of Pula, Rijeka, on Zadar and Split.

Kolb’s (Kolb, tial learning. scalesnumber containedofin students this questionnaire the survey Science Teaching Methodology, the The largest who are the 1984; Kolb, 2015) experiential learning model was chosen as following: completed the questionnaire were 5th-year students because the said course in teaching themethodology relevant theoretical framework, it is 5th not year easilyof teacher • the knowledgestudies acquisition which refers to the is taught at the although 4th and the education at thescale, Universities applicable to educational conditions and traditions in Croaacquisitionof of the theoretical knowledge as the of Pula, Rijeka and Split, while at the Faculty of Teacher Education University of Zadar it basis for tia, and there is no adequate operationalization or measures further learning and which is not a part of Kolb’s is taught at the 3rd and 4th year; however, 3rd-year students were not encompassed by the survey. expeappropriate to our socio-cultural context for the constructs riential learning For the purpose of surveying the students, the questionnaires werecycle; sent via mail to the that we wanted to explore and correlate with a desirable edu• the concrete experience scale, which examines the aforementioned Faculties of Teacher Education. cation practice. Hence, before conducting a concrete empirirespondents’ personal experience with observation, cal research we developed a research measurement instrument planning and delivery of teaching; Results and discussion (questionnaire) which helped us to achieve the set objectives.

• the reflective observation scale, which refers to the The starting point for this research was the experiential learnreflection during and after one’s own class delivery or ing model (Kolb, 1984; Kolb, 2015) which consists of four after observing someone else’s class delivery, i.e. video stages: concrete experience, reflective observation, abstract recordings of good practice examples; Propósitos y Representaciones conceptualization and active experimentation and which, Aug. 2020, Vol. 8, SPE(2), e685 • the abstract conceptualization scale, which includes according to its author, provides an in-depth approach to http://dx.doi.org/10.20511/pyr2020.v8nSPE2.685 items used to evaluate the logical analysis and explanalearning and understanding of the connection between theotion of various pedagogical situations, establishment retical concepts and specific practical problems, and allows the of links with theoretical knowledge, and forecasting of development of competences such as the ability to integrate innovations on the basis of acquired knowledge; declarative, procedural and meta-cognitive knowledge. D.A. • the active experimentation scale, which consists of Kolb and R. Fry (Kolb & Fry, 1975) believe that the learnitems used to evaluate the application of acquired ing cycle can begin at any one of the four stages, and that the knowledge in a new pedagogical situation. learning process should be approached as a continuous spiral development.

Using a five-point Likert scale (where 1 stands for “not at Also, for learning to be accomplished, all four stages of all”, and 5 stands for “absolutely”), respondents were asked the process need to occur. In this research, Kolb’s psychologi- to evaluate the extent to which each of the stages of Kolb’s cal model was attributed the following pedagogical/didactic experiential learning model is present in the aforementioned scales. The developed instrument was checked for satisfactomeanings: • concrete experience refers to observation of teaching or ry metric characteristics. Sensitivity was tested by means of measures of dispersion, construct validity was tested by means one’s own delivery of a teaching unit; of factor analysis, while reliability was tested by means of • reflective observation includes the assessment of one’s Cronbach’s alpha internal consistency method. Internal consisown or somebody else’s practical activity by analysing tency coefficients (Cronbach’s alpha) obtained for all previthe pedagogical situation from various perspectives; ously mentioned scales were extremely high, ranging from • abstract conceptualization refers to the logical analy- 0.863 to 0.932. Data obtained by means of the survey has sis of experience, identification of behaviour patterns, been processed by means of descriptive statistics and factor the establishment of links with theoretical knowledge, analysis. This research encompassed a total of 109 4th- and planning and predicting on the basis of what has been 5th-year students of Teacher Education Studies of the Univerobserved; sities of Pula, Rijeka, Zadar and Split (Table 2).

• while active experimentation refers to the testing of In the survey on Science Teaching Methodology, the largthe drawn conclusions in a new pedagogical situation est number of students who completed the questionnaire were (Vizek Vidović, 2005).

5th-year students because the said course in teaching methodItems have been created and grouped into scales accord- ology is taught at the 4th and the 5th year of teacher educaing to the postulates of Kolb’s theoretical model of experien- tion studies at the Universities of Pula, Rijeka and Split, while

42 • Mensa Research Journal

was named Familiarity with the key features of the subject “Science and social studies” (items 12 to 16); while the third factor was named Familiarity with the essential curriculum contents of Science Teaching Methodology (items 17 to 23 and item 11). On the basis of the aforementioned The Use of Kolb’s Model in Science Teaching Methodology factor analysis, three eponymous sub-scales have been constructed.

Table 3.

Results of the factor analysis of the knowledge acquisition scale for the Science Teaching Methodology and the descriptive statistics of the items of the scale Acquisition of theoretical knowledge from the Science Teaching Methodology

Factor*

Arithmetic mean

Standard deviation

1 2 3 1. Define the sources of knowledge in the course on 0.830 3.990 0.893 Science and social studies 2. Describe the use of teaching instruments and teaching 0.827 4.000 0.957 aids, as well as of information and communication technology in the course on Science and social studies 3. Describe specific traits of social forms of teaching in 0.775 4.254 0.828 the course on Science and social studies 4. Define the process of lesson preparation 0.697 4.036 0.917 5. Identify possibilities of inter-subject and cross-subject 0.626 4.045 0.871 correlation of teaching contents 6. Define teaching strategies, methods and procedures 0.606 4.045 0.794 7. Describe personal and professional characteristics and 0.530 3.727 1.039 competences of a successful teacher 8. Describe locations in which Science and social studies 0.522 3.972 0.817 course is delivered and their advantages 9. Describe the procedures for planning and 0.507 4.036 0.866 programming of the teaching process 10. Define the process of concept formation in Science 0.462 3.736 0.895 and social studies class 0.397 11. Identify curriculum contents related to 0.438 3.819 0.833 environmental education and the importance of raising 0.318 environmental awareness 12. Define the theoretical postulates and structure of the 0.87 4.063 0.777 teaching methodology for science and social studies 6 13. Identify research methods used in the teaching 0.81 4.099 0.852 methodology for science and social studies 6 14. Describe how the idea to introduce the subject 0.70 3.891 0.897 “Science and social studies” in schools was developed 7 15. Define learning outcomes of the subject “Science 0.65 4.225 0.794 and social studies” 0 16. Identify principles of organization of the “Science 0.55 4.036 0.841 and social studies” subject content 3 17. Describe curriculum contents related to the economy 3.666 1.081 (agriculture, industry, trades and crafts, services) 0.915 18. Define curriculum contents related to history (time 3.612 1.063 orientation, historical images, history of objects and 0.853 Močinić, S., Tatković, N., & Tatković, S. phenomena, etc.)

19. Identify curriculum contents related to traffic 3.639 1.025 education 0.801 20. Define curriculum contents related to geography 3.855 0.998 (spatial orientation, cartographic literacy, relief, etc.)

0.793 Propósitos 21. Identify curriculum contents related to natural 3.964 y Representaciones 1.026 Aug. 2020, Vol. 8, SPE(2), e685 sciences (living beings and living communities; 0.560 http://dx.doi.org/10.20511/pyr2020.v8nSPE2.685 inanimate nature: water, air, soil, warmth, light) 22. Define health-related curriculum contents (health 0.391 3.765 1.044 and nutrition, childhood diseases, pathogens, etc.)

0.548 23. Name different approaches to assessment and 0.359 3.648 1.032 methods for evaluation and assessment of students’ 0.490 achievements in the Science and social studies class Factor 1: Familiarity with didactic and methodological contents of Science Teaching Methodology Factor 2: Familiarity with the key features of the subject “Science and social studies” Factor 3: Familiarity with the essential curriculum contents of Science Teaching Methodology *To facilitate interpretation, factor saturations whose absolute value exceeds 0.3 have been shown.

at the Faculty of Teacher thedata University of (Table Zadar 3) Results and discussion OnEducation the basis ofofthe obtained for the subscale Familiarity with didactic and it is taught at the 3rd and 4th year; however, 3rd-year students methodological contents of Science Teaching Methodology canfactor see that the respondents have Results ofwethe analysis in the scales attributedbythe to surveythe item named Describe specific traits of social forms were not encompassed thehighest survey. value For the(M=4.25) purpose of The conducted factor analysis has shown that the acquisiof teaching in the course on Science lowest value (M=3.72), well as the ing the students, the questionnaires were sent via and mailsocial to thestudies. tionThe of knowledge from ScienceasTeaching Methodology is a highest standard dispersion of results (SD=1.03), has been obtained for the item named Define aforementioned Faculties of Teacher Education. multi-dimensional construct. Three factors whose characterpersonal and professional characteristics and competences of a successful teacher. The lowest dispersion (SD=0.79) has been obtained for the item Define teaching strategies, methods and procedures. The analysis of results obtained for the subscale Familiarity with the keyVolume features52, of Issue 3 • 43 the subject “Science and social studies” shows that the highest mean value (M=4.22) was obtained for the item Define tasks of the subject “Science and social studies”, while the lowest mean value

The Use of Kolb’s Model in Science Teaching Methodology

istic root exceeds 1 (characteristic root of the selected three factors: 10.930, 1.718, and 1.578) have been singled out, accounting for 61.853% of the scale score variance. With regard to the size of the coefficient in the matrix shown in Table 3, the first factor was named Familiarity with didactic and methodological contents of Science Teaching Methodology (items 1 to 10); the second factor was named Familiarity with the key features of the subject “Science and social studies” (items 12 to 16); while the third factor was named Familiarity with the essential curriculum contents of Science Teaching Methodology (items 17 to 23 and item 11). On the basis of the aforementioned factor analysis, three eponymous sub-scales have been constructed.

On the basis of the data obtained (Table 3) for the subscale Familiarity with didactic and methodological contents of Science Teaching Methodology we can see that the respondents have attributed the highest value (M=4.25) to the item named Describe specific traits of social forms of teaching in the course on Science and social studies.

The lowest value (M=3.72), as well as the highest standard dispersion of results (SD=1.03), has been obtained for the item named Define personal and professional characteristics and competences of a successful teacher. The lowest dispersion (SD=0.79) has been obtained for the item Define teaching strategies, methods and procedures. The analysis of results obtained for the subscale Familiarity with the key features of the subject “Science and social studies” shows that the highest mean value (M=4.22) was obtained for the item Define tasks of the subject “Science and social studies”, while the lowest mean value (M=3.89) was obtained for the item Describe how the idea to introduce the subject “Science and social studies” in schools was developed. A possible explanation for such high mean values related to this scale is the fact that students of the said course are aware of interdisciplinarity and complexity of this school subject, whose purpose is to acquaint pupils with scientific and social aspects of knowledge about the environment in which they live. Items of the subscale Familiarity with the essential curriculum contents of Science Teaching Methodology were attributed generally lower average values and higher dispersions in comparison with the previous two subscales, which is probably the result of difficulties in processing such a complex and comprehensive course which incorporates curriculum contents from both natural and social sciences and humanities that are an integral part of the Science Teaching Methodology. Looking at the overall score (Table 3), we can conclude that the respondents attributed high levels of importance (from M=3.61 to M=4.25) to all three subscales which are related to the construct Acquisition of theoretical knowledge and which deal with the essential curriculum contents and methodological knowledge of science and social studies.

44 • Mensa Research Journal

The conducted factor analysis has shown that concrete experience with Science Teaching Methodology is a multidimensional construct. Two factors have been singled out whose characteristic root is greater than 1 (characteristic roots of the two selected factors: 6.953 and 3.723) and which account for 56.185% of the scale score variance.

With regard to the size of the coefficient in the matrix shown in Table 4, the first factor was named Experience related to didactic and methodical factors of the Science and social studies class delivery (items 1 to 10), while the second factor was named Experience with the delivery of Science and social studies classes (items 11 to 18). On the basis of the aforementioned factor analysis, two eponymous subscales have been constructed.

The analysis of the items within the subscale Experience related to didactic and methodical factors of the Science and social studies class delivery shows that the respondents attributed the highest value (M=4.03) to the item Analysis of Science and social studies curriculum for the first four grades of primary school, while the lowest value (M=2.43) was attributed to the item Writing lesson plans for combined classes, which was also characterized by the highest dispersion of results (SD=1.40). Furthermore, the conducted statistical analysis of the items of the subscale Experience with the delivery of Science and social studies classes shows that the highest average mean value (M=4.43) and the lowest dispersion (SD=0.77) are associated with the item Writing lesson plans. Also, high average values (M=4.30; M=4.27) have been observed for the items Consulting with a teacher-methodologist and the teacher-mentor. The lowest average value (M=4.01) has been observed for the item Analysis of examples of Science and social studies lessons, while the highest dispersion of results (SD=1.06) has been observed for the item Direct observation of delivery of a Science and social studies class by other teachers.

If we compare the results obtained for these two subscales (Table 4), we notice that the most frequently encountered concrete experiences mentioned by respondents are those related to writing lesson plans and delivering Science and social studies classes (M=4.18), while the least frequent experiences mentioned by students are those related to working in combined classes in local schools (M=2.43), analysing supplementary didactic materials for teachers (M=2.92), and identifying concrete obstacles to learning (M=3.09). These results can be explained by the fact that within this course students acquire a certain degree of concrete experience in the course of their lectures and their school practice, although they might lack a broader perspective on practical teaching which would include alternative manners of organizing and delivering classes, as well as a more thorough study of different learning styles and individual learner needs, potential obstacles to learn-

The Use of Kolb’s Model in Science Teaching Methodology

The Use of Kolb’s Model in Science Teaching Methodology

Table 4.

Results of the factor analysis for the scale Concrete experience with the Science Teaching Methodology and descriptive statistics of the items of the scale Concrete experience with Science Teaching Methodology

Factor* 1 2 0.875

Arithmetic mean

Standard deviation

2.927

1.359

2. Description of concrete obstacles to learning (insufficient prior knowledge, lack of effective learning strategies, misconceptions about the subject’s curriculum content, etc.)

3. Analysis of the student’s textbook for Science and social studies class 4. Writing lesson plans for combined classes

0.811

3.090

1.276

0.792

3.288

1.330

0.765

2.432

1.405

5. Explanation of different learning styles and individual needs of learners in Science and social studies class 6. Drafting the annual curriculum implementation plan

0.713

3.135

1.179

0.687

3.405

1.267

7. Designing objective-type assignments from the Science and social studies curriculum 8. Assessment of objective-type assignments from Science and social studies curriculum 9. Drafting the monthly curriculum implementation plan

0.681

3.396

1.169

0.674

3.261

1.141

0.668

3.378

1.293

10. Analysis of Science and social studies curriculum for the first four grades of primary school 11. Consulting with a teacher-methodologist about the practical implementation of methodology exercises for Science and social studies class 12. Consulting with the teacher-mentor about the practical implementation of methodology exercises for Science and social studies class 13. Direct observation of delivery of a Science and social studies class (other teachers, teacher-mentor, students) 14. Choice of teaching strategies, methods, techniques and procedures in accordance with the learning outcomes 15. Analysis of examples of Science and social studies lessons (different approaches) 16. Formulating educational learning outcomes

0.520

0.382

4.036

1.035

0.854

4.306

0.871

0.853

4.279

0.955

0.803

4.117

1.068

0.802

4.117

0.839

0.801

4.009

0.958

0.740

4.189

0.879

0.604

4.189

0.939

0.582

4.432

0.770

1. Analysis of manuals for elementary school teachers

17. Personal delivery of a lesson within Science and social studies teaching methodology exercises 18. Drafting a plan for delivering a specific teaching topic

Factor 1: Experience related to didactic and methodical factors of the Science and social studies class delivery Factor 2: Experience with the delivery of Science and social studies classes *To facilitate interpretation, factor saturations whose absolute value exceeds 0.3 have been shown.

The analysis of the items within the subscale Experience related to didactic and ing, and supplementary teaching materials, such as teach- tice in Science and social studies classes (items 1 to 12), methodical factors of the Science and social studies class delivery shows that the respondents and the second factor was named Reflection on the deliving manuals. attributed the highest value (M=4.03) to the item Analysis of Science and social studies ery of Science and social studies classes (items 13 to 16). curriculum for the first four grades of primary school, while the lowest value (M=2.43) was Results of factor and descriptive analysis in On the basis of the said factor analysis, two eponymous attributed to the item Writing lesson plans for combined classes, which was also characterized by subscalesthe have been constructed 5). of the teacher training the highest dispersion of results (SD=1.40). Furthermore, conducted statistical(Table analysis Results of the Reflection on the links between The conducted factor analysis has shown that items of the subscale Experience withreflective the delivery of Science andsubscale social studies classes shows anddispersion practice in(SD=0.77) Science and studies classes observation Science Teaching is aand theory thatinthethe highest average meanMethodology value (M=4.43) the lowest are social associated show thatvalues the highest mean M=4.27) value (M=3.86) and the lowest multi-dimensional Two lesson factors plans. with the characwith the construct. item Writing Also, high average (M=4.30; have been observed for the items Consulting teacher-methodologist and the teacher-mentor. dispersion of results (SD=0.93) is associated The with the item teristic root greater than 1 (characteristic roots with of thea two lowest 7.930 average (M=4.01) hassingled been observed for the item Analysis of examples of Science between achieved education objectives and tasks and selected factors: andvalue 1.707) have been out, Links accounting for 60.233% of the scale score variance. With methodological procedures. The lowest average mean value for the item Analysis of an regard to the size of the coefficient, the first factor was (M=2.37) has been observed Propósitos y Representaciones Aug. 2020, Vol. 8, SPE(2), e685 the highnamed Reflection on the links between theory and prac- educational show or a journal for children, while http://dx.doi.org/10.20511/pyr2020.v8nSPE2.685

Volume 52, Issue 3 • 45

studies classes (items 1 to 12), and the second factor was named Reflection on the delivery of Science and social studies classes (items 13 to 16). On the basis of the said factor analysis, two The Useeponymous of Kolb’s Modelsubscales in Science Teaching Methodology have been constructed (Table 5).

Table 5.

Results of the factor analysis of the scale Reflective observation in the Science Teaching Methodology and descriptive statistics of the items of the scale Reflective observation in the Science Teaching Methodology 1. Analysis of the pedagogical and didactic theories employed during a Science and social studies lesson 2. Analysis of learning theories on which the Science and social studies teaching activity was based 3. Analysis of emotions stirred by living and/or evoking the experience of delivering a Science and social studies class 4. Explaining the teaching strategies, methods and procedures used in Science and social studies classes 5.Explaining one’s own actions, beliefs, values and motives in a Science and social studies lesson 6. Linking the achieved educational objectives with tasks and chosen methodological procedures 7. Explanation of different classroom management styles and manners of addressing disciplinary issues 8. Analysis of the teacher-mentor’s personal pedagogical documentation (lesson plan, planning and programming, etc.) related to a Science and social studies class 9. Analysis of an educational show or a journal for children

Factor* 1 0.860

Arithmetic mean 3.481

Standard deviation 1.106

0.822

3.445

1.054

0.784

3.363

1.114

0.761

3.854

0.975

0.750

3.581

1.103

0.749

3.863

0.933

0.745

3.481

1.011

0.721

3.445

1.223

2.372

1.171

0.702

The of Kolb’s in Science Teaching 10.Use Analysis of Model personal opinions, fears, Methodology doubts and 0.692

2

0.427

3.627 1.073 uncertainties about the delivery of Science and social studies classes 11. Analysis of objectives and learning outcomes achieved 0.597 3.818 0.949 during a Science and social studies class 12. Explaining one’s own difficulties in delivering Science 0.563 0.313 3.645 1.185 Propósitos y Representaciones and social studies classes Aug. 2020, Vol. 8, SPE(2), e685 13. Analysis of one’s own class delivered in cooperation 0.841 4.136 1.008 http://dx.doi.org/10.20511/pyr2020.v8nSPE2.685 with a teacher-methodologist, teacher-mentor and other students 14. Analysis of a directly observed class (social forms of 0.722 4.000 0.918 teaching used, teaching methods and procedures used, achieved objectives and lesson articulation) 15. Analysis of feedback from a teacher-methodologist 0.660 4.000 1.125 about the delivery of a Science and social studies class 16. Analysis of feedback from the teacher-mentor about the 0.439 0.510 3.800 1.262 delivery of a Science and social studies class Factor 1: Reflection on the links between theory and practice in Science and social studies classes Factor 2: Reflection on the delivery of Science and social studies classes *To facilitate interpretation, factor saturations whose absolute value exceeds 0.3 have been shown.

Results of the subscale Reflection on the the links between mean theory and practice in Science est dispersion of results (SD=1.22) was observed for est arithmetic (M=4.13) is the Analysis of one’s own and social studies classes show that the highest mean value (M=3.86) and the lowest dispersion item Analysis of personal pedagogical documentation of class delivered in cooperation with other teachers, while the results (SD=0.93) is associated with the item Linkslowest between achieved education objectives and the of teacher-mentor. standard deviation (SD=0.92) has been observed for tasks and methodological procedures. The lowesttheaverage mean value (M=2.37) has been item Analysis of a directly observed class. The results The analysis of results of the subscale Reflection on the observed for the item Analysis of an educational show or a journal for children, while the highest delivery of Science and social studies classes has shown that obtained by means of the descriptive and factor analysis of dispersion of results (SD=1.22) was observed for the item Analysis of personal pedagogical the lowest average mean value (M=3.64) has been observed both subscales (Table 5) show a higher degree of reflection documentation of the teacher-mentor. for the item Explaining one’s own difficulties in delivering about the structure and delivery of the lesson in comparison Science and social studies classes, while the highest disper- to the reflection about the use of pedagogical and didactic The analysis of results of the subscale Reflection on the delivery of Science and social sion (SD=1.12) has been observed for the item Analysis of theories and personal impressions (e.g. emotions and diffistudies classes has shown that the lowest average mean value (M=3.64) has been observed for the feedback from the teacher-mentor about the delivery of a culties) of students during a lesson. The presented results item Explaining one’s own difficulties in delivering Science and social studies classes, while the Science and social studies class. The item with the high- seem to suggest that the majority of respondents practice

highest dispersion (SD=1.12) has been observed for the item Analysis of feedback from the teacher-mentor about the delivery of a Science and social studies class. The item with the highest arithmetic meanJournal (M=4.13) is the Analysis of one’s own class delivered in cooperation with other 46 • Mensa Research teachers, while the lowest standard deviation (SD=0.92) has been observed for the item Analysis

The Use of Kolb’s Model in Science Teaching Methodology

S., Tatković, & Tatković, S. reflection without a deeper analysis of theoretical founda- 2005), whoMočinić, argue that teachers’ N., reflection-in-action and tions on which teaching and learning are based, failing to reflection-on-action (Schön, 1987), i.e. reflection during draw links between methodological theory and practice. and after delivering a class, is mostly based on impressions Another opinion we find interesting is that presented bydynamic, M. Fullan and A. Hargreaves during tumultuous and hectic events This conclusion is supported by theoretical contempla- gained (Fullan & Hargreaves, 2005), who argue that teachers’ reflection-in-action and reflection-ontions by several authors (Striano, 2001; Valenčić-Zuljan & which are typical for classroom life and that such evaluaaction2012; (Schön, 1987),et i.e. reflection and after a class, mostly for based on analytions, delivering although useful, are notissufficient a deeper Vogrinc, Korthagen al., 2001; Altet etduring al., 2006) impressions gained during dynamic, tumultuous and hectic events which are typical for classroom who argue that technical and rational models which do not sis of the teaching practice. Namely, individual experience life and that reflection such evaluations, although notreflection sufficient for a only deeper analysis comprise a small part ofofthethe teaching include a deeper on one’s own teaching useful, practice areand teaching practice.

Namely, individual experience and reflection comprise only a small part of the practice, which needs to be linked with other experiences are still being used in methodology exercises and pedagogwhich needs betolinked with other experiences and theoretical assumptions. and theoretical assumptions.

For reflection to be truly thoricalteaching practice. practice, Students are doing theirto best harmonize For reflection to be truly thorough, it requires “a different pair of eyes”, i.e. it needs to be observed i.e. it needs to their class delivery with the prescribed models or guidelines ough, it requires “a different pair of eyes”, another perspective apart from the of one based on the general of effectiveness be observed fromimpression another perspective apart fromofthe one forfrom educational work, while assessment consists checkspecific situation.

Additionally, forms of general reflection usuallyof effectiveness lack a critical on the impression of a specifingawhether theeducation delivery is in line with the expectations these of based consideration of objectives and principles on which the teaching activity is based, of the level of ic education situation.

Additionally, these forms of reflecmentors and teachers-methodologists and of pointing out cognitive activity of pupils, of an equal participation of all pupils in the activity, and of the mistakes of technical and procedural character. Further- tion usually lack a critical consideration of objectives and influence of the context on(2001) the effectiveness the teaching (Fullan & Hargreaves, principlesprocess on which the teaching activity is2005). based, of the more, in her research, M. Striano encountered of logisHowever, it is important to emphasize that critical thinking skills do not develop spontaneously, tic and organizational difficulties which impair a conscious level of cognitive activity of pupils, of an equal participaneed to articulation be systematically developed in the course of pupils teachers’ later of the tion of all in theinitial activity,training and of theand influence andbut systematic and awareness of reflective professional which is also confirmed by research

by B. Bognar (2009) process and L.(Fullan on the effectiveness of the teaching processes which development, occur during educational work.

This context Mortari (2011). comment by M. Striano can be linked with a commonly & Hargreaves, 2005). However, it is important to emphaencountered lack of an appropriate space and time for the size that critical thinking skills do not develop spontaneconducted has shownously, that but abstract in Science need toconceptualization be systematically developed in the course analysis of aThe lesson in trainingfactor schools.analysis Teachers-mentors Teaching Methodology is a one-dimensional construct.

One factor with characteristic root greater developneed to continue working with pupils, while students are of teachers’ initial training and later professional than 1 (characteristic root: 5.614) has been singled out, accounting for 70.180% of the scale score required to continue fulfilling other course obligations at ment, which is also confirmed by research by B. Bognar This factor was named Links between theoretical insights and (2011). methodological delivery (2009) and L. Mortari thevariance. faculty/department. of Science and social studies classes (items 1 to 8) (Table 6).

On the basis of the said factor The conducted factor analysis has shown that abstract Another opinion we find interesting is that presented analysis, a single eponymous scale has been constructed.

by M. Fullan and A. Hargreaves (Fullan & Hargreaves, conceptualization in Science Teaching Methodology is a

Table 6.

Results of the factor analysis of the scale abstract conceptualization in the Science Teaching Methodology and the descriptive statistics of the items of the scale Abstract conceptualization in the Science Teaching Factor* Arithmetic Standard Methodology 1 mean deviation 1. Linking acquired experiential knowledge with theoretical 0.890 3.270 1.086 insights into the methodological issues of teaching Science and social studies classes 2. Proposing solutions for concrete difficulties, problems and 0.855 3.072 1.173 obstacles in a teaching situation 3. Devising and proposing changes for schools for the future 0.852 3.036 1.190 4. Finding connections between specific factors in Science and 0.842 3.189 1.124 social studies classes 5. Linking theoretical postulates from psychology and pedagogy 0.831 3.099 1.111 with personal findings about the delivery of Science and social studies classes 6. Presenting personal findings about teaching Science and 0.818 2.747 1.209 social studies in papers written for professional/scientific conferences or pedagogical journals 7. Linking personal findings about teaching science and social 0.817 3.144 1.142 studies concepts with learning and teaching theories 8. Creating proposals for new approaches to methodological 0.794 2.955 1.155 issues of teaching science and social studies Factor 1: Links between theoretical insights and methodological delivery of Science and social studies classes *To facilitate interpretation, factor saturations whose absolute value exceeds 0.3 have been shown.

Analysis (Table 6) of the items of the scale named Links between theoretical insights and methodological delivery of Science and social studies classes shows that theVolume item 52, Linking Issue 3 • 47

The Use of Kolb’s Model in Science Teaching Methodology

Močinić, S., Tatković, N., & Tatković, S.

Table 7.

Results of the factor analysis of the scale active experimentation in Science Teaching Methodology and the descriptive statistics of the items of the scale Active experimentation in Science Teaching Methodology

Factor* 1 0.840

Arithmetic mean 2.718

Standard deviation 1.204

1. Development of a supplementary instrument for monitoring students’ progress 2. Carrying out smaller research assignments (e.g. the extent to 0.836 2.254 1.207 which ICT is used in the training centre for teaching science and social studies concepts) 3. Description of the innovations introduced in school practice, 0.835 2.609 1.142 based on reflective practice and action research on science and social studies classes 4. Re-delivering the same teaching unit from the Science and social 0.834 2.336 1.213 studies curriculum with the introduction of new elements 5. Description of the conducted action research about concrete 0.815 2.572 1.266 methodological issues in science and social studies classes 6. Developing precise criteria for assessment of pupils’ knowledge 0.792 2.636 1.147 at different levels according to the selected taxonomy 7. Microteaching - a short simulation of teaching situations from the 0.790 2.090 1.161 science and social studies curriculum, recorded by means of a video camera and then analysed 8. Creating didactic games (for environmental education, traffic 0.675 3.127 1.134 education etc.)

9. Participation in practice communities for the purpose of 0.550 3.072 1.155 comparing experiences Factor 1: Using the acquired knowledge and innovations in Science and social studies classes * To facilitate interpretation, factor saturations whose absolute value exceeds 0.3 have been shown.

one-dimensional One the factor with characterisers to conduct joint research and publish papers together On construct. the one hand, lack of active experimentation at Faculties of Teacher Education is tic root greater than 1 (characteristic root: 5.614) has been with students, in journals or in conference understandable due to a lack of adequate facilities and working conditions in which such proceedings. forms singled out, accounting 70.180% ofbut thealso scaledue score Apart from that, it isexperience, our belief that future teachers, i.e. of teaching can be for implemented, to students’ insufficient which prevents variance.

This factor was named Links between theoretistudents of teacher education studies, lack them from influencing more significant changes in the education process, especially if they support lack in cal insights and methodological delivery of Science and the organization of forums and learning communities support from their teachers-methodologists and teachers-mentors. This is further supported by B. by socialBognar’s studies classes (items 1 toaccording 8) (Table 6). the basis meansinnovations of which they might changes discuss with other the students, (2009) view to On which significant include in both of the said factor analysis, a single eponymous scale has school teachers, teachers-mentors and pedagogues about values and the theoretical understanding of the education process, as well as adoption and been constructed. theirstudents practical cannot experiences in light oftothedo. most development of a new educational philosophy, which be expected On important the theories of learning and teaching.

Such discussions Analysis (Table 6) of the items of the scale named Links other hand, the development of the teacher-researcher, who will analyse and evaluate his or her might a clearer interpretation of the results achieved in between insightsand andstudents’ methodological delivery owntheoretical class delivery learning processprovide in order to improve his or her own teaching practice. of Science and social studies classes shows that the item practice, is being neglected, although willingness and openness to change is considered a desirable Linking acquired experiential with (Razdevšek theoretiIndispensability of reflection characteristic of teachersknowledge for the future Pučko, 2005; Polić, 2006). about the delivered classes, cal insights into the methodological issues of teaching which is essential for any deeper analysis of the professionScience and social classes has the highest mean value al activity, is confirmed researchofby B. research Bognar (2009) Seenstudies that the questionnaire was constructed specifically for the by purpose this (M=3.27), while the lowest mean value (M=2.74), as well about the introduction of substantial changes teaching. and that the items in the scales have never been used before, it was necessary to establishin the as the highest dispersion (SD=1.21), has been observed Teachers involved in Bognar’s action research have internal reliability coefficient for some of the scales and subscales, which was done by means ofrepeatfor the item Presenting personal findings about teaching edly emphasized the importance of a critical evaluation of the Cronbach’s alpha coefficient. Analysis has shown that all scales have satisfactory reliability Science and social studies in papers written for profession- one’s own teaching practice, as the awareness of a lack of coefficients of the internal consistency type, ranging between 0.80 (α = 0.863) and 0.93 (α = al/scientific conferences or pedagogical journals. teaching experience fosters the introduction of changes, 0.932).

The obtained results of factor and descriptive analysis of especially if they are discussed with critical friends, in learning communities or forums,subscales which allows to gain a the previous scale couldto partially be explained byof a lack In order get a clearer image the of average results of individual and one scales, broader perspective of the issue.

However, in the review of the teaching practice and a lack of critical thinkfactor reduction was conducted and descriptive statistics, symmetry and kurtosis were calculatedcourse of his research, Bognar has noticed that the were willingness ing about among students.

Anoth- homogeneous (Tablethe8).lived Theexperience highest average and relatively results (M=4.17; SD=0.67) to discuss and exchange experiences is not always er possible reason for the low average values obtained for obtained for the subscale Experience with the implementation and delivery of Science and socialreadily accepted; rather, it has is frequently met with a certain degree abstract conceptualization in Science Teaching Methodolostudies classes. In the same subscale, a strong negative asymmetry been observed (S=-1.07), gy might be the insufficient motivation of university teach- of resistance and refraining from sincere comments. TherePropósitos y Representaciones

48 •Aug. Mensa Journal 2020,Research Vol. 8, SPE(2), e685

http://dx.doi.org/10.20511/pyr2020.v8nSPE2.685

The Use of Kolb’s Model in Science Teaching Methodology

fore it is advisable to encourage this form of work already to students’ insufficient experience, which prevents them from influencing more significant changes in the education during teachers’ initial training.

The conducted factor analysis has shown that active process, especially if they lack support from their teachexperimentation in Science Teaching Methodology is a ers-methodologists and teachers-mentors. This is further one-dimensional construct. One factor whose characteris- supported by B. Bognar’s (2009) view according to which tic root is greater than 1 (characteristic root of the factor: significant innovations include changes in both the values 5.469) has been singled out, accounting for 60.764% of and the theoretical understanding of the education process, the scale score variance. That factor was named the Use of as well as adoption and development of a new educational acquired knowledge and innovations in Science and social philosophy, which students cannot be expected to do. On studies classes (items 1 to 9) (Table 7). On the basis of the other hand, the development of the teacher-researcher, the aforementioned factor analysis, one eponymous scale who will analyse and evaluate his or her own class delivhas been constructed. If we examine the scale (Table 7) ery and students’ learning process in order to improve his Use of acquired knowledge and innovations in science or her own teaching practice, is being neglected, although and social studies classes, we can observe that the respon- willingness and openness to change is considered a desirdents attributed the highest average (M=3.12), although able characteristic of teachers for the future (Razdevšek rather inhomogeneous values (SD=1.13) to the item Creat- Pučko, 2005; Polić, 2006). ing didactic games. Although highest in comparison with Seen that the questionnaire was constructed specificalother scale scores, the obtained average value is relatively ly for the purpose of this research and that the items in low and non-homogeneous. The lowest average values have the scales have never been used before, it was necessary been obtained for the items Microteaching (M=2.09) and to establish the internal reliability coefficient for some of Carrying out smaller research assignments (M=2.25). The the scales and subscales, which was done by means of the obtained results of the factor analysis and descriptive analy- Cronbach’s alpha coefficient. Analysis has shown that all sis show that the majority of students rarely introduce new scales have satisfactory reliability coefficients of the interprocedures during their demonstration lessons of Science nal consistency type, ranging between 0.80 (α = 0.863) and and social studies, and that the new elements are usual- 0.93 (α = 0.932).

The Use of Kolb’s Model in Science Teaching Methodology ly limited by the available choice of teaching technology.

In order to get a clearer image of the average results Furthermore, the obtained results indicate that research of individual subscales and scales, factor reduction was assignments are not frequently implemented in the Science conducted and descriptive statistics, symmetry and kurtowhich means that the results are grouped around high values. On the basis of the obtained results Teaching Methodology. sis were calculated (Table 8). The highest average and it can be concluded that the lesson preparation and delivery under the guidance of the teacherOn the one hand, the lack of active experimentation at relatively homogeneous results (M=4.17; SD=0.67) were mentor and a teacher-methodologist is one of the predominant professional experiences within Faculties of Teacher Education is understandable due to a obtained for the subscale Experience with the implementhis methodology. However, we wonder how sufficient is the professional training of future lack of adequate facilities and working conditions in which tation and delivery of Science and social studies classes. teachers which is based only on the acquisition of practical experiences related to the delivery of such forms of teaching can be implemented, but also due In the same subscale, a strong negative asymmetry has

new teaching contents and use of classroom management techniques?

Table 8.

Descriptive statistics, symmetry, kurtosis and reliability of scales and subscales (Science Teaching Methodology) Name of scale or subscale Knowledge 1.a Familiarity with didactic / methodology-related acquisition curriculum contents of the Science Teaching Methodology 1.b Familiarity with the key features of the subject “Science and social studies” 1.c Familiarity with the essential curriculum contents of the Science Teaching Methodology Concrete 2.a Experience with didactic and methodical factors experience of the Science Teaching Methodology 2.b Experience with the implementation and delivery of Science and social studies classes Reflective 3.a Reflection on links between theory and practice in observation Science Teaching Methodology 3.b Reflection on the delivery of Science and social studies classes Abstract 4. Links between theoretical insights and conceptualization methodological delivery of Science and social studies Active classes 5.

Use of acquired knowledge and innovations in experimentation Science and social studies classes

N 110

M 3.971

SD 0.630

S -0.862

K 1.469

alpha 0.893

111

4.063

0.670

-0.488

-0.266

0.863

111

3.736

0.872

-0.842

0.559

0.932

111

3.235

0.914

-0.330

-0.455

0.903

111

4.172

0.676

-1.072

0.991

0.894

110

3.498

0.802

-0.692

0.322

0.927

110

3.984

0.862

-0.981

0.901

0.804

111

3.064

0.916

-0.180

-0.929

0.934

110

2.602

0.961

-0.030

-0.490

0.917

Volume 52, Issue 3 • 49

Unfortunately, exemplary activities such as accompanying pupils on school trips and

The Use of Kolb’s Model in Science Teaching Methodology

been observed (S=-1.07), which means that the results are grouped around high values. On the basis of the obtained results it can be concluded that the lesson preparation and delivery under the guidance of the teacher-mentor and a teacher-methodologist is one of the predominant professional experiences within this methodology. However, we wonder how sufficient is the professional training of future teachers which is based only on the acquisition of practical experiences related to the delivery of new teaching contents and use of classroom management techniques?

Unfortunately, exemplary activities such as accompanying pupils on school trips and excursions, organization of integrated and extra-classroom teaching, outdoor education and similar is still only rarely encountered, which is understandable to a certain extent, as it is technically difficult to implement such forms of teaching in the current conditions of cooperation between teacher education faculties and training schools, especially when it comes to the implementation of methodology exercises. Extraclassroom teaching and outdoor education are costly and no financial resources have been allocated for these activities, neither in training schools nor in higher education institutions. Furthermore, in order to enable participation of students in extra-classroom teaching, outdoor education, and winter or summer holidays, it is necessary to provide longer periods of student practice in the curricula of teacher education studies, with a higher level of responsibility as well as practical experience with organizing and implementing such forms of teaching.

The lowest average value (M=2.60) has been obtained for the scale Using the acquired knowledge and innovations in Science and social studies classes, which is also characterized by the highest standard dispersion (SD=0.96), indicating that students’ answers in this scale were relatively heterogeneous and that their experiences with introducing innovations in methodology exercises for Science and social studies classes differ significantly. As mentioned before, students cannot be expected to introduce substantial changes in conceptions of teaching and in study programs or to solve problems of the school system, but they can be encouraged to make changes related to their personal and professional development, learning process, teaching strategies, teacher-student relationship, creative learning and similar. How successful their efforts will be depends on numerous factors, among which the most crucial ones are school atmosphere, support of teachers-methodologists, friendly and cooperative relationship with teachers-mentors, and students’ willingness to introduce innovations, i.e. their resistance to or fear of change.

The obtained correlations among scales and subscales (Table 9) are mostly positive and statistically significant, whereas the highest degree of positive correlation (r=0.811; p<0.01) has been observed between the scales

50 • Mensa Research Journal

Links between theoretical insights and methodological delivery of Science and social studies classes and Use of the acquired knowledge and innovations in Science and social studies classes. In this case, the correlation between the two aforementioned scales was expected, because students need to be able to implement the acquired theoretical knowledge in practice during their lectures on methodological issues of Science and social studies classes. A high degree of correlation (r=0.739; p<0.01) between subscales Familiarity with the essential curriculum contents and Familiarity with didactic/methodology-related curriculum contents of the Science Teaching Methodology indicates an interdependence of pedagogical and psychological sciences and substrate sciences in the Science Teaching Methodology.

There is no correlation between the subscale Familiarity with key features of the subject “Science and social studies” and subscales Links between theoretical insights and methodological delivery of Science and social studies classes (r=0.080) and Use of the acquired knowledge and innovations in Science and social studies classes (r=0.062).

Furthermore, there is no correlation between the subscale Experience with the delivery of Science and social studies classes and the scales Links between theoretical insights and methodological delivery of Science and social studies classes (r=0.129) and Use of the acquired knowledge and innovations in Science and social studies classes (r=0.027).

The lack of correlation between familiarity with key features of the subject “Science and social studies” and the delivery of classes from that subject was expected, as the organizational structure of the subject Science and social studies is of formal character, which means that the subject is artificially created and named differently in different countries, encompassing various topics from several substrate sciences and organized in accordance with pupils’ psycho-physical characteristics rather than with the system of particular scientific areas (De Zan, 1999). The aforementioned characteristics are accepted as such and are not linked with methodological delivery of the subject or with innovations in teaching.

A rather high level of correlation between the constructs related to the links and the use of knowledge from Science Teaching Methodology seems to suggest that the respondents do not perceive the difference between the two constructs. The lack of correlation between the experience with the delivery of Science and social studies classes, abstract conceptualization and use of the acquired knowledge does not necessarily mean that students do not recognize the cyclical process of experiential learning as presented by Kolb (Kolb, 1984, Kolb, 2015) in cognitive processes related to this methodology; rather, they might simply be at one of the stages of experiential learning which does not coincide with the constant change of stages in Kolb’s spiral cycle.

essential curriculum contents and Familiarity with didactic/methodology-related curriculum contents of the Science Teaching Methodology indicates an interdependence of pedagogical and psychological sciences and substrate sciences in the Science Teaching Methodology.

The Use of Kolb’s Model in Science Teaching Methodology Table 9.

Correlations among scales and subscales of the Science Teaching methodology questionnaire Name of scale and Pearson’s correlation among scales and subscales subscale 1.a 1.b 1.c 2.a 2.b 1.a Familiarity with 1 didactic/methodologyrelated curriculum contents of Science Teaching Methodology 1.b Familiarity with 0.612** 1 key features of the subject “Science and social studies” 1.c Familiarity with 0.739** 0.607** 1 the essential curriculum contents of the Science teaching methodology 2.a Experience with 0.443** 0.266** 0.557** 1 didactic/methodologyrelated factors of Science and social studies classes 2.b Experience with 0.509** 0.513** 0.398** 0.322** 1 the delivery of Science and social studies classes 3.a Reflection on the 0.417** 0.291** 0.390** 0.620** 0.467** links between theory and practice in Science and social studies classes 3.b Reflection on the 0.290** 0.400** 0.255** 0.246** 0.676** delivery of Science and social studies classes 0.325** 0.584** 0.129 4. Links between 0.318** 0.080 theoretical insights and methodological The Use of delivery of Kolb’s ScienceModel in Science Teaching Methodology and social studies classes The Use of Kolb’s Model in Science Teaching Methodology 0.062 0.359** 0.591** 0.027 5.and Use ofsocial the acquired studies 0.255** knowledge and classes innovations in Science and social studies classes

3.a

3.b

4.

5.

1

0.582**

1

0.574**

0.313**

1

0.538**

0.203**

0.811**

1

** p˂0.01; * p˂0.05

Propósitos y Representaciones

Aug. 2020, Vol.authors 8, SPE(2), e685researched the application of Numerous have of published research studies on both K-12 education and There is no correlation between the subscale Familiarity with key features of the subject http://dx.doi.org/10.20511/pyr2020.v8nSPE2.685 p˂0.01; * p˂0.05 the**Kolb’s experiential learning model in designing and the education of adults which is most commonly integrated “Science and social studies” and subscales Links between theoretical insights and methodological realising study programs (Svinicki & Dixon, 1987; Shar- in higher education. delivery of Science and socialbetween studies classes (r=0.080) and Usewith of the knowledge and There no Kolb, correlation the subscale keyacquired features of the of subject lanova, 2004; Kolbisand 2005; Reggio, 2010; Roark Familiarity In Croatia the possible application Kolb’s model in innovations in Science andand social studiesLinks classes (r=0.062).

Furthermore, there is no correlation “Science and social studies” subscales between theoretical insights and methodological & Norling, 2010), rising the scientific level of research education was studied by the author V. Vizek Vidović betweenofthe subscale withclasses the delivery of Science social studiesknowledge classes andand the delivery Science andExperience social studies (r=0.080) and Useand of the acquired on teaching practices (Sanders & MacCutcheon, 1986, (Vizek Vidović, 2005; Vizek Vidović, 2011), but not in scales Links between theoretical insights and methodological delivery of Science and social innovations in Science and social studies classes (r=0.062). Furthermore, there is no correlation Mortari, 2011), teaching geography at universities (Healey the field of Science Teaching Methodology and teachers’ studies classes (r=0.129) and Usewith of thethe acquired knowledge innovations in Science between the subscale Experience delivery of Scienceand and social studies classesand andsocial the & Jenkins, 2000), e-learning (Correia, 2008) and other initial education.

Therefore, this research is relevant; it studies classes (r=0.027). scales Links between theoretical insights and methodological delivery of Science and social fields of education. Most research on the application of shows that the whole course of a subject can be organised studies classes (r=0.129) and Use of the acquired knowledge and innovations in Science and social experiential learning inof education havebetween been conducted in with so as key to enable students’ successful learning.

The lack correlation familiarity features of themore subject “Science and Namely, studies classes (r=0.027). the subject Science Teaching Methodology to be effechigher education.

There a relatively small number social studies” andhas thebeen delivery of classes from thatfor subject was expected, as the organizational

structure the of subject Science and social studieswith is ofkey formal character, which means thatand the Theoflack correlation between familiarity features of the subject “Science subject is artificially created and named differently in different countries, encompassing various social studies” and the delivery of classes from that subject was expected, as the organizational Volume 52, Issue 3 • 51 topics from several substrate and studies organized in formal accordance with pupils’ structure of the subject Sciencesciences and social is of character, which psycho-physical means that the characteristics rathercreated than with the system of particular scientific areasencompassing (De Zan, 1999).

The subject is artificially and named differently in different countries, various

The Use of Kolb’s Model in Science Teaching Methodology

tive and help students become teachers and reflective practitioners, all the steps of the spiral cycle should be included in university teaching, and it includes four phases: experience, reflection, generalisation and application, repeating interchangeably.

Conclusions

In selecting the relevant theoretical framework, Kolb’s experiential learning model was chosen, which is not easily applicable to our educational conditions and traditions.

Furthermore, availability of publications from the studied area of interest in Croatia was rather limited. According to the results obtained by means of a student questionnaire and on the basis of the conducted descriptive and factor analysis, it can be concluded that the aforementioned methodology is dominated by the acquisition of academic and methodological knowledge, whereas the activities of concrete teaching experience are occasionally encountered, the reflection on the lived experience is rarely encountered, and experimentation and introduction of innovations in teaching is very rarely encountered. It can also be concluded that there is a lack of balance between theoretical and practical knowledge, while their mutual integration is insufficient. This confirms both initial hypotheses.

With regard to the obtained results, we can conclude that it is necessary to introduce a greater degree of concrete experience in the initial teacher training curriculum and to integrate it with theoretical knowledge. With regard to the obtained results it is necessary to introduce a greater degree of concrete experience in the initial teacher training curriculum and to integrate it with theoretical knowledge.

References

Altet, M., Charlier, E., Paquay, L., Perrenoud, Ph. (2006).

Formare gli insegnanti professionisti. Quali strategie? Quali competenze? Roma: Armando editore.

Anđić, D. (2007). Learning and teaching nature and society in open spaces. Methodical Horizons, 2(1), 7-23.

Bognar, B. (2009). Making essential changes in educational practice through action research. Educational Sciences, 11(2), 147-162.

Borić, E. (2009). Research teaching nature and society. Osijek: Učiteljski fakultet.

Borić, E., Škugor, A., Perković, I. (2010). Teachers’ selfassessment of extracurricular research teaching of nature and society. Educational Sciences, 12(2), 361-373.

Correia, A.P. (2008). A shift from theory to real-world experiences in the e-learning community. Edupoint Magazine, 8(65).

De Zan, I. (1999). Methods of teaching nature and society.

Zagreb: Školska knjiga.

De Zan, I. (2005). Methods of teaching nature and society.

Zagreb: Školska knjiga.

Fullan, M., Hargreaves, A. (2005). Cosa vale la pena cambiare nella nostra scuola? Trento: Erickson.

52 • Mensa Research Journal

Healey, M., Jenkins, A. (2000). Kolb’s experiential learning theory and its application in geography in higher education.

Journal of Geography, 99, 185-195.

Kolb, A.Y., Kolb, D.A. (2005). Learning styles and learning spaces: Enhancing experiential learning in higher education. Academy of Management Learning & Education, 4(2), 193-212.

Kolb, D.A. (1984). Experiential learning. Experience as the source of learning and development. New Jersey: Prentice Hall.

Kolb, D.A. (2015). Experiential learning: experience as the source of learning and development. New Jersey: Pearson Education.

Kolb, D.A., Fry, R. (1975). Towards an applied theory of experiential learning. New York: Wiley.

Korthagen, F.A.J., Kessels, J., Koster, B., Lagerwerf, B., Wubbels, T. (2001). Linking practice and theory. The pedagogy of realistic teacher education. New York, London: Routledge.

Letina, A. (2016). The effectiveness of research-oriented teaching of nature and society in the development of students’ natural science competencies. Croatian Journal of Education, 18(3), 665-696.

Mortari, L. (2011). Ricercare e riflettere. La formazione del docente professionista. Roma: Carocci editore.

MoSES. (2016). National curriculum for the school subject “Science and social studies” Retrieved from: http://mzos.hr/ datoteke/7-Predmetni_kurikulum-Priroda_i_drustvo.pdf Passarelli, A.M., Kolb, D.A. (2011). The Learning Way – Learning from Experience as the Path to Lifelong Learning and Development. In book: M. London (Ed.), Handbook of Lifelong Learning. Retrieved from: https://weatherhead. case.edu/departments/organizational-behavior/workingPapers/WP-09-03.pdf Polić, M. (2006). Facts and values. Zagreb: Hrvatsko filozofsko društvo.

Razdevšek Pučko, C. (2005). What kind of teacher / teacher does the school need (expected) today (and tomorrow)?

Progress, 146(1), 75-90.

Reggio, P. (2010). Guida all’apprendimento esperienziale.

Roma: Carocci editore.

Roark, M.F., Norling, J.C. (2010). An application of a modified experiential learning model for a higher education course.

Evidence of increased outcomes. Journal of Outdoor Recreation, Education and Leadership, 2(1), 59-73.

Sanders, D., MacChutcheon, G. (1986). The development of practical theories of teaching. Journal of Curriculum and Supervision, 2(1), 50-67.

Schön, D.A. (1987). Toward a new design for teaching and learning in the professions. San Francisco: Jossey Bass.

Sharlanova, V. (2004). Experiential learning. Trakia Journal of Sciences, 2(4), 36-39.

Striano, M. (2001). La “razionalità riflessiva” nell’agire educativo. Napoli: Liguori Editore.

The Use of Kolb’s Model in Science Teaching Methodology

Svinicki, M.D., Dixon, N.M. (1987). The Kolb model modified for classroom activities. College Teaching, 35(4), 141-146.

Szczepanski, A. (2001). What is Outdoor Education? In Other Ways of Learning. In book: 4th Euro Congress of the European Institute of Outdoor Adventure Education and Experiential Learning, pp. 17-24.

Valenčić-Zuljan, M., Vogrinc, J. (2012). Pedagogical Practice and the Process of Developing the Competences of Students of Future Classroom Teachers of the Faculty of Education, University of Ljubljana. In book: M. Valenčić-Zuljan, G. Gojkov, A. Rončević, J. Vogrinc (Eds.). Pedagogical Practice and Process of Developing Competences of Stu-

dents of Future Teachers in Croatia, Serbia and Slovenia, pp.109-137.

Vizek Vidović, V. (Ed.) (2005). Lifelong teacher education: Multiple perspectives. Zagreb: Institut za društvena istraživanja.

Vizek Vidović, V. (Ed.) (2011). Teachers and their mentors. The role of mentors in the professional development of teachers.

Zagreb: Institut za društvena istraživanja.

Vizek Vidović, V., Vlahović-Štetić, V. (2007). Adult learning models and professional development. Chronicle of Social Work, 14 (2), 283-310.

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Volume 52, Issue 3 • 53

MRJ

Entrepreneurial Learning From Failure.

A Systematic Review Wolfgang Lattacher and Malgorzata Anna Wdowiak

Abstract Purpose – Failure plays a pivotal role in entrepreneurial learning. Knowledge of the learning process that enables an entrepreneur to re-emerge stronger after a failure, though considerable, is fragmented. This paper systematically collects relevant literature, assigns it to the stages of the experiential learning process (concrete experience, reflective observation, abstract conceptualization, active experimentation; Kolb, 1984), evaluates the research coverage of each stage and identifies promising avenues for future research.

Design/methodology/approach – This systematic literature review follows the guidelines articulated by Short (2009) and Tranfield et al. (2003), using Web of Science and EBSCO as primary data sources. Kolb’s (1984) experiential learning theory provides a basis for organizing the identified material into a framework of entrepreneurial learning from failure.

Findings – The literature provides insights on all stages of the process of entrepreneurial learning from failure.

Particularly well elaborated are the nature of failure and its triggering effect for reflection, the factors influencing reflection, the contents of the resulting learning and their application in entrepreneurial re-emergence.

Other topics remain under-researched, including alternative modes of recovery, the impact of personal attributes upon reflection, the cognitive processes underlying reflection, the transformation of failure-based observations into logically sound concepts and the application of this learning in non-entrepreneurial contexts.

Originality/value – This review provides the most complete overview of research into the process of entrepreneurial learning from failure. The systematic, theory-based mapping of this literature takes stock of current knowledge and proposes areas for future research.

1. Introduction

“Entrepreneurship is a process of learning” (Minniti and Bygrave, 2001). Entrepreneurs can profit from particularly rich learning in the aftermath of critical events (Cope, 2011). One of the most critical events an entrepreneur can face is failure (Espinoza-Benavides and DÍaz, 2019) — the closure of a business that does not meet a minimum threshold for economic viability (Cope, 2011; Ucbasaran et al., 2013). Given the considerable degree of uncertainty and ambiguity associated with entrepreneurship, failure is a common phenomenon (Politis, 2008; Sarasvathy, 2001).

Entrepreneurial learning from failure is therefore important for practitioners and a topic that has recently gained traction in research.

In practice, entrepreneurial learning is important, as it improves the individual’s stock of knowledge. The knowledge acquired through failure can, under certain conditions, facilitate successful entrepreneurial re-emergence.

Moreover, failed entrepreneurs may profit from learning outcomes in other occupational contexts and when coping with subsequent critical events. From a research perspective, entrepreneurial learning from failure is interesting for at least three reasons. First, failure, despite having gained considerable research interest recently, still constitutes an emerging field with a number of questions to be answered

54 • Mensa Research Journal

(McGrath, 1999; Ucbasaran et al., 2013). Second, the application of learning theories to the context of failure may not only improve our understanding of failure but also yield opportunities to further advance learning theory.

Third, research into how entrepreneurs learn from failure responds to the call for more research that facilitates a dynamic view of entrepreneurship (Cope, 2005).

Research on entrepreneurial learning from failure emerged more than fifteen years ago (Shepherd, 2003), gaining momentum in the last few years (more than half of all studies on the topic have appeared in 2015 or later).

As initially noted by Shepherd (2003), research provides rich evidence that failure yields opportunities for learning but at the same time represents a difficult context in which to learn. While some interesting insights about the learning mechanism can be found in qualitative overview studies (Amankwah-Amoah et al., 2018; Cope, 2011; Frota Faculty of Management and Economics, Department of Innovation Management and Entrepreneurship, University of Klagenfurt, Klagenfurt, Austria International Journal of Entrepreneurial Behavior & Research Vol. 26 No. 5, 2020, pp. 1093-1131, Emerald Publishing Limited, 1355-2554, DOI 10.1108/IJEBR-02-2019-0085

Entrepreneurial Learning From Failure. A Systematic Review

Vasconcellos Dias and Martens, 2019), most research is situated in highly specialized sub-fields and discusses the influence of particular single factors on learning from failure. These factors include the individual’s initial stock of knowledge (Huovinen and Tihula, 2008; Politis, 2005; Politis and Gabrielsson, 2009), personality traits such as narcissism (Liu et al., 2019), the attribution of the failure to particular causes (Eggers and Song, 2015; Walsh and Cunningham, 2017; Yamakawa et al., 2015) and emotions (Dias and Teixeira, 2017; Shepherd, 2003; Shepherd et al., 2009). As learning is not complete until the resulting knowledge is applied to a new (entrepreneurial) context (Yamakawa and Cardon, 2015), scholars also address factors influencing knowledge transfer. Findings suggest that mindfulness of knowledge transfer (Rerup, 2005) as well as the proximity between the two ventures in time and industry (Eggers and Song, 2015) influence learning effectiveness.

Existing research thus provides deep insights into many of the elements that shape the process of entrepreneurial learning from failure. However, the high degree of specialization of many of these research endeavors leads to a fragmentation of the field (Nogueira, 2019). This, in turn, limits the progress of research, as scholars struggle to build appropriately on the work of others and to identify clear directions for future endeavors. We acknowledge the valuable review works that have been conducted by Ucbasaran et al. (2013) and Wang and Chugh (2014). However, these studies address entrepreneurial learning from failure as merely one facet of a broader research context (Ucbasaran et al., 2013: entrepreneurial failure; Wang and Chugh, 2014: entrepreneurial learning). Further, at the time of their publication, less than half of the current literature in the field existed. As a consequence, the fragmentation of the literature on entrepreneurial learning from failure requires fresh consideration, and additional review work is necessary for the further development of the field.

The present paper is aimed at addressing these issues.

Systematic review methodology is applied to collect and critically evaluate existing literature (Short, 2009; Tranfield et al., 2003) using the databases EBSCO and Web of Science. The final sample of 40 articles is organized and discussed from a processual perspective that is informed by Kolb’s (1984) theory of experiential learning. Kolb (1984) identifies four stages that an individual must go through in order to learn effectively from an experience: concrete experience, reflective observation, abstract conceptualization and active experimentation. In this review, literature findings are classified according to these stages to generate a theory-guided, processual overview of the field. Through a comparison of what should be covered in each stage according to experiential learning theory (Kolb, 1984) and what is actually discussed in the existing literature, avenues for future research are derived. Our results reveal that the exist-

ing research – while in different intensities and a dispersed manner – thematizes all stages of the experiential learning process (Kolb, 1984). Particularly well elaborated are the nature of failure and its triggering effect for reflection, specific factors influencing reflection (emotion and attribution), the contents of the resulting learning (e.g. person-, venture- or relationship-oriented) and their application in entrepreneurial re-emergence. Under-researched are alternative recovery modes (e.g. epiphanies), personal characteristics (e.g. resilience and narcissism) and their impact upon reflection. Further, the cognitive processes underlying reflection itself and especially the transformation of failure-based observations into logically sound concepts have not adequately been covered so far. Likewise, little attention has been paid to the application of learning in nonentrepreneurial contexts. With these insights, the present review contributes to research on entrepreneurial learning from failure in at least two ways. First, it provides what is, to our knowledge, the most comprehensive overview of the process of entrepreneurial learning from failure — one that, moreover, results from a systematic literature search and is informed by a clear theoretical background. Second, it identifies promising avenues for further research to build a foundation for future research endeavors.

The paper is structured as follows. First, the theoretical background and conceptual understanding of entrepreneurial learning and failure are given. Second, the methodology, in particular the systematic review approach, is presented. Third, the findings from the literature, which are processual in their focus and guided by theory, are provided. Fourth, the status quo of the research field is critically discussed. Based on this discussion, fruitful areas for future research are proposed and the practical implications of the study, as well as its limitations, are considered.

2. Theoretical and conceptual basis

2.1 Entrepreneurial learning Entrepreneurial learning is a promising research field at the interface of entrepreneurship and individual as well as organizational learning (Harrison and Leitch, 2005; Kim, 1993). Often defined as “learning in the entrepreneurial process” (Holcomb et al., 2009; Politis, 2005; Ravasi and Turati, 2005; Wang and Chugh, 2014), the field is particularly concerned with how and when learning takes place (Wang and Chugh, 2014). As Wang and Chugh (2014) show, studies on entrepreneurial learning have utilized a wide range of theoretical perspectives: experiential learning, organizational learning, social cognitive theory, population ecology and configuration theory. Among these theoretical perspectives, experiential learning has emerged in recent years as the most influential theory in entrepreneurial learning research (Fust et al., 2018).

The perspective of experiential learning conceptualizes entrepreneurial learning as a process of updating a subjecVolume 52, Issue 3 • 55

Entrepreneurial Learning From Failure. A Systematic Review

tive stock of knowledge based on experiences (Cope, 2005; formative element of Kolb’s first learning stage. This reacMinniti and Bygrave, 2001; Politis, 2005). The entrepre- tion comprises a preliminary evaluation and comparison neur learns from a given experience via personal reflec- of the event with existing abstract concepts. In the second tion and direct action (Politis and Gabrielsson, 2009). The stage, a deeper type of analysis, namely reflective observation, nature of the experience significantly influences the learn- takes place. This reflection has to be performed deliberateing process and its outcomes. As Cope and Watts (2000) ly and includes a variety of perspectives. As Duley (1981) find, insignificant experiences provoke only “lower-level” stresses, the difficulty of executing this kind of reflection learning, which involves incremental, adaptive changes tends to be the greatest obstacle to individual learning. to existing mental models.

Experiences that are perceived With a deeper of what happened, the learner research for understanding how entrepreneurs learnsense (Morris et al.,has 2012).

Kolb perceives IJEBR as critical or discontinuous, however, bear the potential subsequently enters thethrough stage of the abstract conceptualization. learning as “the process whereby knowledge is created transformation of 26,5 to occasion “higher-level” learning (Cope, 2003).

Thison the experience” (Kolb, 1984).

Drawing workstage, of Lewin (1951)isand others (e.g. Dewey, 1910; In this creativity more important than reflectivPiaget, reflection 1971), Kolb four stagesity. a learner musthas pass to learnineffectively from process involves considerable anddefines may ultimateThe learner tothrough play, mentally, order to integrate an experience.

First, the individual is exposed to a concrete experience, which is subsequently ly lead to significant changes in mind and behavior (Cope, observations into logically sound theories. As a final step, analyzed through observation.

The resulting insights are then shaped into new 2003; Pittaway and Thorpe, 2012).

As thereflective present paper is the learner enters the stage of active experimentation. Applyknowledge via abstract conceptualization and via active experimentation (see Figure 1). concerned very critical event in the life of ing the tested 1096 with failure—aThe abstract knowledge he orItshe has concrete experience is the starting point and basis for learning. acts asgenerated, a referencethe an entrepreneur (Espinoza-Benavides and DÍaz, 2019)— individual tests its adequacy. If another unexpected expeline for testing the existing abstract concepts. Kolb, citing Hegel (1953), recognizes the the concrete process of importance “higher-level” its influrience results from thishas experimentation, of learning a certainand degree of significance the experience for the learner. aInnew fact,learning “any encing factors are of particular interest.

In order to strucexperience that does not violate expectation not worthy of the name experience” episode is starts.

As a consequence, over the whole (Hegel, entrepreture existing research 1953). findings related to this process, we neurial Similarly, Dewey (1933), whose work islife, influential for Kolb’s, stresses that in1order to the process illustrated in Figure is cyclical reflection and developed learning, the flow must be interrupted by a “deep” experience— utilize the experientialinitiate learning framework by daily rather than sequential (Kolb and Kolb, 2018). Yet for the for example, being stuck with a problem, something unusual or strange. In addition to the Kolb (1984). purpose of analyzing a specific event, to a concrete experience itself, the initial reaction is a formative elementtheof reduction Kolb’s first Kolb’s approach to experiential learning theory not learner’s only four-step process appears adequate (Politis, 2005). learning stage. This reaction comprises a preliminary evaluation and comparison of the event is widely recognized in psychology but also serves as the with existing abstract concepts. In the second stage, a deeper type of analysis, namely dominant theoretical reflective framework used in entrepreneur2.2 Entrepreneurial observation, takes place. This reflection has tofailure be performed deliberately and ship research for understanding entrepreneurs learn AsEntrepreneurial failure has important field includes a how variety of perspectives.

Duley (1981) stresses, the emerged difficultyasofanexecuting this (Morris et al., 2012). Kolb learning as to “the kindperceives of reflection tends beprocess the greatest obstacle to individual learning.

With a deeper sense of research, since the seminal work of McGrath (1999) what has happened, learner subsequently entersawareness the stageofofthe abstract conceptualization. whereby knowledge isofcreated through the the transformaraised scholars’ fact that failure is an inherIn this stage, creativity reflectivity.

The learner has to play, mentally, tion of experience” (Kolb, 1984).

Drawing on is themore workimportant of ent than part of the entrepreneurship phenomenon.

Although in (e.g. orderDewey, to integrate logically theories.

As asubject final step, the learner Lewin (1951) and others 1910; observations Piaget, 1971),intothe body ofsound knowledge on this has grown tremenenters the stage active experimentation. the abstract knowledge he or she has Kolb defines four stages a learner mustof pass through to douslyApplying since then, there are still many ambiguities regardgenerated, the individual tests its adequacy. If another unexpected experience results from learn effectively from an experience. First, the individual ing our understanding of entrepreneurial failure (He et al., this experimentation, a new learning episode starts. As a consequence, over the whole is exposed to a concrete experience, which is subsequent2018;inJenkins McKelvie, 2016; Wennberg and DeTientrepreneurial life, the process illustrated Figure and 1 is cyclical rather than sequential (Kolb ly analyzed through reflective observation.

The resulting enne, 2014).

In a very broad sense, failure includes every and Kolb, 2018). Yet for the purpose of analyzing a specific event, the reduction to a four-step negative deviation of actual outcomes from expected ones insights are then shaped into new knowledge via(Politis, abstract2005). process appears adequate conceptualization and tested via active experimentation (see (Politis and Gabrielsson, 2009). If we try to grasp the basic 2.2 Entrepreneurial failure concept of entrepreneurial failure, three levels of interpreFigure 1).

Entrepreneurial failure has emerged as an important field of research, since the seminal work tation become apparent: firstly,isfailure as the disappearance The concrete experience is the starting andscholars’ basis forawareness of McGrath (1999)point raised of the fact that failure an inherent part of the of the from market, secondly an grown organizalearning. It acts as a reference line for testing the existing entrepreneurship phenomenon.

Although thefirm body of aknowledge on this failure subjectinhas tional term and thirdlyregarding failure asour defined by the personal since then, there the are still many ambiguities understanding of abstract concepts. Kolb,tremendously citing Hegel (1953), recognizes perception of the entrepreneur. entrepreneurial failure (He et al., 2018; Jenkins and McKelvie, 2016; Wennberg and DeTienne, importance of a certain degree of significance the experi2014).

In a“any veryexperience broad sense, negative deviation of actualmarket outcomes Withinevery the first vein of interpretation, persisence has for the learner.

In fact, that failure does includes from expected ones (Politis and Gabrielsson, 2009). If as wea core try to grasp the basic concept of tence is regarded criterion for entrepreneurial failnot violate expectation is not worthy of the name experientrepreneurial failure, three levels of interpretation become apparent: firstly, failure as the ure (Mitchell and Singh, 1993; Perkins, 2014). This seems ence” (Hegel, 1953). Similarly, Dewey of (1933), whose work disappearance the firm from a market, secondly failure in an organizational term and to beperception quite a narrow interpretation of the concept of failure, is influential for Kolb’s, stresses that in order to initiate thirdly failure as defined by the personal of the entrepreneur. one closely related to ecological approaches (Fotopoulos reflection and learning, the daily flow must be interrupted Within the first vein of interpretation, market persistence is regarded as a core criterion for and Louri, 2000).

However, non-survival compaby a “deep” experienceentrepreneurial — for example,failure being stuck withand a Singh, (Mitchell 1993; Perkins, 2014).the This seems to of bethe quite a narrow interpretation of the concept of failure, one closely related to ecological approaches problem, something unusual or strange. In addition to the ny within a given market does not necessarily mean the (Fotopoulos andinitial Louri,reaction 2000). However, the non-survival of the within given of the business, as ancompany organization maya continue concrete experience itself, the learner’s is a cessation market does not necessarily mean the cessation of the business, as an organization may Figure 1.

Entrepreneurial learning process (cf. Kolb, 1984)

I) Concrete experience

56 • Mensa Research Journal

II) Reflective observation

III) Abstract conceptualization

IV) Active experimentation

Entrepreneurial Learning From Failure. A Systematic Review

to exist, offering new products or services and competing in new markets or new economies (Josefy et al., 2017).

The second lens focuses on organizational failure, which is the discontinuance of a business (Bruno et al., 1992; He et al., 2018; Singh et al., 2015). This dimension primarily describes cases of bankruptcy and insolvency (Shepherd, 2003), and it also encompasses cases in which businesses have not yet reached insolvency but nevertheless suffer financial losses and poor economic viability (Ucbasaran et al., 2013). However, companies can close for reasons of a more neutral or even positive nature. Closure can occur due to the retirement of the entrepreneur or to personal changes (the desire to work socially or in another profession) (Wennberg and DeTienne, 2014; Wennberg et al., 2010).

It can also happen because of serious health problems or for reasons relating to family (DeTienne and Wennberg, 2016), as well as due to unexpected circumstances such as legal constraints, war or pandemic (e.g. Wdowiak et al., 2017).

Finally, the individual lens focuses on failure defined by the fact that it is (cognitively) perceived as such by the entrepreneur, regardless of whether or not the company survives (Cope, 2011; Ucbasaran et al., 2013). A rather obvious case refers to the closure of the company, which also involves a personally perceived failure of the entrepreneur (Cope, 2011; Singh et al., 2007). In some cases, however, the company does survive, but its development is not satisfactory from the entrepreneur’s point of view, which leads to his or her withdrawal from the company (Ucbasaran et al., 2010). Researchers argue that welleducated and experienced entrepreneurs, in particular, are willing to take this last step because they have especially high growth expectations or because they have better opportunities on the labor market (Gimeno et al., 1997).

This plethora of understandings of entrepreneurial failure, coupled with the wide range of research questions addressed in existing research (Jenkins and McKelvie, 2016), obviously leads to methodological variation.

Differences become particularly apparent in the approach to measuring entrepreneurial failure. On one side, failure is measured objectively. Most often, economic performance is used as the basis for measurement in objective approaches, as poor financial figures are generally the basis for cases of bankruptcy and insolvency (see, e.g. Jenkins and McKelvie, 2016; Shepherd, 2003; Shepherd et al., 2009; Yamakawa et al., 2015). On the other side, failure is measured subjectively. Subjective approaches build on the comparison of individually set goals and actual outcomes (Jenkins and McKelvie, 2016). Here, failure can be ascribed even to well-functioning companies that do not meet the individually defined criteria (see, e.g. He et al., 2018; Sitkin, 1992). Another subjective way of measuring failure takes into account the personal attitude and situation of the entrepreneur, acknowledging that entrepreneurs differ in

how deeply failure impacts them psychologically and financially (Cope, 2011).

In defining entrepreneurial failure for our own research purpose, we rely upon the organizational lens (discontinuance of business) and objective criteria of failure (economic performance). This approach leads to a relatively homogenous sample of organizations in terms of financial performance and triggering events. Consequently, it allows for comparison of subsequent individual reactions. Many studies that focus on learning from failure adopt this perspective (e.g. Byrne and Shepherd, 2015; Cope, 2011; Shepherd, 2003; Stam et al., 2008), which facilitates the comparison of findings. We follow Ucbasaran et al. (2013) in going beyond the very narrow criterion of bankruptcy. In fact, we include cases in which businesses are closed because they consistently create losses. As a consequence, our working definition of failure for this literature review is the closure of a business because it has not met a minimum threshold for economic viability.

3. Methodology

We conducted a systematic literature review (SLR) following the guidelines of Short (2009) and Tranfield et al.

(2003), which are established in the area of entrepreneurship (Bird et al., 2012; Nason et al., 2015; Ucbasaran et al., 2013). The SLR process is illustrated in Figure 2 (see Wang and Chugh, 2014 for a similar approach). As a starting point, we defined our research objectives, which can be summarized as analyzing the status quo and providing avenues for future research in the field of entrepreneurial learning from failure. Second, we defined our research boundaries according to the definitional considerations presented above. We focus on entrepreneurial learning from failure and define failure as the closure of a business because it has not met a minimum threshold for economic viability (Cope, 2011; Ucbasaran et al., 2013). Based on these objectives and this definition, we set the following inclusion criteria. We searched for peer-reviewed articles in the electronic databases EBSCO and Web of Science.

Within these databases, we searched simultaneously in title, keywords and abstract fields. As learning from failure is a topic in various contexts, theoretical backgrounds and research domains, we opted for a broad approach in defining the search terms. We were aware that this would imply a high number of articles to be excluded manually. However, the rather small field of our research allows for such a procedure, which decreases the risk (immanent in SLR) of missing relevant publications (Pittaway et al., 2004).

Our search operators were: (entrepr* OR self-employed) AND (fail* OR clos* OR loss* OR bankrupt* OR insolven* OR liquidat* OR death AND learn*). Applying this search agenda and limiting the search to publications in the English language led to 394 results in Web of Science and 335 results in EBSCO. As we aimed to provide a full

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Entrepreneurial Learning From Failure. A Systematic Review

picture of the development of research in this area over time, we decided to refrain from setting time restrictions.

Thus, all relevant publication activity up to and including 2019 is considered. To ensure a systematic and reliable approach, we defined exclusion criteria (for details see Appendix, Table A1). The most frequent reasons for exclusion were that articles 1) lacked an entrepreneurial focus (i.e. were situated in an organizational learning context), 2) did not focus on failure-based learning (i.e. referred to learning in other contexts than failure), and 3) provided insights into the phenomenon of entrepreneurial failure without a considerable contribution on learning (i.e. targeted failure-related questions that are irrelevant from a learning perspective). Both researchers separately read all titles and abstracts to exclude irrelevant articles. Cases of doubt were discussed and consensus was reached. For further validation, a third researcher independently applied the exclusion criteria to 100 articles gathered from Web of Science. In 99 cases, exclusion outcomes mirrored ours. In the remaining case, a consensus was reached. Applying the exclusion criteria, 30 articles from Web of Science and 26

58 • Mensa Research Journal

from EBSCO were found to be relevant. After the elimination of duplicates (22), we carefully read the remaining papers. In the course of this process, six additional articles came to our attention which focused on topics linked to learning. As they delivered important additional insights, we decided to include them in the review. Consequently, our final sample for the review consists of 40 articles.

To prepare the relevant information for the literature analysis, all sample articles were read again and open coding was applied. Specifically, we identified which of the four stages of experiential learning each publication considered. In addition, we analyzed the articles’ key contributions and collected general information relating to authorship, methodology and publication outlet. To secure an objective process, the coding of all articles was executed by both researchers separately. Although there was a degree of subjective judgment involved in the classification of the literature results according to the experiential learning phases, the coding of 36 of 40 sample articles was consistent. In the remaining four cases, a consensus was reached by revisiting the articles and discussing the nature

Entrepreneurial Learning From Failure. A Systematic Review

IJEBR 26,5

8 7 6

1100

5 4 3 2 1

Figure 3.

Publication distribution (time and methodology)

0

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Conceptual

Qualita�ve

Quan�ta�ve

Mixed

understanding of entrepreneurial learning from experience, specifically elaborated on failure of their findings. As a consequence, thetype finalof data basis for From 2008), grief (Shepherd et al.,studies 2009), on attitudes failas an important experience.

2007 onward, empirical a widetoward range of this review represents the shared understanding of the two ure (Politis and Gabrielsson, 2009), comparative optimism relevant topics, such as re-engagement (Stam et al., 2008), experience transformation researchers.

(Ucbasaran al., 2010) and toward attribution (Ucbasaran et al., (Huovinen and Tihula, 2008), grief (Shepherd et al.,et2009), attitudes failure (Politis and Gabrielsson, 2009), comparative optimism (Ucbasaran et al., 2010) attribution (Ucbasaran 2011) emerged. These studiesand increased knowledge but also et al., 2011) emerged. These studies increased knowledge butwhich also led fragmentation, 4. Results led to fragmentation, wastopartly solved by which a second was partly solved by a second wave of conceptual studies (2012–2014) that sought to make to 4.1 Development of the field wave of conceptual studies (2012–2014) that sought sense of the earlier empirical findings (Coad, 2014; Pittaway and Thorpe, 2012; Ucbasaran Entrepreneurial learning from failure is a young and high- make sense of the earlier empirical findings (Coad, 2014; et al., 2013). The substantial body of recent research shows three main foci. First, studies have ly specialized research tested stream,the informed by the literatures Pittaway andand Thorpe, 2012; Ucbasaran 2013). The (learning-based) link between failure performance increase et in al., subsequent on entrepreneurial learning and entrepreneurial failure. substantial body of recent research shows three mainhas foci. entrepreneurial endeavors (Boso et al., 2019; Paik, 2014; Parker, 2013). Second, research As illustrated in Figure 3, the first research on this topFirst, studies have tested the (learning-based) link between attempted to provide a holistic view of the learning process from failure to re-emergence ic emerged at the beginning of the twenty-first (Amankwah-Amoah et al.,century.

2018; Dias and and Teixeira, 2017; Frota Vasconcellos Dias and failure performance increase in subsequent entrepreWhile relevant publications rare until 2010, methodology.

Martens,remained 2019), applying qualitative Third,(Boso scholars, drawing learning neurial endeavors et al., 2019; on Paik, 2014; from Parker, have focused on changes specific behaviors—such as internationalization research interest in thisfailure, field increased considerably in sub- in 2013).

Second, research has attempted to provide a holisal., of 2019), strategic actiontic(Lin et al., 2019) and negotiation of venture capital sequent years. Indeed,(Lafuente more thanethalf all relevant artiview of the learning process from failure to re-emer(Nahata, 2019)—upon re-emergence. cles were published in 2015 or later.

While theentrepreneurial still limited gence (Amankwah-Amoah et al., 2018; Dias and Teixeira, number of studies and the heterogeneity of their research 2017; Frota Vasconcellos Dias and Martens, 2019), applypurposes make it difficult to generalize the emer4.2 Provenance of about the research ing qualitative methodology. Third, scholars, drawing on our selection criteria, all articles were published in peer-reviewed journals. gence of the field, weConsistent attempt towith elaborate some major learning from failure, have focused on changes in specific Most themes that have shaped thepapers field sowere far. found in the Journal of Business Venturing (seven) and Entrepreneurship behaviors—such as internationalization (Lafuente et al., Theory andbyPractice (five), as well Influenced by the call issued McGrath (1999) to as the International Journal of Entrepreneurial Behavior 2019), of strategic action (Lin etisal., 2019) and and Research (four). As far as the country author’s affiliation concerned, thenegotiation United correct the bias in entrepreneurship research toward venture(21) capital entrepreneurial States of America (23) and the United of Kingdom were(Nahata, the most2019)—upon important research spots. success, scholars began shed light level, on failure-related Onto a continental most scholars were affiliated with universities in Europe (43), followed re-emergence. topics. This wave first hit entrepreneurial learning by the North America (25).

The literremaining continents provided lower numbers of relevant ature at the beginningcontributions of the twenty-first century, when 4.2 Provenance (Asia: ten; Australia/Oceania: nine; Africa: four; South America: four). of the research at research collaborations (indicated with by differing affiliations among co-authors), Shepherd (2003) reflectedLooking on the learning process follow- Consistent our selection criteria, all articles were pubonethecan were crafted in international collaborations, with 12 of them ing business failure and roleseeof that grief14 as papers an important lished in peer-reviewed journals. Most papers were found influencing factor [1]. Additional studies of the learning in the Journal of Business Venturing (seven) and Entrepreprocess were published two years later, when Politis (2005) neurship Theory and Practice (five), as well as the Interand Rerup (2005), both aiming for a general understand- national Journal of Entrepreneurial Behavior and Research ing of entrepreneurial learning from experience, specifi- (four). As far as the country of author’s affiliation is concally elaborated on failure as an important type of expe- cerned, the United States of America (23) and the United rience. From 2007 onward, empirical studies on a wide Kingdom (21) were the most important research spots. On range of relevant topics, such as re-engagement (Stam et al., a continental level, most scholars were affiliated with uni2008), experience transformation (Huovinen and Tihula, versities in Europe (43), followed by North America (25).

Volume 52, Issue 3 • 59

Entrepreneurial Learning From Failure. A Systematic Review

The remaining continents provided lower numbers of relevant contributions (Asia: ten; Australia/Oceania: nine; Africa: four; South America: four).

Looking at research collaborations (indicated by differing affiliations among co-authors), one can see that 14 papers were crafted in international collaborations, with 12 of them originating from two or more continents. In all 12 intercontinental collaborations, at least one scholar had an affiliation in the United States. While earlier papers emerged primarily through collaborations between the United States and Europe, more recent collaborations have included researchers from Africa and Asia. In general, a rising trend toward cooperation is visible, as about twothirds of all collaborative publications stem from the last four years.

4.3 Methods Research on entrepreneurial learning from failure utilizes conceptual, qualitative and quantitative approaches.

Among the 40 studies in our sample, eight apply a purely conceptual lens, 14 use qualitative methods, 16 quantitative methods and two a mixed-method approach. A temporal perspective reveals that early research predominantly applied conceptual lenses to create a basic understanding of the phenomenon of learning from failure (Politis, 2005; Rerup, 2005; Shepherd, 2003). Recent research, by contrast, is often of an empirical nature, utilizing qualitative and quantitative approaches with nearly similar frequency.

Qualitative studies use samples of one (Huovinen and Tihula, 2008; Pretorius and le Roux, 2011) to (initially) 30 (Walsh and Cunningham, 2017) “failed” entrepreneurs.

Thirteen of the 14 qualitative studies build on in-depth interviews. In some cases (e.g. Byrne and Shepherd, 2015), the data basis is expanded by observation and written documents. To approach the challenge of biases stemming from the processual nature of learning, studies either utilize narrative interview techniques that help participants to recall relevant information (e.g. Corner et al., 2017) or include informal follow-up conversations (Singh et al., 2015). Quantitative studies are based on samples of between 142 (He et al., 2018) and 41,259 (Nielsen and Sarasvathy, 2016) entrepreneurs. Several works compare the performance of initial and subsequent entrepreneurial attempts on the basis of income- or profit-related data (see, e.g. Chen, 2013; Parker, 2013). Additional descriptive statistics on the research methods are presented in Table 1. For an overview of sample sizes by methodology, see Appendix Table A2.

4.4 Key contributions Existing research on entrepreneurial learning from failure predominantly addresses three issues. One group of papers explores the question of whether learning from failure, as such, exists and to what extent it positively influences future venture endeavors. This area of inquiry is informed 60 • Mensa Research Journal

mainly by a conceptual paper by Coad (2014) and a number of quantitative studies dedicated to testing the failure– learning and/or failure–future performance relationship (Boso et al., 2019; Espinoza-Benavides and D’ıaz, 2019; Mueller and Shepherd, 2016; Paik, 2014; Parker, 2013).

While Coad (2014) in his conceptual work is critical about the effects of failure-induced learning, empirical findings predominantly suggest that, under certain circumstances, learning from failure is possible. A second group of articles focuses on factors that are assumed to influence learning (for an overview see Wei et al., 2019). Among those factors, emotion (Byrne and Shepherd, 2015; Corner et al., 2017; Shepherd, 2003; Shepherd et al., 2009) and failure attribution (Cardon et al., 2011; Eggers and Song, 2015; Mantere et al., 2013; Ucbasaran et al., 2011; Walsh and Cunningham, 2017; Yamakawa and Cardon, 2015; Yamakawa et al., 2015) are most frequently studied. Further factors of interest are mindfulness (Rerup, 2005), attitude toward failure (Politis and Gabrielsson, 2009), comparative optimism (Ucbasaran et al., 2010), stigma (Singh et al., 2015), pre-education (Nielsen and Sarasvathy, 2016), failure velocity (He et al., 2018) and narcissism (Liu et al., 2019). A third group of papers takes a broader view by exploring the learning process or parts thereof. Areas of inquiry include the transformation of experience into knowledge (Huovinen and Tihula, 2008); failure perception, reflection and the resulting learning outcomes (Cope, 2011; Dias and Teixeira, 2017; Frota Vasconcellos Dias and Martens, 2019; Heinze, 2013; Pittaway and Thorpe, 2012; Pretorius and Le Roux, 2011; Singh et al., 2007; Ucbasaran et al., 2013) and learning-based behavioral changes upon entrepreneurial re-emergence (Amankwah-Amoah et al., 2018; Lafuente et al., 2019; Lin et al., 2019; Nahata, 2019).

As visible, the contributions of 37 of 40 research studies can be linked to one of the three issues mentioned above.

The remaining papers make a very heterogeneous range of contributions, such as clarifying definitional issues (Jenkins and McKelvie, 2016) or proposing conceptual learning frameworks (Politis, 2005) as well as theories of re-emergence (Stam et al., 2008).

A comprehensive list of publications, including their key contributions and other relevant information, is provided in Table 1.

4.5 Learning process In this section, we present the state of research on entrepreneurial learning from failure from an experiential learning perspective, structuring our findings according to the experiential learning process developed by Kolb (1984).

4.5.1 Concrete experience. The failure of an entrepreneurial endeavor is in many cases a highly critical event influencing both the business and the personal life of an entrepreneur (Coad, 2014; Cope and Watts, 2000; Dias and Teixeira, 2017; Huovinen and Tihula, 2008; Shep-

Table 1.

Literature for review

2015

Byrne and Shepherd

2014

2019

Boso

Coad

2018

Conceptual

Empirical (qualitative)

Empirical (quantitative)

Empirical (qualitative)

UK

UK, US

GH, US, UK, GH

UK, UK, UK

International Small Business Journal

Entrepreneurship Theory and Practice

Journal of Business Research

Group and Organization Management

Journal

Interviews with 13 entrepreneurs who failed [Country: United Kingdom]

240 entrepreneurs who reemerged after business failure

22 entrepreneurs who failed (phase 1); 15 entrepreneurs from phase 1, who subsequently reengaged in entrepreneurship (phase 2) [Country: Ghana]

Sample

1

1

2

2

[2] Reflective observation

3

[3] Abstract conceptualization

4

4

4

[4] Active experimentation

(continued )

The authors develop an evolutionary phase model to explain how prior business failure experience influences successive newly started businesses. Applying a multiple case analysis, they discover four sub-processes: grief and despair (1), transition (2), formation (3) and legacy (4). While the first two stages are associated with reflecting and learning, the subsequent stages involve processes of imprinting entrepreneurial knowledge on successive ventures Business failure experience only influences subsequent venture performance if it is channeled through entrepreneurial learning.

A model is created and successfully tested that links business failure to new venture performance. Thereby, learning is found to play a mediating role. The influence of learning on new venture performance is moderated by the entrepreneur’s alertness The authors examine the relationship between emotion and perceived learning. In fact, they ask entrepreneurs for their emotional state upon and after business failure. Most perceived learning is reported by those who initially felt negative emotions changing to positive emotional status after the failure. This implies that negative emotions act as trigger for sensemaking, whereas positive emotions are important for broadening and building knowledge Critical evaluation of the tendency to see business failure–based on the assumption of being a valuable opportunity for learning–as something positive. The author reminds of the lack of large-scale empirical evidence supporting the positive effect of failure on learning

Key contributions

IJEBR 26,5

AmankwahAmoah et al.

Country

[1] Concrete experience

1102

Authors

Research Year method

Entrepreneurial Learning From Failure. A Systematic Review

Volume 52, Issue 3 • 61

62 • Mensa Research Journal

2017

2017

2015

Corner et al.

Dias and Teixeira

Eggers and Song

Empirical (quantitative)

Empirical (qualitative)

Empirical (qualitative)

US, CN

PT, PT

NZ, NZ, NZ

UK

2011

Cope

Empirical (qualitative)

Country

Authors

Research Year method

Academy of Management Journal

European Journal of Management and Business Economics

International Small Business Journal: Researching Entrepreneurship

Journal of Business Venturing

Journal

253 serial entrepreneurs [Country: China (Beijing)]

6 failed entrepreneurs, 3 from the north of Europe, 3 from the south [Country: Various in Europe]

11 failed entrepreneurs [Country: New Zealand]

8 failed entrepreneurs [Country: United Kingdom and United States]

Sample

1

1

[1] Concrete experience

2

2

2

2

[2] Reflective observation 3

[3] Abstract conceptualization

4

4

[4] Active experimentation

(continued )

Cope argues that learning from failure is a process highly related with emotional feelings. After an initial hiatus, the entrepreneur typically enters a stage of deep, critical reflection which may lead to future reflective action (thus re-engagement in entrepreneurial activities). Outcomes of this reflective process may be various learning contents: They comprise learning about oneself, about one’s venture, about networks and about venture management Applying a qualitative research approach, the authors find that the majority of entrepreneurs within their sample show emotional resilience after their failure. This insight challenges the common assumption that entrepreneurs have to pass through a process of recovery after failure in order to learn and successfully re-emerge This qualitative study on business failure investigates – on the basis of the conceptualization of Ucbasaran et al. (2013) – the aftermath of failure events. Thereby, one aspect examined was learning. The results are in line with the theoretical reasoning of Ucbasaran et al. (2013) Eggers and Song find that learning from failure is difficult due to erroneous attributions: Entrepreneurs attribute the reasons for their failure primarily to external factors. Therefore, they change these factors (namely: the sector) when opening their subsequent business while retaining other internal aspects (management etc.).

Therefore, sector-specific knowledge cannot be transferred properly leading to poorer performance

Key contributions

Entrepreneurial Learning From Failure. A Systematic Review

Entreprene learning fa

1

Ta

1.

2019

2019

2018

2013

2008

Frota Vasconcellos Dias and Martens

He et al.

Heinze

Huovinen and Tihula

Empirical (qualitative)

Empirical (qualitative)

Empirical (quantitative)

Empirical (qualitative)

Empirical (quantitative)

FI, FI

UK

CH, CH, US, CH

BR, BR

CL, CL

International Journal of Entrepreneurial Behavior and Research

Small Enterprise Research

Entrepreneurship Theory and Practice

Brazilian Journal of Management

International Journal of Entrepreneurial Behavior and Research

Journal

1 portfolio entrepreneur [Country: Finland]

6 failed entrepreneurs [Country: United Kingdom]

142 entrepreneurs in the IT industry [Countries: Finland and United States]

3 failed entrepreneurs [Country: Brazil]

2,024 entrepreneurs of whom 233 previously experienced a business failure [Country: Chile]

Sample

1

1

1

1

2

2

2

2

[2] Reflective observation

3

3

3

[3] Abstract conceptualization

4

4

4

[4] Active experimentation

(continued )

The study compares personal characteristics of entrepreneurs who reengage after a prior entrepreneurial failure with characteristics of first-time entrepreneurs. Among other differences, the authors find that “failed” entrepreneurs possess significantly superior skills and knowledge, which are attributed to learning The study analyzes the entrepreneurial learning of three micro and small-size company founders, who – following failure – re-engaged in entrepreneurial activity.

Findings demonstrate that reflection following the failure event leads to learning that has the potential to positively influence subsequent venture emergence and performance The authors develop and test a model that links failure velocity and learning behaviors.

They find an inverted U-shaped relationship between failure velocity and learning behaviors. Further, they investigate emotion regulation to moderate this relationship The study explores the sensemaking of six entrepreneurs who experienced business failure. Particular attention is paid to the influence of the entrepreneurs’ social environment. Findings reveal that social interactions triggered strong emotions that interfere with learning. Further, evidence on learning and emotions is provided that supports the work of Cope (2011) and Shepherd (2003) Examining the experiences of a portfolio entrepreneur, the authors test and confirm the conceptual framework of Politis (2005) empirically

Key contributions

R

EspinozaBenavides and D ıaz

Country

[1] Concrete experience

4

Authors

Research Year method

Entrepreneurial Learning From Failure. A Systematic Review

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64 • Mensa Research Journal

2016

2019

2019

2019

Jenkins and McKelvie

Lafuente et al.

Lin et al.

Liu et al.

Authors

Empirical (quantitative)

Empirical (quantitative)

Empirical (mixed)

Conceptual

Research Year method

CN, US, CN, CN

CN, US, CN

ES, FR, UK, PT

SE, US

Country

Journal of Business Venturing

International Entrepreneurship and Management Journal

Applied Psychology

International Small Business Journal

Journal

180 failed entrepreneurs [Country: China]

253 serial entrepreneurs, of which 144 had a failure experience

380 serial entrepreneurs of which 31% had reemerged after failure [Country: Spain]

Sample 1

[1] Concrete experience

2

[2] Reflective observation

3

[3] Abstract conceptualization

4

4

[4] Active experimentation

(continued )

The authors discuss and map existing conceptualizations of failure. The emerging framework distinguishes between objective and subjective as well as individual-level and firm-level failures. Based on this structure, the various conceptualizations, their origins in literature and potential future application fields are discussed and links to learning provided The study finds that serial entrepreneurs show significantly improved cognitive capacity and increased levels of international orientation compared to their novice counterparts. These differences apply to cases of prior failure and prior success both. However, previously failed entrepreneurs were found—despite reporting rich learning—to be less likely to re-engage in entrepreneurship The study links learning from failure with changes in strategic behavior upon entrepreneurial re-emergence. Applying a perspective of strategic incrementalism, the authors provide evidence that previously failed entrepreneurs, who engage intensively in learning, exhibit in their new venturing episodes more proactive strategic actions The authors find that narcissism has a negative impact on learning from failure.

This particularly applies in cases when the costs of failure (especially: social costs) are high

Key contributions

Entrepreneurial Learning From Failure. A Systematic Review

Entr lea

2013

2016

2019

Authors

Mantere et al.

Mueller and Shepherd

Nahata

Empirical (quantitative)

Empirical (mixed)

Empirical (qualitative)

Research Year method

US

US, US

FI, FI, FI

Country

Journal of Corporate Finance

Entrepreneurship Theory and Practice

Journal of Business Venturing

Journal

1,262 VC-backed IPOs; in 357 cases, at least one founder is a serial entrepreneur; 83 of these serial entrepreneurs “failed” in their prior endeavor [Country: United States]

114 entrepreneurs; mainly high-tech industry [Country: United States]

18 interviews with stakeholders of 3 failed companies

Sample

1

1

[1] Concrete experience 2

[2] Reflective observation

3

3

[3] Abstract conceptualization

4

[4] Active experimentation

(continued )

The study finds attribution differences of entrepreneurial failure between entrepreneurs, hired executives, employees and the media. Further, a fine-grained set of possible attributions is provided, forming a continuum between internal and external attribution The authors find that failure is linked to a specific type of thinking–structural alignment. Structural alignment involves cognitive processes of comparison between items or ideas that results in useful implications. It thus can foster learning– especially (as discussed in the current study) about better opportunity recognition. While the main effect between failure experience and the use of structural alignment processes was not significant, this study found that when coupled with the proper cognitive tools (expert opportunity prototypes, cognitive style), failure experience can be beneficial in the long run, helping to equip individuals for success in subsequent ventures (at least in the identification of opportunities) The study reveals that on the strength of their entrepreneurial learning, serial entrepreneurs negotiate more favorable venture capital deal terms than their novice counterparts. Specifically, they achieve greater board control, suffer less dilution of equity, are more likely to retain their CEO positions, and receive higher valuations from venture capitalists. This pattern applies to previously “failed” entrepreneurs as well as to successful ones

Key contributions

Entrepreneurial Learning From Failure. A Systematic Review

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Paik

Nielsen and Sarasvathy

Authors

66 • Mensa Research Journal

2009

2011

Politis and Gabrielsson

Pretorius and le Roux

Empirical (qualitative)

Empirical (quantitative)

ZA, ZA

International Journal of Entrepreneurial Behavior and Research SA Journal of Human Resource Management

Entrepreneurship Theory and Practice

231 entrepreneurs who reengaged in entrepreneurial activities [Country: Sweden] 1 single case study [Country: South Africa]

Sample

707 entrepreneurs of whom 226 experienced two or more times of selfemployment [Country: United States]

172 firms in semiconductor industry [Country: United States]

1,418 restarters and 39,841 one-time entrepreneurs [Country: Denmark]

Sample

1

2

2

2

2

[2] Reflective observation

1

[1] Concrete experience

1

1

[2] Reflective observation

3

[3] Abstract conceptualization

3

[3] Abstract conceptualization

4

[4] Active experimentation

4

4

4

[4] Active experimentation

Entrepreneurial learning from failure

1107

Table 1.

(continued )

Politis conceptualizes learning as a process (continued ) that transforms various kinds of entrepreneurial career experience (start-up/ management/industry related) into entrepreneurial knowledge. This knowledge can either lead to improved opportunity recognition or superior coping capacity with the liabilities of newness. The extent to which each form of knowledge is created is influenced by the manner of transformation.

This can either be via exploitation, meaning that the entrepreneur acts according to his/ her existing knowledge or exploration, a process of going new paths. The actual manner of transformation is influenced by the outcomes of previous events, predominant logic or reasoning and the entrepreneur’s career orientation The study finds that critical experiences in terms of founding and closing businesses positively impact the attitude toward business failure The study explores the case of an entrepreneur, who experienced repeated failures (in total six) over a time span of 20 years. The obvious lack of learning is attributed to the fact that the entrepreneur never had entered a stage of reflection.

Instead, following business failure he immediately re-emerged in another entrepreneurial endeavor

Nielsen and Sarasvathy argue that entrepreneurial learning is possible, but it does not happen automatically. It requires, in particular, a stock of knowledge – in order to allow highly educated entrepreneurs to learn from exit. On the other side, entrepreneurs who see business failure per se as a rich source for learning, might fail due to overconfidence bias According to Paik, serial entrepreneurs perform – regardless of their prior venture experience being a success or failure – better than novice entrepreneurs Based on an investigation of performance trajectories of serial entrepreneurs the authors find that learning does exist.

However, according to human capital theory, this positive influence depreciates over time, limiting the possibility of “cumulative learning” Review and evaluation of the contribution to entrepreneurial learning by Jason Cope.

Divided into three sub-chapters the paper illustrates Cope’s research summarizing it Key contributions into a conceptual framework

Key contributions

1108

SE, SE

SE

Journal

Entrepreneurship and Regional Development

Journal of Business Venturing

Strategic Entrepreneurship Journal

Academy of Management Discoveries

Journal

[1] Concrete experience

IJEBR 26,5

Conceptual

2005

Authors

Politis

US, UK

Country

Conceptual

CA

US

DK, US

Country

Research Year method

2012

Pittaway and Thorpe

Empirical (quantitative)

Empirical (quantitative)

2014

2013

Table 1.

Parker

Empirical (quantitative)

2016

Research Year method

Entrepreneurial Learning From Failure. A Systematic Review

2003

2009

2015

Shepherd

Shepherd et al.

Singh et al.

Empirical (qualitative)

Conceptual

Conceptual

NZ, NZ, NZ

US, SE, US

US

CA

2005

Rerup

Conceptual

Country

Authors

Research Year method

Journal of Business Venturing

Journal of Business Venturing

Academy of Management Review

Scandinavian Journal of Management

Journal

12 failed entrepreneurs [Country: New Zealand]

Sample

1

1

[1] Concrete experience

2

2

2

[2] Reflective observation [3] Abstract conceptualization

4

4

[4] Active experimentation

(continued )

Rerup focuses on the transformation of learning to a useful factor of success for a new venture. Drawing on mindfulness, he explains that in situations with high similarity between two ventures and low level of change, extended levels of (costly) mindfulness might be suboptimal. Thus, mindfulness is an important factor, however not only positive and thus shall be used in situations of dynamic, ill-structured, ambiguous and unpredictable entrepreneurial circumstances Business failure typically leads to personrelated levels of grief. Grief is a negative emotion that can distract the entrepreneur from objective reflection of the business failure. Thus, Shepherd suggests to oscillate between focusing on healing from the negative emotion (restoration orientation) and focusing on the failure and its causes (loss orientation) as the best path toward learning The authors discuss the phenomenon of delaying business failure. This behavior typically leads to high financial costs and thus harms recovery. Yet, under some circumstances, delaying a failure may help to balance financial and emotional costs. As a result, the overall recovery and subsequent entrepreneurial action can be promoted The study explores the role of stigma for learning from failure. Stigma ends when the failed entrepreneur experiences a so-called epiphany, a moment of insight. From this moment he or she sees failure as something positive and is ready to make use of learning outcomes–either in form of entrepreneurial re-engagement or alternative applications (e.g. consultancy)

Key contributions

Entrepreneurial Learning From Failure. A Systematic Review

Entrepreneu learning f fai

Volume 52, Issue 3 • 67

11

Tab

2007

2008

2013

2011

2010

2017

Authors

Singh et al.

Stam et al.

Ucbasaran et al.

68 • Mensa Research Journal

Ucbasaran et al.

Ucbasaran et al.

Walsh and Cunningham

Empirical (qualitative)

Empirical (quantitative)

Empirical (quantitative)

Conceptual

Empirical (quantitative)

Empirical (qualitative)

Research Year method

ES, UK

UK, UK, UK, UK

UK, UK, UK

UK, US, UK, UK

NL, DE, US

NZ, NZ, NZ

Country

International Journal of Entrepreneurial Behavior and Research

Journal of Business Venturing

Harvard Business Review

Journal of Management

Journal of Evolutionary Economics

Journal of Management and Organization

Journal

3

2

30 entrepreneurs from ICT industry, who reentered in entrepreneurship after failure [Country: Ireland]

2

2

3

[3] Abstract conceptualization

3

1

[2] Reflective observation

576 entrepreneurs (278 novice and 298 repeat entrepreneurs) [Country: United Kingdom]

576 serial-/portfolio entrepreneurs [Country: United Kingdom]

240 entrepreneurs who closed their business [Country: The Netherlands]

5 ex-entrepreneurs who experienced failure [Country: New Zealand]

Sample

[1] Concrete experience

4

4

[4] Active experimentation

(continued )

According to this qualitative study, business failures lead to economic, social, psychological and physiological learning outcomes The authors argue that one visible outcome of learning is the fact that even in case of failure people re-engage in entrepreneurial activity. If they did not believe in learning– from the perspective of the homo oeconomicus–there would be no reason to restart Ucbasaran et al. (2013) argue that failure triggers sensemaking, a process consisting of interrelated stages of scanning, interpretation and learning. This process is influenced by attributions and emotions.

The outcome may be a change in behavior Serial entrepreneurs are found not to reflect on failures and thus do not learn from one attempt to the next. The reasons are overconfidence and wrong attributions. In fact, serial entrepreneurs (different to portfolio entrepreneurs) — potentially as a coping mechanism–attribute the causes of failures to external factors Ucbasaran et al. (2010) argue that overoptimism is a specific trait of entrepreneurs and at the same time an important antecedent to failure. While portfolio entrepreneurs–through experience–become more realistic (decreasing the tendency of being over-optimistic), this is not true for serial entrepreneurs The study finds that the attribution of business failure influences the entrepreneur’s response and subsequently the learning focus

Key contributions

Entrepreneurial Learning From Failure. A Systematic Review

2019

2015

2015

Authors

Wei et al.

Yamakawa and Cardon

Yamakawa et al.

Empirical (quantitative)

Empirical (quantitative)

Conceptual followed an empirical illustration (qualitative)

Research Year method

US, US, US

US, US

CN, CN, CN, CN

Country

Entrepreneurship Theory and Practice

Small Business Economics

Frontiers in Psychology

Journal

203 entrepreneurs who experienced business failure [Country: Japan]

220 entrepreneurs who previously failed and reentered into selfemployment [Country: Japan]

1 single case study [Country: China]

Sample 1

[1] Concrete experience

2

2

2

[2] Reflective observation [3] Abstract conceptualization

4

4

[4] Active experimentation

Based on a literature analysis, 24 factors influencing entrepreneurial learning from failure are detected. These factors are grouped in a hierarchical order. The emerging system is subsequently empirically evaluated by one single case study Yamakawa and Cardon find that failure ascriptions (how the core causal characteristics of a failure are identified) influence perceived learning from failure. In fact, internal unstable failure ascriptions lead to higher perceived learning, whereas external stable ascriptions deteriorate learning potential. Further, in the case of internal unstable ascriptions, a short time between failure and restart positively influences perceived learning. In the case of external ascriptions, domain abandonment further lowers perceived learning from failure in the new venture Failure does not automatically lead to learning and thus superior venture performance in the future. According to this study, to promote learning, internal attribution of failure is necessary. However, excessively high levels of internal attributions may lead to a sense of shame and guilt preventing the entrepreneur from re-engaging in entrepreneurial activities.

Further, the extent of failure experiences may have an inverted U-relationship with learning: in general, failure is seen to be a valuable basis for learning to take place but at a certain level, factors like negative emotions may limit learning

Key contributions

Entrepreneurial Learning From Failure. A Systematic Review

Entrepreneuri learning fro failu

111

Table

Volume 52, Issue 3 • 69

Entrepreneurial Learning From Failure. A Systematic Review

herd, 2003; Singh et al., 2007). Spheres of impact include financial, emotional, physiological, social, professional and entrepreneurial domains (Cope, 2011; Heinze, 2013; Pittaway and Thorpe, 2012). The actual level of impact depends on the nature of the failure event (e.g. bankruptcy, closure due to sustained losses) and a range of subjective factors determined primarily by the entrepreneur’s personality. Indeed, perceptions of failure may vary widely. Shepherd (2003) even sees links between entrepreneurial failure and the loss of a loved person, given the strong bonds between ventures and their owners (Frota Vasconcellos Dias and Martens, 2019; Shepherd, 2003). In contrast, Dias and Teixeira (2017) find that in some cases failure may be experienced as a relief after the stress of the process of descending into failure.

A large number of studies stress the pivotal role of failure as a trigger for learning (e.g. Amankwah-Amoah et al., 2018; Cope, 2011; Eggers and Song, 2015; He et al., 2018; Singh et al., 2007). Drawing on the work of Fiol and Lyles (1985), Cope (2003) states that “shocks, jolts, and crises are necessary for unlearning, new higher-level learning and readaptation to take place.” In a later study of eight “failed” entrepreneurs, Cope (2011) illustrates how failure can trigger higher-level learning, resulting in a variety of outcomes (e.g. learning about oneself and about entrepreneurship—for details see stage 3). Yet, as Shepherd (2003) mentions, learning from failure is neither automatic nor instantaneous. It requires specific learning behaviors that occur during subsequent stages of the experiential learning process.

4.5.2 Reflective observation. An entrepreneur who perceives a failure as critical may enter a stage of reflective observation on what has happened. Reflective observation is—in the entrepreneurial context—well captured by the notion of sensemaking articulated in Ucbasaran et al.

(2013). Ucbasaran et al. (2013) conceptualize sensemaking as a complex process aimed at giving meaning to occurrences. From a temporal perspective, sensemaking consists of the sub-stages scanning and reflecting. Scanning entails paying selective attention to information regarding the failure (Ucbasaran et al., 2013). Reflecting can be seen as a stage of information processing and attaching meaning to the insights achieved. Pittaway and Thorpe (2012), interpreting Cope’s lifetime contribution to the field of entrepreneurial learning, portray reflection as a process of four interrelated activities: looking backward, reminiscing about the experience; looking forward to further possible actions; looking outward to the environment; and looking inward to oneself.

The importance of reflective observation for experiential learning is illustrated empirically by Pretorius and Le Roux (2011). The authors investigate a 20-year-long entrepreneurial career that consisted of five consecutive business failures. The analysis reveals that the entrepreneur never

70 • Mensa Research Journal

reflected on these failures but instead directly re-engaged in the next entrepreneurial endeavor. The study finds no evidence of learning behaviors or learning outcomes and thus sees this lack of learning as a main cause for the persistent failing.

The process of reflective observation is influenced by a variety of interrelated cognitive and emotional factors (Schwandt, 2005; Ucbasaran et al., 2013). The literature discusses the role of the individual stock of knowledge, the trait of narcissism, the attribution of the failure to particular causes and the individual emotional patterns for this learning stage.

Stock of knowledge. The nature of experiential learning as experience-based updating of previous knowledge (Kolb, 1984) is visible in the entrepreneurial context. Minniti and Bygrave (2001) equate learning to updating a subjective stock of knowledge. Politis (2005), empirically supported

by Huovinen and Tihula (2008), views learning as a transformation of experience into knowledge and also considers the role of pre-existing knowledge for interpretation and reflection. This insight is supported by Mueller and Shepherd (2016), who highlight that the benefits that result from an experience of failure depend on prior knowledge.

Specifically, they argue that more experienced entrepreneurs possess more enhanced opportunity prototypes. An opportunity prototype is “a cognitive representation of the ideal business opportunity,” which influences the transformation of the experience of failure into knowledge about the process of opportunity identification. In addition, as Politis and Gabrielsson (2009) find, prior start-up and business closure experience may influence an entrepreneur’s attitude toward failure, which in turn impacts the reflective observation process.

Narcissism. In their recent quantitative study, Liu et al.

(2019) show that narcissism has a strong influence on an entrepreneur’s ability and motivation to engage in reflective observation. Narcissism entails an exaggeratedly positive self-view that the individual wishes to maintain. Entrepreneurs with highly narcissistic tendencies might show limited openness to external feedback and apply only selective information scanning mechanisms. Hence, the information they gather about their failures might be limited, both in amount and validity. This phenomenon applies particularly in cases of high social costs. Given the strong need narcissists have to maintain their reputations, they will apply coping mechanisms that limit critical reflection on causes of failure.

Attribution of failure to specific causes. The extent and flow of reflection are significantly influenced by the identification of reasons for the failure (Eggers and Song, 2015; Walsh and Cunningham, 2017; Yamakawa et al., 2015).

Mantere et al. (2013) illustrate seven types of failure narratives, of which four were found to be predominantly used

Entrepreneurial Learning From Failure. A Systematic Review

by entrepreneurs. These narratives include the acceptance of personal responsibility (“catharsis”), the attribution of irrational behavior to collective hubris in the venture (“hubris”), the “downfall of the entrepreneurial hero” due to externals (e.g. investors) (“nemesis”) and unexpected market developments (“fate”). Despite this variety of attributions of failure, research mainly builds on simpler conceptualizations.

Yamakawa and Cardon (2015) distinguish internal, unstable attribution from external, stable attribution. The former refers to a cognitive pattern of blaming oneself for the failure. The entrepreneur finds the cause of failure to be a shortcoming in his or her skills, management expertise or financial planning. Internal attribution enables so-called counterfactual thinking, a type of reflection that enhances the understanding of cause–effect relationships. As a consequence, rich learning can be expected, changing the previously erroneous mindset and rendering the failure cause unstable. In another study, Yamakawa et al. (2015) confirm the potential positive impact of internally attributed failures on reflection. However, they highlight that the extent of prior failure experiences influences this relationship. For entrepreneurs who have suffered a high number of failure experiences, internal attribution can limit the ability to reflect. If the entrepreneur, on the other hand, ascribes the failure to external, stable causes, negative emotions (e.g. feelings of shame or grief ) can be mitigated (Yamakawa et al., 2015). This, however, implies that he or she perceives failure as a result of unfavorable external conditions like strong competition and environmental uncertainty, limiting the signaling effect of failure and thereby limiting reflection. A group that appears prone to external failure attribution are serial entrepreneurs (Ucbasaran et al., 2011). Despite repeated failure, serial entrepreneurs have been found to adhere to external failure attribution, impeding their learning progress. Walsh and Cunningham (2017) link failure attribution to specific learning outcomes. They explore three different types of failure ascriptions: internal, external and hybrid. Internal failure ascription triggers affective responses leading to person-related learning outcomes—that is, “learning about oneself ” (Cope, 2005, 2011). Entrepreneurs who attribute failure to external causes show behavioral changes with regard to venture and network/relationship dimensions. Hybrid approaches combining internal and external ascription lead to cognitive responses with regard to venture management.

Emotional sphere. Failure, as an exceptionally critical event, strongly impacts the entrepreneur’s emotional sphere (Dias and Teixeira, 2017; Shepherd, 2003; Shepherd et al., 2009). Failure-induced emotions are manifold and can include grief, regret, disappointment, frustration, pain, remorse, shame, anger, guilt, blame, depression and the development of phobias (Byrne and Shepherd, 2015; Singh et al., 2007, 2015; Ucbasaran et al., 2013). Byrne

and Shepherd (2015), drawing on the work of others, highlight that failure may also facilitate positive emotions (e.g. feelings of pride, confidence and enthusiasm). The concrete emotional impact of a failure depends on various factors, such as the entrepreneur’s experience, age, perception of blame and degree of resilience (Corner et al., 2017; Shepherd, 2003; Ucbasaran et al., 2013). Further, as Frota Vasconcellos Dias and Martens (2019) stress, emotions related to failure can also be considerably influenced or even triggered by the entrepreneur’s social environment (friends, spouse, parents and other family members). The emergence of emotions is a process, and emotions often emerge only at a certain temporal distance from the failure event itself (Heinze, 2013).

Despite the commonly shared awareness of emotional diversity, existing research focuses mainly on one specific form of emotion: grief. This stream was established by Shepherd (2003), who applied psychological insights to the entrepreneurial context. Shepherd argues that grief, as a negative emotional response to failure, may interfere with the entrepreneur’s allocation of attention to the causes of failure. Overcoming grief as an obstacle to learning requires efforts in two directions. On the one hand, in the close aftermath of failure, the entrepreneur might feel the need to distract himself or herself from thinking about the loss (“restoration orientation”). Cope (2011) refers to this as an “initial hiatus,” a process of stepping back in order to heal emotionally. On the other hand, Shepherd (2003) and Cope (2011) similarly note that from a certain point, active engagement with the failure becomes essential for recovering and learning (“loss orientation”). In addition, Shepherd (2003) argues that founding a new company might also accelerate recovery from failure. However, this manner of coping involves the danger of repeating mistakes due to insufficient learning (Shepherd, 2003; Pretorius and Le Roux, 2011). Instead, “oscillation” between restoration and loss orientation is seen as the ideal path toward recovery and subsequent learning. Reduced grief after stages of restoration orientation may enable the entrepreneur to focus for a time and to a certain extent on the loss before embarking on a further phase of restoration. This dual process continues until the entrepreneur has recovered. The exact time span of an individual’s process of recovery from grief varies.

Amankwah-Amoah et al. (2018), drawing on a sample of 15 re-emerged entrepreneurs, report on periods of between one and two years.

Byrne and Shepherd (2015) offer another perspective on the underlying process. The authors asked “failed” entrepreneurs for their overall emotional feeling at the time of failure and after some time had passed. Linking the responses to the respective learning progress, they find that strong negative emotions at the beginning followed by strong positive emotions are the most effective constellation for learning. In this way, the negative emotions trigger deep reflec-

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Entrepreneurial Learning From Failure. A Systematic Review

tion. The process of reflection (probably via oscillation) enables the entrepreneur to reduce grief and to concentrate on the causes of failure. Yet, as Corner et al. (2017) argue, not every case requires intensive efforts toward recovery. Indeed, their qualitative investigation of the emotional processes of 11 “failed” entrepreneurs revealed that the majority showed resilience, and thus stable levels of functioning, after a severe event. Consequently, there may exist other emotional pathways following a failure that have yet to be explored.

One potential path is described in the work of Singh et al. (2015). In a qualitative study, they found evidence that entrepreneurs felt tainted with stigma—a negative emotion that emerged even prior to the failure and inhibited subsequent reflection. Yet at some point, study participants experienced a so-called “epiphany”. This epiphany, defined as a sudden, deep insight into how the entrepreneur himself or herself had contributed to the failure, changed the prior negative emotional state into a positive one and enabled reflective observation.

While there are obviously different views on how emotions should be regulated, studies concur about the pivotal role this process plays in learning (AmankwahAmoah et al., 2018; Cope, 2011; Shepherd, 2003; Singh et al., 2007; Wei et al., 2019). In cases of multiple failures, He et al. (2018) find that the rate at which failure events are experienced (“failure velocity”) influences learning. Failure may, on the one hand, trigger sensemaking while on the other hand generating strong emotions that hinder learning. Consequently, the relationship between failure velocity and learning behaviors follows an inverted U-shape.

4.5.3 Abstract conceptualization. In the stage of abstract conceptualization, the entrepreneur further develops his or her conclusions about the failure experience.

Specifically, the insights from the previous stage of reflective observation are linked to existing knowledge to form sound theories (Kolb, 1984). This results in a variety of abstract learning outcomes that are not situation-specific but rather applicable in a range of contexts (entrepreneurship, consulting, mentoring, etc.; Cope, 2011). With regard to the content of the learning, research has found evidence for learning within the personal, social, venture and entrepreneurial spheres (Cope, 2011; Frota Vasconcellos Dias and Martens, 2019; Mueller and Shepherd, 2016; Singh et al., 2007). These findings represent perceived learning outcomes, predominantly derived from in-depth interviews with failed entrepreneurs (Cope, 2011; Frota Vasconcellos Dias and Martens, 2019; Singh et al., 2007).

The personal sphere comprises insights about one’s own strengths, weaknesses, skills, attitudes, beliefs and areas for development as well as interests and motivations. Cope’s (2011) findings are complemented by a number of further exploratory studies (e.g. Frota Vasconcellos Dias and

72 • Mensa Research Journal

Martens, 2019; Heinze, 2013). Specific examples of learning have included the consciousness of personal strengths (Cope, 2011), the need to follow one’s passion (Heinze, 2013) and the awareness of increased resilience (Frota Vasconcellos Dias and Martens, 2019). Conceptually, Cope (2011) links person-related outcomes to the concept of “transformative learning” (Mezirow, 1991). Transformative learning is a higher-order form of learning with a distinctly personal dimension, able to induce profound changes in “the self ” of the entrepreneur (Cope, 2003, 2011; Mezirow, 1991). Walsh and Cunningham (2017) find that this learning outcome appears also in situations of extended grief.

However, it depends upon identifying the cause of failure primarily in oneself (Walsh and Cunningham, 2017).

This may also reflect reality in many cases, as the failure as a catalyst for transformative learning often is self-imposed (Pittaway and Thorpe, 2012). A sustainable, critical focus on areas for personal (and business) development may lead to what Lindh and Thorgren (2016) call a “continuous reflective ability” and a “better self-view” (Ucbasaran et al., 2010) in the long run.

Learning about social relationships refers to improved insights into the nature and management of social networks inside and outside the venture (Cope, 2011; Frota Vasconcellos Dias and Martens, 2019). The range of network partners is wide, including, for example, the entrepreneurial team, employees, customers, suppliers, competitors, advisory agencies and support services. Better understanding of and ability to handle social ties may enhance the ability to spot and seize entrepreneurial opportunities (Politis, 2005).

Venture-related learning outcomes relate to an enhanced understanding with reference to the (former) enterprise’s strengths, weaknesses, opportunities and threats (Cope, 2005, 2011; Espinoza-Benavides and DÍaz, 2019; Frota Vasconcellos Dias and Martens, 2019). Moreover, entrepreneurs may gain a clearer picture of internal business needs, requirements for growth and future strategic directions (Cope, 2005; Lafuente et al., 2019; Lin et al., 2019). These outcomes result from “double-loop learning”, a means of higher-level learning enabling a renewed understanding or redefinition of organizational processes and strategies (Cope, 2011).

Learning about entrepreneurial activities refers to entrepreneurial tasks in a narrower sense (recognizing opportunities, coping with the liabilities of newness) as well as to more general venture management activities. The formers are discussed in a conceptual work by Politis (2005), who sees improvements in opportunity recognition and liability handling as primary outcomes of entrepreneurial learning. This conceptualization of entrepreneurial learning has been applied empirically by Huovinen and Tihula (2008). Mueller and Shepherd (2016) find further evidence that learning from failure may lead to improved abilities of opportunity identification. This, however, requires the use

Entrepreneurial Learning From Failure. A Systematic Review

of proper cognitive tools, such as a certain style of sensemaking (Mueller and Shepherd, 2016). Among general venture management activities, better capabilities in negotiating with venture capitalists (Nahata, 2019) and acting effectively under pressure and tension are thematized (Frota Vasconcellos Dias and Martens, 2019). Conceptually, learning about venture management can be linked to Gibb’s (1997) concept of “generative learning,” implying that the entrepreneur may become more proactive in future venturing decisions (Cope, 2011).

4.5.4 Active experimentation. Previously failed entrepreneurs may choose among a variety of ways to actively experiment with their newly acquired learning outcomes.

Indeed, research stresses that, besides further entrepreneurial activity, there are other options, like consulting and networking, through which a “failed” entrepreneur can utilize and test his or her knowledge base (Cope, 2011; Singh et al., 2015). However, empirical studies are mostly concerned with entrepreneurial re-engagement (e.g.

Amankwah-Amoah et al., 2018; Boso et al., 2019; Espinoza-Benavides and DÍaz, 2019; Nielsen and Sarasvathy, 2016; Yamakawa and Cardon, 2015; Yamakawa et al., 2015). Specifically, they attempt to understand why certain individuals (and not others) decide to actively experiment via re-engagement (e.g. Nielsen and Sarasvathy, 2016; Stam et al., 2008) as well as to determine how and when this application of knowledge is executed (e.g. AmankwahAmoah et al., 2018; Huovinen and Tihula, 2008; Rerup, 2005). Moreover, research focuses on specific behavioral changes upon re-emergence, including modified strategic actions (Lin et al., 2019), negotiation behavior with venture capitalists (Nahata, 2019) and internationalization (Lafuente et al., 2019). Further, scholars attempt to measure the degree of success that is derived from learning (e.g. Paik, 2014; Yamakawa et al., 2015).

The question of why “failed” entrepreneurs decide to enter the stage of active experimentation via entrepreneurial re-emergence has attracted considerable research interest (Nielsen and Sarasvathy, 2016; Stam et al., 2008; Ucbasaran et al., 2010, 2013). Stam et al. (2008) stress learning as the primary reason for restarting entrepreneurship when a previous attempt has failed. While assumed learning may not in itself be enough, in many cases, to prompt an entrepreneur to decide to re-emerge (Lafuente et al., 2019), learning, taken in conjunction with overconfidence and a lack of other employment opportunities, has been found to drive most re-engagement decisions (Nielsen and Sarasvathy, 2016; Ucbasaran et al., 2010, 2013). In addition, Amankwah-Amoah et al. (2018) highlight the role of family as a supporting factor. Eggers and Song (2015) as well as Yamakawa et al. (2015) see a connection between the primary direction of failure ascription and motivation for a restart. They argue that external failure ascription might lead to a higher probability of re-engagement.

In the opposite case (internal failure ascription), entrepreneurs might see themselves as not being talented enough and therefore refrain from re-engagement. This insight may be linked to the finding of Singh et al. (2015) that the feeling of stigma needs to be overcome prior to entering the experimentation stage.

Recognizing that the mindful application of prior experience is essential for successful future venture performance (Rerup, 2005), research analyzes patterns of re-engagement behaviors. In particular, the question of when and how active experimentation takes place has been of interest. Dias and Teixeira (2017) stress that failure appears to have a significant impact on how entrepreneurs design their re-emergence. Specifically, “failed” serial entrepreneurs tend to change industries when opening another business (Eggers and Song, 2015). This decision can be traced back to external failure attribution, which may lead entrepreneurs to change the context but retain the same management style. As a result, lessons learned may be unfavorably applied, leading to poor firm performance (Eggers and Song, 2015; Pretorius and Le Roux, 2011). Other studies find that, on the strength of their learning, entrepreneurs show a stronger tendency toward internationalization (Lafuente et al., 2019) and more proactive strategic behavior upon re-emergence (Lin et al., 2019).

The question of whether, and under what circumstances, learning from failure can lead to successful entrepreneurial re-emergence has generated considerable research interest (Boso et al., 2019; Eggers and Song, 2015; Huovinen and Tihula, 2008; Liu et al., 2019; Paik, 2014; Parker, 2013; Yamakawa and Cardon, 2015; Yamakawa et al., 2015). Apart from Huovinen and Tihula (2008), who illustrate through a single case study how learning affects the process of forming an entrepreneurial team, all the other studies cited above apply quantitative methods.

Success is measured either by venture performance indicators (growth: Eggers and Song, 2015 as well as Yamakawa et al., 2015; profits: Parker, 2013; survival: Paik, 2014; subjective performance: Boso et al., 2019) or perceived learning (Liu et al., 2019; Yamakawa and Cardon, 2015).

Empirical evidence predominantly suggests that failures can indeed lead to learning-based improvements upon entrepreneurial re-emergence (e.g. Boso et al., 2019; Paik, 2014; Parker, 2013; Yamakawa and Cardon, 2015). However, this mechanism is subject to a number of conditions and limitations. For example, Yamakawa and Cardon (2015) find more perceived learning in cases of internal failure ascription. Parker (2013) discovers a depreciation effect of learning benefits over time. Eggers and Song (2015) are critical about the learning of serial entrepreneurs, who are frequently seen to blame external factors for their failures and to change industries upon re-emergence. To sum up, large-scale empirical data support the view that learning from failure is possible but at the same time highlights

Volume 52, Issue 3 • 73

( (

(

entrepreneurial learning from failure

Open issues (overlooked aspects, contradictions)

(

a t 1

(3) (4)

(3)

(2) (2)

Entrepreneur’s immediate reaction to failure Systematic analysis of factors influencing criticality perception

(1)

Detected but unresearched alternative emotional trajectories (e.g. resilience, ignorance) Epiphanies as alternative emotional recovery mechanism Social context as influence factor on emotions Cognitive process of reflective observation (as opposed to abstract conceptualization)

(1) (2) (3)

(1) Open issues (overlooked aspects, contradictions)

Process of reflection Stock of experience Attribution Emotions Narcissism (1) (2) (3) (4) (5) Conceptualization of failure Perception of criticality Importance of failure as a learning trigger (1)

25

# of sample studies contributing to learning stage Central themes in existing research on entrepreneurial learning from failure

(2)

Abstract conceptualization as a creative process Link between abstract learning outcomes and antecedents is only researched with regard to failure attribution Abstract learning outcomes represent “perceived” learnings

Abstract learning outcomes

21

The application of abstract learning outcomes to test them

The creative process of forming observations to abstract learning outcomes 13 The experience and the actor’s immediate reaction to the experience 19 Key issues according to Kolb

The actor’s deeper reflection on what has happened

4. Active experimentation 3. Abstract conceptualization

(1) Decision on entrepreneurial re-emergence (2) Determinants of effective use of learning (3) Behavioral changes upon re-emergence (4) Venture performance in Kolb’s learning stages new endeavor(s) (1) Other ways of active Key issues according to experimentation (e.g.

Kolb consulting, mentoring, employment) # of sample studies (2) Importance of specific contributing to learning abstract learning categoriesstage for specific settings of Central themes in active experimentation existing research on

1

74 • Mensa Research Journal

2. Reflective observation

This review aims to take stock of research on entrepreneurial learning from failure and to identify promising avenues for future research. Existing knowledge, which appears to be 1118 fragmented, is mapped in the light of experiential learning theory. Utilizing Kolb’s (1984) experiential learning model, we assign and structure the literature according to four stages of learning (see Table 2) that range from the initial experience of business failure to the eventual application of lessons learned in, for example, a new entrepreneurial episode.

This theory-guided approach allows scholars to systematically detect overlooked questions and contradictions within existing research.

According to Kolb (1984), the first learning stage starts with the “concrete experience.” In the context of this study, this stage comprises the business failure and the entrepreneur’s immediate reaction to this event. Regarding failure itself, existing knowledge is rather comprehensive and concerns conceptual issues (Jenkins and McKelvie, 2016) as well as the criticality of such events and the potential they create for learning (Cope, 2011). Previous research shows substantial individual differences in perceptions of failure (Dias and Teixeira, 2017; Frota Vasconcellos Dias and Martens, 2019).

Nevertheless, there is broad agreement that it is not the event itself that determines how critical a business failure is but rather how it is perceived subjectively and the individual attitude taken to the failure (Cope, 2011; Ucbasaran et al., 2013). Mainly drawing on its criticality, research appears convinced of the Table 2. learningOverview potential of that the failure bears current state of et al., 2018; (e.g. Amankwah-Amoah research Cope, 2011; Eggers and Song, 2015;

1. Concrete experience

5. Discussion IJEBR and future26,5 research

Table 2.

Overview of the current state of research

Kolb’s learning stages

several factors that were already familiar from conceptual and qualitative studies.

(1)

Entrepreneurial Learning From Failure. A Systematic Review

Entrepreneurial Learning From Failure. A Systematic Review

He et al., 2018; Singh et al., 2007). Regarding the entrepreneur’s immediate reaction to failure, however, knowledge is limited.

Based on these findings, two important avenues for future research emerge. First, investigating the entrepreneur’s immediate reaction (cognitive, emotional, activityoriented) to business failure appears relevant, as different reactions can lead to different coping strategies and processes of emotional recovery (Byrne and Shepherd, 2015).

Contrasting the immediate reaction and the later process of reflection may enable researchers to detect trajectories that have an explanatory character for subsequent learning outcomes. A study of these trajectories should preferably apply a longitudinal research design. Second, research is needed to better understand the determinants that shape the perception of the criticality of business failure. As a starting point, the papers by Lindh and Thorgren (2016) and Morris et al. (2012) may elucidate critical event recognition in the entrepreneurial context. Morris et al. (2012, p.

19), for instance, suggest that the significance of an event is “a function of an event’s novelty, expectedness, and consistency with the individual’s assumptions and knowledge base.” Further research linking the entrepreneur’s identity and biography with the recognition of business failure could prove illuminating in this regard.

The second stage in Kolb’s learning process, “reflective observation,” features the deliberate and detailed sensemaking of the experience. With 25 studies in our sample exploring aspects of this stage, the stage of reflective observation is the one that has attracted the most scholarly attention so far. Studies frequently utilize “reflection” as an umbrella term that covers reflective observation and abstract conceptualization. In most studies, knowledge of reflection has emerged as a side product, as research endeavors are mainly concerned with particular factors (such as emotions or attribution) influencing reflective observation (Eggers and Song, 2015; Huovinen and Tihula, 2008; Liu et al., 2019; Shepherd, 2003). A prominent part of such studies is dedicated to the role of emotions in the process of recovery from failure. Mostly, they are concerned with the recovery from grief (Cope, 2011; Shepherd, 2003). Singh et al.

(2015) offer an alternative path to emotional recovery that builds on the abolition of stigma. In addition, a number of scholars provide evidence for alternative reactions such as emotional resilience or immediate re-engagement in a new entrepreneurship episode (Corner et al., 2017; Pretorius and Le Roux, 2011). To a limited extent, these studies also provide links to other influencing factors and later learning outcomes (e.g. Walsh and Cunningham, 2017).

Our analysis reveals at least four avenues for future research on reflective observation. The first one concerns alternative trajectories of the influence of emotional factors.

Corner et al. (2017) found patterns of resilience that lead to a different emotional impact and development pattern.

An explanatory, longitudinal study that examines the individual’s emotional status and its impact on willingness and ability to reflect could unveil the existence of a variety of different trajectories for how emotions and reflection interact over time. Another related phenomenon to be analyzed is the pattern of immediate entrepreneurial re-emergence without reflective observation (as shown by Pretorius and Le Roux, 2011). Specifically, it appears interesting that a lack of emotional impact or a deliberate decision to overcome negative emotional feelings might drive the immediate entrepreneurial re-emergence. Second, the concept of a process of critical reflection that requires oscillation between managing negative emotions and reflecting on the failure (Cope, 2011) appears to conflict with the concept of epiphanies (Singh et al., 2015). A qualitative study could compare these mechanisms, considering the spheres of emotion, reflection and learning. Third, we encourage future researchers to heed the call issued in several studies (e.g. Cope, 2011; Jenkins and McKelvie, 2016; Liu et al., 2019) to examine the role of the social environment (e.g. the family) on reflective observation. This should include the influence on the perception of failure and the emotional response of the entrepreneur. Fourth, the field would benefit from a better understanding of the cognitive process that constitutes reflective observation in a narrower sense. Apart from certain influencing mechanisms (e.g. emotions), reflection still remains a “black box,” which limits our understanding of entrepreneurial learning. The research design of such a study could be geared to those of comparable prior endeavors (Cope, 2003, 2011; Shepherd, 2003; Shepherd et al., 2009).

“Abstract conceptualization”, the third stage in the entrepreneurial learning process, entails the transformation of insights on the specific experience into sound abstract learning outcomes. In the context of entrepreneurial learning from failure, this stage is clearly under-researched. In particular, the question of how failed entrepreneurs transform their observation of an experience into abstract learning is largely unanswered. Existing research on reflection (Cope, 2011; Pittaway and Thorpe, 2012) and sensemaking (Ucbasaran et al., 2013) from failure may provide some insights. However, this research fails to elaborate on the differences between the more reflective process of building a perception of an experience and the creative process of transforming this perception into abstract knowledge (Kolb, 1984). Pertaining to the resulting abstract knowledge—that is, the specific content of the learning—a number of qualitative studies found evidence for learning within the personal, social, venture and entrepreneurial spheres (Cope, 2011; Frota Vasconcellos Dias and Martens, 2019; Mueller and Shepherd, 2016; Singh et al., 2007). However, these findings consider perceived learning outcomes. As we know from the literature of learning in educational contexts, perceived and actual learning can

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vary dramatically (Bacon, 2016). This difficulty likely also applies in the context of entrepreneurial failure, given the potential for biases stemming from failure attribution, stigmatization, emotional coping and optimism. As Nielsen and Sarasvathy (2016) argue, failure can lead to overconfidence, with the founder erroneously believing the failure was a valuable learning experience. Consequently, the entrepreneur may encounter repeated failures due to inaccurate perceptions of his or her own learning (Pretorius and Le Roux, 2011). Other factors that have to be kept in mind when interpreting reported learning outcomes are the elapsed time between failure and data collection as well as any eventual entrepreneurial re-emergence. Existing research builds on rather heterogeneous cases: for example, in the study by Heinze (2013), interviews were conducted between six months and nine years after the failure event; in the study by Cope (2011), one of eight studied entrepreneurs had re-emerged at the time of the interview.

To advance our knowledge on this learning stage, we especially encourage future researchers to shed light on the creative process of transforming experience-based insights into logical, sound concepts. So far, little is known about how abstract learning outcomes emerge, which is an important cornerstone for fully understanding entrepreneurial learning (Kolb, 1984). As far as the influencing factors are concerned, some aspects that play an influential role in the second stage (e.g. stock of knowledge, narcissism) may also be relevant for abstract conceptualization. Given the creative dimension of this process (Kolb, 1984), additional influencing factors (e.g. capacity for abstract thinking, creativity) may play key roles. Furthermore, research might follow the example of Walsh and Cunningham (2017) and try to identify links between particular influencing factors and subsequent learning outcome dimensions. With respect to the potential deviations between perceived and actual learning, we do not see a clear direction toward a reliable and valid method of capturing of actual learning outcomes. However, we encourage future researchers to pay closer attention to the credibility of learning outcomes by not only presenting learning contents but also investigating whether the reasoning leading to these contents appears credible. One example of this procedure can be found in Nielsen and Sarasvathy (2016, p. 262), who critically evaluate a statement by a failed entrepreneur and question whether he had “learned the right lesson.”

The fourth stage of Kolb’s learning process is “active experimentation”—that is, the application of learning outcomes in practice. Research on entrepreneurial learning from failure (e.g. Cope, 2011) recognizes that there are several possible work settings apart from entrepreneurship in which to apply and test abstract learning. However, empirical studies exclusively target the case of entrepreneurial re-emergence (i.e. starting a new entrepreneurial episode). This stream of research flows into four direc-

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tions. First, scholars are concerned with the question of whether and under what conditions “failed” entrepreneurs decide to re-emerge. Presumed learning effects (Stam et al., 2008), overconfidence (Nielsen and Sarasvathy, 2016; Ucbasaran et al., 2010, 2013), family support (Amankwah-Amoah et al., 2018) and failure ascription (Eggers and Song, 2015; Yamakawa et al., 2015) are identified as factors that influence this decision. Second, the process of transferring abstract knowledge to practical settings is of interest—in particular, the degree of mindfulness in knowledge transfer (Rerup, 2005) and the choice of industry and time for re-emergence (Eggers and Song, 2015; Parker, 2013). Third is a very recent research stream focusing on specific behavioral changes upon re-emergence, such as an increased tendency toward internationalization (Lafuente et al., 2019), proactive strategic actions (Lin et al., 2019) and improved negotiating with venture capitalists (Nahata, 2019). While studies within this stream focus predominantly on the outcome (behavioral changes) and less on the learning process leading to this outcome, they reveal the potential of seeking a more detailed view of how learning influences future behavior. Fourth, scholars attempt to evaluate whether and under what circumstances the application of learning is successful. Findings predominantly support the view that failure can lead to learning and successful entrepreneurial re-emergence. However, there are at least two limitations to be highlighted. One is that studies unanimously stress that this learning mechanism is subject to a number of conditional factors. Another is that learning success is measured via either self-reporting or venture performance indicators (e.g. growth, profit, survival). Hence, as discussed above, self-reported learning builds on learning perceptions that may deviate from actual learning. Taking venture performance indicators as proxies for learning risks neglecting explanatory factors for venture success (e.g. social networks).

Future research is required to broaden the field of inquiry to encompass alternative processes of active experimentation. These could include employment as opposed to entrepreneurship as well as mentoring and consulting activities.

With regard to concrete research aims, existing work on entrepreneurial re-emergence may act as a map offering orientation (i.e. reasons for re-emergence, transfer process, evaluation of learning). In addition, we advocate a finegrained analysis on the level of learning categories. Not every learning category (e.g. person-related, entrepreneurship-related) or concrete outcome (e.g. awareness of susceptibility to stress; knowledge of the start-up process) may be relevant in every experimentation setting. Recognizing the links between specific learning categories and success in active experimentation may improve our understanding of the kinds of learning that are important for different kinds of re-emergence. Finally, we encourage scholars to follow the example of Lafuente et al. (2019), Lin et al. (2019) and

Entrepreneurial Learning From Failure. A Systematic Review

Nahata (2019) and provide more fine-grained research on edge. In this regard, we advocate for a better adaption of concrete learning-induced behavioral changes. To further methodological approaches to the longitudinal character increase the contribution made by such studies, it might of learning from failure. This issue has frequently been be valuable to qualitatively explore the entire (learning) raised in existing research (Cope, 2011; He et al., 2018; process leading to the modified behavior.

Ucbasaran et al., 2010; Yamakawa and Cardon, 2015). It The identified areas for future research contain a number is particularly pertinent to qualitative studies, which are of interesting questions, which are summarized in Table 3. prone to recall biases due to single interviews targeting an This overview of research questions also includes referenc- entire venturing, failing and learning process (Podsakoff es to studies that support a certain research inquiry and/or and Organ, 1986). Future research should—at a minimum — utilize quasi-narrative interview designs to take give detailed methodological suggestions.

The identified areas for future research contain a number of interesting questions, which IJEBR advantage of narration-based recall advances (Flick, 2018).

Our discussion has revealed a numberinof fruitful areasoverview are summarized Table 3.

This of research questions also includes references to However, for studies covering longer periods (e.g. for26,5 further research. They constitute large, under-explored studies that support a certain research inquiry and/or give detailed methodological the fields (e.g. the process ofsuggestions. abstract conceptualization; alter- whole process of learning from failure), a design with two or three data collection points preferable (Holland et al., Our discussion revealed of fruitful areas for isfurther research.

They native ways of applying learning outcomeshas to new prac- a number constitute large, under-explored fields (e.g. the process of abstract conceptualization; 2006; McLeod, 2003). tical settings) and rather intensively studied aspects (e.g. alternative ways applying learningTooutcomes new practical settings) and rather sum up, to research in its present state offers consideremotional As aofconsequence, 1122 recovery, stigmatization). intensively studied aspects (e.g. emotional recovery, stigmatization). As a consequence, able knowledge of how entrepreneurs learn from qualitative, exploratory qualitative, research designs as well as quantiexploratory research designs as well as quantitative ones will be necessaryfailure. in tative ones will be necessary in order to advance our knowl- However, our analysis has also unveiled a number of blind Research questions Stage 1: Concrete experience How do entrepreneurs initially react when they face business failure (cognitively, emotionally, activityoriented)? Are these immediate reactions different from later coping and emotional recovery processes?

Which patterns of trajectories exist between initial and later reactions? How do these trajectories influence abstract learning outcomes?

- see also: Corner et al. (2017) Which factors do influence the perceived criticality of a business failure? How does failure perception differ in diverse geographic and/or cultural contexts?

Stage 2: Reflective observation Which alternative trajectories to emotional recovery from failure do exist? Which forms do they take? How do they influence the reflective observation of the failure? What determines which trajectory is pursued?

- see also: Corner et al. (2017) What are the reasons for skipping the stage of reflective observation via an immediate entrepreneurial reemergence? Is this pattern a deliberate coping mechanism or the result of a lack of emotional impact?

- see also: Pretorius and Le Roux (2011) How do Cope’s (2011) critical reflection and Singh et al.’s (2015) concept of epiphanies relate to each other?

What are the differences regarding abstract learning outcomes?

- see also: Singh et al. (2015) What role does the entrepreneur’s social environment (e.g. family, friends) play in the stage of reflective observation? Specifically, how does the social environment influences cognitive and emotional processes?

• see also: Cope (2011); Jenkins and McKelvie (2016); Liu et al. (2019) What cognitive processes constitute the process of reflective observation on business failure in a narrower sense?

- see also: Kolb (1984); Walsh and Cunningham (2017) Stage 3: Abstract conceptualization How do entrepreneurs transform their failure-based observations into logically sound theories (abstract conceptualization)? What influences this process?

- see also: Kolb (1984) What distinguishes reflective observation and abstract conceptualization when learning from a business failure?

• see also: Kolb (1984) How are specific influence factors on abstract conceptualization linked to subsequent learning outcomes?

How do abstract learning outcomes, which result from individual perceptions, relate to actual learning?

• see also: Nielsen and Sarasvathy (2016, p. 262), who critically evaluate the reliability of a (reported) perceived learning outcome Stage 4: Active experimentation What determines which setting of active experimentation (e.g. entrepreneurship, employment) is chosen by a previously failed entrepreneur?

- see also: Singh et al. (2015); Walsh and Cunningham (2017) How are abstract learning outcomes transferred to subsequent activities? Which factors do influence this process?

Table 3.

Research questions for Which abstract learning outcomes are perceived as particularly important/unimportant in specific settings of active experimentation? (e.g. start-up-knowledge may be more relevant for entrepreneurial re-emergence future research than for employed work) endeavors

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spots in the research, measurement problems and partly contradictory findings. In general, one may conclude that the earlier stages of the learning process (the failing and the reflective observation on what has happened) have received more attention and study than the later stages (abstract conceptualization and subsequent application of learning outcomes). As a consequence, future research on the earlier stages will build pre-knowledge but will still need to target blind spots and inconsistencies. A fuller understanding of the later stages of the learning process demands broad, exploratory endeavors that particularly target the process of abstract conceptualization and application of knowledge. In sum, one may conclude that learning from failure provides a range of areas for future research. We therefore encourage future researchers to maintain the recent interest in this field, as it yields open questions that are both interesting for research and relevant for practice.

6. Practical implications

This review yields important implications for entrepreneurs and policy makers. Entrepreneurs should accept failure as an inherently entrepreneurial phenomenon (AmankwahAmoah et al., 2018; Cope, 2011; Li et al., 2019). While failure is a critical event that can cause a range of negative effects (e.g. financial, psychological and physiological problems; Byrne and Shepherd, 2015; Shepherd et al., 2009), it also represents an opportunity for learning (Boso et al., 2019; Cope, 2011; Dias and Teixeira, 2017; Espinoza-Benavides and DÍaz, 2019; Li et al., 2019). This learning enables growth in individual knowledge that can play a significant role in the success of subsequent (entrepreneurial or other) endeavors (Amankwah-Amoah, 2018; Boso et al., 2019; Paik, 2014; Parker, 2013). Consequently, entrepreneurs should see failure neither as the ultimate end of their entrepreneurial careers (Boso et al., 2019) nor as a proof of being unsuited to entrepreneurship (Lafuente et al., 2019). However, our findings also support the notion that learning from failure does not happen automatically (Shepherd, 2003). Entrepreneurs must consciously manage their negative emotions and engage in critical reflection (Cope, 2011; Shepherd, 2003; Ucbasaran et al., 2013). This implies, also, that they should not unreflectively blame the external environment or bad luck as primary causes of failure but rather mindfully transfer learning outcomes to new endeavors (Yamakawa et al., 2015).

Policy makers may be stimulated by our findings on their role in facilitating the use and transfer of the knowledge that results from failure-based learning. In a narrow sense, policy should support the transfer of knowledge between successive entrepreneurial episodes. Our implications for the individual (i.e. that learning is possible and that failure is no sign of inadequacy for entrepreneurship) suggest that policy makers should strive to support the re-emergence of previously failed entrepreneurs as they support first-time entrepreneurs (Lafuente et al., 2019). This requires them

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to combat the existing social stigma attached to failure, as it could prevent entrepreneurial re-emergence (Singh et al., 2015). Moreover, policy makers should facilitate the development of institutions and initiatives that support failed entrepreneurs in their re-engagement (Boso et al., 2019), such as specialized accelerator programs. In a wider sense, policy makers should ensure that lessons learned from failure are spread across the entrepreneurial community and the society (Cope, 2011). For example, other entrepreneurs could learn from the failures of their peers in self-help groups. Additionally, those failed entrepreneurs who do not wish to re-emerge should nevertheless be given opportunities to distribute their insights. Such opportunities could be organized in the course of public events that focus on how and what to learn from failure. Finally, failure and the lessons learned from it should become an integral part of entrepreneurship education (González-López et al., 2019). In this way, aspiring entrepreneurs can profit from what others have learned by failing and at the same time gain a realistic picture of failure as a relevant entrepreneurial phenomenon.

7. Limitations

As a matter of course, our literature review is subject to some limitations. Applying a systematic review methodology acts as a double-edged sword (Wang and Chugh, 2014). On the one hand, a systematic review approach offers a replicable, scientific and transparent agenda for the collection and analysis of data (Tranfield et al., 2003).

On the other hand, it introduces potential limitations that stem from the rigid conceptualization and execution of the research (Pittaway et al., 2004; Wang and Chugh, 2014).

In selecting the literature to be included, our search focused on peer-reviewed academic journals. In the light of quality standards, the restriction to literature from particular sources is a common practice, generally recommended for literature reviews (Bouncken et al., 2015; Wang and Chugh, 2014). However, one must be aware that knowledge disseminated via other outlets (e.g. unpublished papers and books) may be missed. As we include only articles written in English, another limitation is that the insights of researchers who publish in other languages are excluded. In terms of content, our deliberately narrow and clean definition of “failure” results in a relatively focused area of inquiry, which goes hand in hand with a rather small number of articles in the sample. Looking at other state-of-the-art literature reviews that focus on young topics and follow highly systematic review procedures (e.g. Kraus et al., 2018; Pret and Cogan, 2019), we observe comparable sample sizes. Referring to the definitional demarcation, we are aware that there exist related research areas that might hold potential for a systematic review—for instance, entrepreneurial learning from successful exit and intrapreneurial learning from project failure. For the present endeav-

Entrepreneurial Learning From Failure. A Systematic Review

or, we decided against extending the scope of research to include these related fields for two reasons. First, despite their relevance, positive entrepreneurial exit and project failure represent significantly different contexts (e.g. Wennberg and DeTienne, 2014 for the former and Shepherd and Kuratko, 2009 for the latter). Second, an adequate elaboration of the contextual differences would far exceed the scope of a review paper. However, we are convinced that these related topics represent fruitful areas for future research. The present paper, with its systematic, theoryinformed review approach, may act as a guide for these future research endeavors. Moreover, it might be interesting, subsequently, to compare findings from different learning contexts.

Pertaining to the analysis and systematization of the data, we are aware of potential biases stemming from subjectivity (Bouncken et al., 2015). To target this shortcoming, two researchers analyzed the data separately and discussed any differences of perception. Regarding the systematization and presentation of the literature, we find our theory-based approach, which utilizes Kolb’s experiential learning stages to map existing research, to be adequate and beneficial. In this approach, we apply a well-reputed framework grounded in experiential learning theory (Politis, 2005). While experiential learning theory is the most influential theoretical framework in the field of entrepreneurial learning (Fust et al., 2018), we are aware that there are other theoretical lenses that could be applied (see Wang and Chugh, 2014 for an overview). Alternatively, it would be possible for a review to utilize a purely processual perspective (see, e.g. Morris et al., 2012) or to map existing research into streams/interest groups (see, e.g. Nogueira, 2019).

8. Conclusion

In this systematic literature review, we identify and critically evaluate the literature on entrepreneurial learning from failure. Existing research is mapped in the light of experiential learning theory. Specifically, we classify literature according to the four stages of Kolb’s model of experiential learning. In this way, we provide a systematic, dynamic overview of the process of entrepreneurial learning from failure. Further, by comparing the scope of knowledge suggested by the theory with the actual knowledge available in the existing literature, we are able to detect a number of fruitful avenues for future research. Our findings reveal that the despite the infancy of the field, research already provides valuable insights regarding wide parts of the process of learning from failure. This pertains to the nature of failure and its triggering effect for learning. Moreover, a deep discussion is underway on specific factors influencing the entrepreneur’s reflection on what had happened, focusing especially on the role of emotions such as grief and shame as well as the role of attribution of failure. Further, the contents of the learning that results from failure (whether of a personal, a social, an entrepreneurial or a

managerial nature) and the transfer of learned content to subsequent entrepreneurial episodes receive a fair amount of attention.

Important areas that still require significant research efforts include Kolb’s stages of “reflective observation” and “abstract conceptualization.” With respect to the former, the role of personal attributes and behaviors such as resilience, but also ignorance and narcissism, as well as the cognitive processes underlying reflection itself still remain under-researched. With respect to the latter, the creative process of abstract conceptualization, or how entrepreneurs transform their failure-based observations into logically sound concepts, has not yet been covered. Investigating the influence of cognitive and social factors could help to better understand this process. While “active experimentation” in new entrepreneurial ventures is already widely addressed, a broader view that includes other fields of application, such as consulting and employed work, remains neglected. A more general issue that seems still unresolved pertains to the measurement of learning. In fact, learning is often self-reported and subjectively measured. While we suggest some solutions to overcome this issue, at least partly (e.g. the integration of credibility checks on how particular learnings are derived), the question of whether entrepreneurs actually learn or merely think they do still requires researchers’ attention. To conclude, entrepreneurial learning from failure represents a flourishing research field that still yields a number of promising research questions. We encourage other scholars to use this article as a roadmap to examine these potentially fruitful issues.

Note 1.

We are aware of earlier works, such as the conceptual article on learning from failure by Sitkin (1992) and the qualitative study on critical incidents for learning

by Cope and Watts (2000). However, these articles lack the scope of the present review, as the former is contextualized within organizational learning and the latter has no explicit focus on business failure.

References

Articles of the literature review sample are marked with an asterisk (*) *Amankwah-Amoah, J., Boso, N. and Antwi-Agyei, I. (2018), “The Effects of Business Failure Experience on Successive Entrepreneurial Engagements: An Evolutionary Phase Model”, Group and Organization Management, Vol. 43 No. 4, pp. 648-682.

Bacon, D.R. (2016), “Reporting actual and perceived student learning in education research”, Journal of Marketing Education, Vol. 38 No. 1, pp. 3-6.

Bird, B., Schjoedt, L. and Baum, J.R. (2012), “Entrepreneurs’ behavior: elucidation and measurement introduction”, Entrepreneurship: Theory and Practice, Vol. 36 No. 5, pp.

889-913.

Volume 52, Issue 3 • 79

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*Boso, N., Adeleye, I., Donbesuur, F. and Gyensare, M. (2019), “Do entrepreneurs always benefit from business failure experience?”, Journal of Business Research, Vol. 98, pp. 370-379.

Bouncken, R.B., Gast, J., Kraus, S. and Bogers, M. (2015), “Coopetition: a systematic review, synthesis, and future research directions”, Review of Managerial Science, Vol. 9 No. 3, pp. 577-601.

Bruno, A.V., Mcquarrie, E.F. and Torgrimson, C.G. (1992), “The evolution of new technology ventures over 20 years: patterns of failure, merger, and survival”, Journal of Business Venturing, Vol. 7 No. 4, pp. 291-302. *Byrne, O. and Shepherd, D.A. (2015), “Different strokes for different folks: entrepreneurial narratives of emotion, cognition, and making sense of business failure”, Entrepreneurship: Theory and Practice, Vol. 39 No. 2, pp. 375-405.

Cardon, M.S., Stevens, C.E. and Potter, D.R. (2011), “Misfortunes or mistakes?: cultural sensemaking of entrepreneurial failure”, Journal of Business Venturing, Vol. 26 No. 1, pp. 79-92.

Chen, J. (2013), “Selection and serial entrepreneurs”, Journal of Economics and Management Strategy, Vol. 22 No. 2, pp.

281-311. *Coad, A. (2014), “Death is not a success: reflections on business exit”, International Small Business Journal, Vol. 32 No. 7, pp. 721-732. *Cope, J. and Watts, G. (2000), “Learning by doing – an exploration of experience, critical incidents and reflection in entrepreneurial learning”, International Journal of Entrepreneurial Behavior and Research, Vol. 6 No. 3, pp. 104-124.

Cope, J. (2003), “Entrepreneurial learning and critical reflection – discontinuous events as triggers for ‘higher-level’ learning”, Management Learning, Vol. 34 No. 4, pp. 429-450.

Cope, J. (2005), “Toward a dynamic learning perspective of entrepreneurship”, Entrepreneurship: Theory and Practice, Vol. 29 No. 4, pp. 373-397. *Cope, J. (2011), “Entrepreneurial learning from failure: an interpretative phenomenological analysis”, Journal of Business Venturing, Vol. 26 No. 6, pp. 604-623. *Corner, P.D., Singh, S. and Pavlovich, K. (2017), “Entrepreneurial resilience and venture failure”, International Small Business Journal-Researching Entrepreneurship, Vol. 35 No. 6, pp. 687-708.

DeTienne, D. and Wennberg, K. (2016), “Studying exit from entrepreneurship: new directions and insights”, International Small Business Journal, Vol. 34 No. 2, pp. 151-156.

Dewey, J. (1910), How We Think, D.C. Heath, New York.

Dewey, J. (1933), How We Think: A Restatement of the Relation of Reflective Thinking to the Educative Process, D.C. Heath, New York. *Dias, A. and Teixeira, A. (2017), “The anatomy of business failure: a qualitative account of its implications for future business success”, European Journal of Management and Business Economics, Vol. 26 No. 1, pp. 2-20.

80 • Mensa Research Journal

Duley, J.S. (1981), “Field experience education”, in Chickering, A.W. (Ed.), The Modern American College, Jossey-Bass, San Francisco. *Eggers, J.P. and Song, L. (2015), “Dealing with failure: serial entrepreneurs and the costs of changing industries between ventures”, Academy of Management Journal, Vol. 58 No. 6, pp. 1785-1803. *Espinoza-Benavides, J. and DÍaz, D. (2019), “The entrepreneurial profile after failure”, International Journal of Entrepreneurial Behavior and Research, Vol. 25 No. 8, pp.

1634-1651.

Fiol, C.M. and Lyles, M.A. (1985), “Organizational learning”, Academy of Management Review, Vol. 10 No. 4, pp.

803-813.

Flick, U. (2018), An Introduction to Qualitative Research, Sage, Los Angeles, London, New Delhi, Singapore, Washington DC, Melbourne.

Fotopoulos, G. and Louri, H. (2000), “Location and survival of new entry”, Small Business Economics, Vol. 14 No. 4, pp.

311-321. *Frota Vasconcellos Dias, T.R. and Martens, C.D.P. (2019), “Business failure and the dimension of entrepreneurial learning: study with entrepreneurs of micro and smallsized enterprises”, Brazilian Journal of Management/Revista de Administração da UFSM, Vol. 12 No. 1, pp. 107-124.

Fust, A.P., Jenert, T. and Winkler, C. (2018), “Experiential or self-regulated learning: a critical reflection of entrepreneurial learning processes”, Entrepreneurship Research Journal, Vol. 8 No. 2, pp. 1-11.

Gibb, A.A. (1997), “Small firms’ training and competitiveness.

Building upon the small business as a learning organisation”, International Small Business Journal, Vol. 15 No. 3, pp. 13-29.

Gimeno, J., Folta, T.B., Cooper, A.C. and Woo, C.Y. (1997), “Survival of the fittest? Entrepreneurial human capital and the persistence of underperforming firms”, Administrative Science Quarterly, Vol. 42 No. 4, pp. 750-783.

González-López, M.J., Pérez-López, M.C. and RodrÍguez-Ariza, L. (2019), “Clearing the hurdles in the entrepreneurial race: the role of resilience in entrepreneurship education”, Academy of Management Learning and Education, Vol. 18 No. 3, pp. 457-483.

Harrison, R.T. and Leitch, C.M. (2005), “Entrepreneurial learning: researching the interface between learning and the entrepreneurial context”, Entrepreneurship: Theory and Practice, Vol. 29 No. 4, pp. 351-371. *He, V.F., Siren, C., Singh, S., Solomon, G. and Von Krogh, G. (2018), “Keep calm and carry on: emotion regulation in entrepreneurs’ learning from failure”, Entrepreneurship: Theory and Practice, Vol. 42 No. 4, pp. 605-630.

Hegel, G.F. (1953), “Philosophy of right and law 1820”, in Friedrich, C. (Ed.), The Philosophy of Hegel, Modern Library, New York.

Entrepreneurial Learning From Failure. A Systematic Review

*Heinze, I. (2013), “Entrepreneur sense-making of business failure”, Small Enterprise Research, Vol. 20 No. 1, pp. 21-39.

Holcomb, T.R., Ireland, R.D., Holmes, R.M. and Hitt, M.A. (2009), “Architecture of entrepreneurial learning: exploring the link among heuristics, knowledge, and action”, Entrepreneurship: Theory and Practice, Vol. 33 No. 1, pp.

167-192.

Holland, J., Thomson, R. and Henderson, S. (2006), “Qualitative longitudinal research: a discussion paper, London South Bank University London. *Huovinen, J. and Tihula, S. (2008), “Entrepreneurial learning in the context of portfolio entrepreneurship”, International Journal of Entrepreneurial Behavior and Research, Vol. 14 No. 3, pp. 152-171. *Jenkins, A. and McKelvie, A. (2016), “What is entrepreneurial failure? Implications for future research”, International Small Business Journal, Vol. 34 No. 2, pp. 176-188.

Josefy, M.A., Harrison, J.S., Sirmon, D.G. and Carnes, C. (2017), “Living and dying. Synthesizing the literature on firm survival and failure across stages of development”, The Academy of Management Annals, Vol. 11 No. 2, pp.

770-799.

Kim, D.H. (1993), “The link between individual and organizational learning”, Sloan Management Review, Fall, Vol. 35, pp. 37-50.

Kolb, D. and Kolb, A.Y. (2018), “Eight important things to know about the experiential learning cycle”, Australian Educational Leader, Vol. 40 No. 3, pp. 8-14.

Kolb, D. (1984), Experiential Learning. Experience as the Source of Learning and Development, Prentice Hall, Englewood Cliffs.

Kraus, S., Palmer, C., Kailer, N., Kallinger, F.L. and Spitzer, J. (2018), “Digital entrepreneurship: a research agenda on new business models for the twenty-first century”, International Journal of Entrepreneurial Behavior and Research, Vol. 25 No. 2, pp. 353-375. *Lafuente, E., Vaillant, Y., Vendrell-Herrero, F. and Gomes, E. (2019), “Bouncing back from failure: entrepreneurial resilience and the internationalisation of subsequent ventures created by serial entrepreneurs”, Applied Psychology, Vol. 68 No. 4, pp. 658-694.

Lewin, K. (1951), Field Theory in Social Sciences, Harper & Row, New York. *Lin, S., Yamakawa, Y. and Li, J. (2019), “Emergent learning and change in strategy: empirical study of Chinese serial entrepreneurs with failure experience”, The International Entrepreneurship and Management Journal, Vol. 15 No. 3, pp. 773-792.

Lindh, I. and Thorgren, S. (2016), “Critical event recognition: an extended view of reflective learning”, Management Learning, Vol. 47 No. 5, pp. 525-542. *Liu, Y., Li, Y., Hao, X. and Zhang, Y. (2019), “Narcissism and learning from entrepreneurial failure”, Journal of Business Venturing, Vol. 34 No. 3, pp. 496-512.

*Mantere, S., Aula, P., Schildt, H. and Vaara, E. (2013), “Narrative attributions of entrepreneurial failure”, Journal of Business Venturing, Vol. 28 No. 4, pp. 459-473.

McGrath, R.G. (1999), “Falling forward: real options reasoning and entrepreneurial failure”, Academy of Management Review, Vol. 24 No. 1, pp. 13-30.

McLeod, J. (2003), “Why we interview now–reflexivity and perspective in a longitudinal study”, International Journal of Social Research Methodology, Vol. 6 No. 3, pp. 201-211.

Mezirow, J. (1991), Transformative Dimensions of Adult Learning, Jossey-Bass, San Francisco.

Minniti, M. and Bygrave, W. (2001), “A dynamic model of entrepreneurial learning”, Entrepreneurship: Theory and Practice, Vol. 25 No. 3, pp. 5-16.

Mitchell, W. and Singh, K. (1993), “Death of the lethargic: effects of expansion into new technical subfields on performance in a firm’s base business”, Organization Science, Vol. 4 No. 2, pp. 152-180.

Morris, M.H., Kuratko, D.F., Schindehutte, M. and Spivack, A.J. (2012), “Framing the entrepreneurial experience”, Entrepreneurship: Theory and Practice, Vol. 36 No. 1, pp. 11-40. *Mueller, B.A. and Shepherd, D.A. (2016), “Making the most of failure experiences: exploring the relationship between business failure and the identification of business opportunities”, Entrepreneurship: Theory and Practice, Vol. 40 No. 3, pp. 457-487.

Nahata, R. (2019), “Success is good but failure is not so bad either: serial entrepreneurs and venture capital contracting”, Journal of Corporate Finance, Vol. 58, pp. 624-649.

Nason, R.S., McKelvie, A. and Lumpkin, G.T. (2015), “The role of organizational size in the heterogeneous nature of corporate entrepreneurship”, Small Business Economics, Vol. 45 No. 2, pp. 279-304. *Nielsen, K. and Sarasvathy, S.D. (2016), “A market for lemons in serial entrepreneurship? Exploring type I and type II errors in the restart decision”, Academy of Management Discoveries, Vol. 2 No. 3, pp. 247-271.

Nogueira, T.F. (2019), “Entrepreneurial learning: what do we mean by it?”, The Learning Organization, Vol. 26 No. 6, pp. 560-573. *Paik, Y. (2014), “Serial entrepreneurs and venture survival: evidence from US venture-capital-financed semiconductor firms”, Strategic Entrepreneurship Journal, Vol. 8 No. 3, pp.

254-268.

Parker, S.C. (2013), “Do serial entrepreneurs run successively better-performing businesses?”, Journal of Business Venturing, Vol. 28 No. 5, pp. 652-666.

Perkins, S.E. (2014), “When does prior experience pay?

Institutional experience and the multinational corporation”, Administrative Science Quarterly, Vol. 59 No. 1, pp.

145-181.

Piaget, J. (1971), Psychology and Epistemology, Penguin Books, Middlesex.

Volume 52, Issue 3 • 81

Entrepreneurial Learning From Failure. A Systematic Review

*Pittaway, L. and Thorpe, R. (2012), “A framework for entrepreneurial learning: a tribute to Jason Cope”, Entrepreneurship and Regional Development, Vol. 24 Nos 9/10, pp. 837-859.

Pittaway, L., Robertson, M., Munir, K., Denyer, D. and Neely, A. (2004), “Networking and innovation: a systematic review of the evidence”, International Journal of Management Reviews, Vols 5-6 Nos 3/4, pp. 137-168.

Podsakoff, P.M. and Organ, D.W. (1986), “Self-reports in organizational research: problems and prospects”, Journal of Management, Vol. 12 No. 4, pp. 531-544. *Politis, D. and Gabrielsson, J. (2009), “Entrepreneurs’ attitudes towards failure: an experiential learning approach”, International Journal of Entrepreneurial Behavior and Research, Vol. 15 No. 4, pp. 364-383. *Politis, D. (2005), “The process of entrepreneurial learning: a conceptual framework”, Entrepreneurship: Theory and Practice, Vol. 29 No. 4, pp. 399-424.

Politis, D. (2008), “Does prior start-up experience matter for entrepreneurs’ learning?”, Journal of Small Business and Enterprise Development, Vol. 15 No. 3, pp. 472-489.

Pret, T. and Cogan, A. (2019), “Artisan entrepreneurship: a systematic literature review and research agenda”, International Journal of Entrepreneurial Behavior and Research, Vol. 25 No. 4, pp. 592-614. *Pretorius, M. and Le Roux, I. (2011), “Successive failure, repeat entrepreneurship and no learning: a case study: original research”, SA Journal of Human Resource Management, Vol. 9 No. 1, pp. 1-13.

Ravasi, D. and Turati, C. (2005), “Exploring entrepreneurial learning: a comparative study of technology development projects”, Journal of Business Venturing, Vol. 20 No. 1, pp.

137-164. *Rerup, C. (2005), “Learning from past experience: footnotes on mindfulness and habitual entrepreneurship”, Scandinavian Journal of Management, Vol. 21 No. 4, pp. 451-472.

Sarasvathy, S.D. (2001), “Causation and effectuation: toward a theoretical shift from economic inevitability to entrepreneurial contingency”, Academy of Management Review, Vol. 26 No. 2, pp. 243-263.

Schwandt, D.R. (2005), “When managers become philosophers: integrating learning with sensemaking”, Academy of Management Learning and Education, Vol. 4 No. 2, pp.

176-192. *Shepherd, D.A. and Kuratko, D.F. (2009), “The death of an innovative project: how grief recovery enhances learning”, Business Horizons, Vol. 52 No. 5, pp. 451-458. *Shepherd, D.A., Wiklund, J. and Haynie, J.M. (2009), “Moving forward: balancing the financial and emotional costs of business failure”, Journal of Business Venturing, Vol. 24 No. 2, pp. 134-148. *Shepherd, D.A. (2003), “Learning from business failure: propositions of grief recovery for the self-employed”, Academy of Management Review, Vol. 28 No. 2, pp. 318-328.

Short, J. (2009), “The art of writing a review article”, Journal of

82 • Mensa Research Journal

Management, Vol. 35 No. 6, pp. 1312-1317. *Singh, S., Corner, P.D. and Pavlovich, K. (2007), “Coping with entrepreneurial failure”, Journal of Management and Organization, Vol. 13 No. 4, pp. 331-344. *Singh, S., Corner, P.D. and Pavlovich, K. (2015), “Failed, not finished: a narrative approach to understanding venture failure stigmatization”, Journal of Business Venturing, Vol. 30 No. 1, pp. 150-166.

Sitkin, S.B. (1992), “Learning through failure – the strategy of small losses”, Research in Organizational Behavior, Vol. 14 No. 1, pp. 231-266. *Stam, E., Audretsch, D. and Meijaard, J. (2008), “Renascent entrepreneurship”, Journal of Evolutionary Economics, Vol. 18 Nos 3-4, pp. 493-507.

Tranfield, D.R., Denyer, D. and Smart, P. (2003), “Towards a methodology for developing evidence-informed management knowledge by means of systematic review”, British Journal of Management, Vol. 14 No. 3, pp. 207-222. *Ucbasaran, D., Westhead, P., Wright, M. and Flores, M. (2010), “The nature of entrepreneurial experience, business failure and comparative optimism”, Journal of Business Venturing, Vol. 25 No. 6, pp. 541-555. *Ucbasaran, D., Westhead, P. and Wright, M. (2011), “Why serial entrepreneurs don’t learn from failure”, Harvard Business Review, Vol. 89 No. 4, p. 26. *Ucbasaran, D., Shepherd, D.A., Lockett, A. and Lyon, S.J. (2013), “Life after business failure: the process and consequences of business failure for entrepreneurs”, Journal of Management, Vol. 39 No. 1, pp. 163-202. *Walsh, G. and Cunningham, J. (2017), “Regenerative failure and attribution: examining the underlying processes affecting entrepreneurial learning”, International Journal of Entrepreneurial Behavior and Research, Vol. 23 No. 4, pp.

688-707.

Wang, C.L. and Chugh, H. (2014), “Entrepreneurial learning: past research and future challenges”, International Journal of Management Reviews, Vol. 16 No. 1, pp. 24-61.

Wdowiak, M.A., Schwarz, E.J. and Parastuty, Z. (2017), “How to teach about entrepreneurial failure? Objectives, assumptions, and evidence”, paper presented at the ECSB Entrepreneurship Education Conference (3E), 10 May-12 May, Cork. *Wei, J., Chen, Y., Zhang, J. and Gong, Y. (2019), “Research on factors affecting the entrepreneurial learning from failure: an interpretive structure model”, Frontiers in Psychology, Vol. 10, Art. 1304, pp. 1-10.

Wennberg, K. and DeTienne, D.R. (2014), “What do we really mean when we talk about ‘exit?’ A critical review of research on entrepreneurial exit”, International Small Business Journal, Vol. 32 No. 1, pp. 4-16.

Wennberg, K., Wiklund, J., DeTienne, D.R. and Cardon, M.S. (2010), “Reconceptualizing entrepreneurial exit: divergent exit routes and their drivers”, Journal of Business Venturing, Vol. 25 No. 4, pp. 361-375.

No. 1, pp. 4-16.

Wennberg, K., Wiklund, J., DeTienne, D.R. and Cardon, M.S. (2010), “Reconceptualizing entrepreneurial exit: divergent exit routes and their drivers”, Journal Entrepreneurial of Business Venturing, Learning From Failure. A Systematic Review Vol. 25 No. 4, pp. 361-375. *Yamakawa, Y. and Cardon, M.S. (2015), “Causal ascriptions and perceived learning from

*Yamakawa, Y. and Cardon, “Causal ascriptions *Yamakawa, Y., Peng, M.W. and Deeds, D.L. (2015), “Rising entrepreneurial failure”,M.S. Small(2015), Business Economics, Vol. 44 No. 4, pp. 797-820. and perceived learning from entrepreneurial failure”, Small from the ashes: cognitiveofdeterminants of venture growth *Yamakawa, Y., Peng, M.W. and Deeds, D.L. (2015), “Rising from the ashes: cognitive determinants Business Economics, Vol. 44 No. 4, pp. 797-820. after entrepreneurial failure”, venture growth after entrepreneurial failure”, Entrepreneurship: Theory and Practice, Vol. 39 Entrepreneurship: Theory and No. 2, pp. 209-236.

Practice, Vol. 39 No. 2, pp. 209-236.

Appendix

Reasons for exclusion of articles from the final sample Guideline for exclusion: To be included in our final sample, an article (1) had to be settled within the context of entrepreneurship, (2) had to target the context of failure (defined as the closure of a business because it has not met a minimum threshold for economic viability) and (3) had to provide insights that contribute to a better understanding of learning Papers that did not meet one or more of these criteria were excluded from the sample Exclusion criterion

Ratio behind exclusion

Examples

(1) Lack of entrepreneurial focus

As we wish to contribute to the discipline of entrepreneurship, a clean differentiation from knowledge targeting other possible settings and disciplines is necessary We paid particular attention to a clean definition of failure (see above).

Consequently, studies that clearly utilized a different understanding of failure, were excluded To contribute to the understanding of learning, a study had to be at least clearly linked their findings to the phenomenon of learning (e.g. discussing the relationship of emotions and learning)

(1) Studies on organizational learning (2) Studies that are limited to a macroeconomic perspective

(2) Absence of failure (as defined) (3) Lack of focus on learning

e A1. ns for exclusion icles

(1) Studies that perceive failure in the sense of “setback” (i.e. a nondiscontinuous event) (2) Studies that only deal with the fear of failure (1) Studies on antecedents to failure (2) Studies on effects of failure without targeting learning or at least providing links to learning

Entrepreneurial learning from failure

Table A2.

Methodologies of studies on entrepreneurial learning from failure Methods Approach

Number of publications

Minimum

Mean

Sample Median

Maximum

Conceptual 8 Qualitative 14 1 10 7 30 Quantitative 16 142 455 240 2,024 Multi-method 2 114 247 247 380 Note(s): Table A2 considers the sample size of Nielsen and Sarasvathy (2016) (pp. 41, 259) as an outlier as it is significantly higher than the sample of any other study (see median: 240)

1131 Table A2.

Methodologies of studies on entrepreneurial learning from failure

Corresponding author Wolfgang Lattacher can be contacted at: wolfgang.lattacher@aau.at

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traditional information transmission model. In a typical application, insights from ELT along with corresponding tips for educator the educator provides a direct concrete experiencing event, such as a practice: field trip, a lab experiment, or a role play, and then organises personal 1. Learning is an endlessly recurring cycle not a linear process. or group reflections on the experience. The conceptualisation phase 2. Experiencing is necessary for learning. focuses on understanding the meaning of the experience often with 3. The brain is built for experiential learning. the addition of related subject matter lectures or reading. Learners are then asked to apply what they have learned in their own life and 4. The dialectic poles of the cycle are what motivate learning. work context. There have been countless applications of the learning 5. Learning styles are different ways of going around the learning cycle concept in educational programs ranging from individual class cycle. sessions, to courses and training programs, degree programs, the total 6. Full cycle learning increases learning flexibility and school and university curriculum, and even to national curricular development.

Dr. Aliceand Kolb and Professor David Experience policies standards in New Zealand (NZKolb, Ministry of EducationBased Learning Systems 7. Teaching around the learning cycle.

2004) and Singapore (Singapore Ministry of Education 2015).

MRJ

Eight Important Things To Know About The Experiential Learning Cycle

Figure 1. The Experiential Learning Cycle

THE EXPERIENTIAL LEARNING cycle is the most widely

8 recognised and used concept in Experiential Learning

Theory (ELT) (Kolb 2015; Kolb & Kolb 2017). The simplicity and usefulness of the four stage cycle of experiencing, reflecting, thinking and acting is the main reason for its popularity (see Figure 1). It is an adaptable template for the creation of educational programs that actively engage learners in the learning process, providing an alternative to the overused and ineffective traditional information transmission model. In a typical application, the educator provides a direct concrete experiencing event, such as a field trip, a lab experiment, or a role play, and then organises personal or group reflections on the experience. The conceptualisation phase focuses on understanding the meaning of the experience often with the addition of related subject matter lectures or reading. Learners are then asked to apply what they have learned in their own life and work context.

There have been countless applications of the learning cycle concept in educational programs ranging from individual class sessions, to courses and training programs, degree programs, the total school and university curriculum, and even to national curricular policies and standards in New Zealand (NZ Ministry of Education 2004) and Singapore (Singapore Ministry of Education 2015).

In our own work, we have met many colleagues who, based on what they have learned about it from popular reports, have used the learning cycle in their teaching for many years. When we explained the deeper foundations of

84 • Mensa Research Journal

8. cycle The learning cycle canLearning be a rubricTheory for holistic, authentic the learning in Experiential to them, they adopted assessment. new perspectives on their practice and discovered new ways to improve their teaching with experiential 1. this Learning anwill endlessly cycleimpornot a linear learning. In article,iswe outlinerecurring eight of these process tant insights from ELT along with corresponding tips for The first thing to know is that the learning cycle is an endlessly educator practice: recurringisprocess of exchange between the not learner’s internal world 1. Learning an endlessly recurring cycle a linear and the external environment. Learning is like breathing; a lifelong process. process of taking in and putting out. For educators, it is about 2. Experiencing is necessary learning. learners with the knowledge impression and expressionfor – impressing necessary live and in today’s world and coaching them to 3. The brain istobuilt for work experiential learning. express what they have learned in highly skilled ways.

4. The dialectic poles of the cycle are what motivate The learning cycle is a recursive circle or spiral as opposed to the learning. linear, traditional transmission model of learning styles areinformation different ways of going around 5. Learning used in most education where information is transferred from the the learning cycle. teacher to the learner. Paulo Freire (1992) called this the ‘banking 6. Full cycle oflearning increases learning flexibility andminds of concept education’ where ideas are deposited in the development. passive learners. In the cycle of learning, learners receive information througharound concretethe experiences transform it through reflection and 7. Teaching learningand cycle.

8. The learning cycle can be a rubric for holistic, authentic assessment.

1. Learning is an endlessly recurring cycle not a linear process

The first thing to know is that the learning cycle is an endlessly recurring process of exchange between the learner’s internal world and the external environment. Learning is like breathing; a lifelong process of taking in and putting out. For educators, it is about impression and expression – impressing learners with the knowledge necessary to live and work in today’s world and coaching them to express what they have learned in highly skilled ways.

The learning cycle is a recursive circle or spiral as opposed to the linear, traditional information transmission model of learning used in most education where information is transferred from the teacher to the learner. Paulo Freire (1992) called this the ‘banking concept of education’ where ideas are deposited in the minds of passive learners. In the cycle of learning, learners receive information through concrete experiences and transform it through reflection and thinking and then transform it again through their actions to change the world. They are both receivers and creators of information.

A tip for educators: Organise your course or curriculum as a series of learning cycles to form a deepening spiral of Originally published in volume 40 issue 3 of Australian Educational Leader, Experience Based Learning Systems

in complexity and application. The learning modes are revisited, and students’ understanding is developed further each time. They discover more about the practical limits and the wider applications of their new knowledge by taking what they have learned in one situation and using it in another.

Eight Important Things To Know About the Experiential Learning Cycle

necessary to activate such reflection in the first place. While some learning probably occurs from everyday experience, it is probably the kind that reinforces previous conclusions or refines thought or behavior in small ways. For bigger changes in beliefs and behaviour, a ‘shock’ that disrupts life may be required.

A tip for educators: As educators it is important to create learning experiences such as field projects, role plays and other experiential exercises where learners are experiencing and not just going through the motions of a class exercise.

The experiential approach places the subject to be learned in the centre to be experienced by both the educator and learner. As Parker Palmer states, in the subject-centred classroom, ‘the third thing (the subject) has a presence so real, so vivid, so vocal, that it can hold teacher and students alike accountable for what they say and do’ (1998, p. 117).

3. The brain is built for experiential learning

There have been a number of studies that examine the relationship between the learning cycle and brain functioning Figure 2. The Experiential Learning Spiral (Eagleton 2011; McCarthy 1987), but the most systematic examination of the neurological basis of the learning cycle learning that expands in complexity and application. The is James Zull’s research reported in his two great books, The 2. Experiencing is necessary for learning learning modes are revisited, and students’ understanding Art of Changing the Brain (2002) and From Brain to Mind A Google image search of ‘learning cycle’ or ‘experiential learning is developed further each time. They discover more about (2011). His aim was to understand how Piaget’s concept of cycle’ shows that the Concrete Experience, a.k.a. Experiencing mode constructivism in learning could be understood in neurothe practical limitscycle, and isthe wider applicationsAofnumber their new of the ELT learning widely misunderstood. of the logical terms. His basic idea was that knowledge resides in knowledge taking whatexperiencing they have learned in one situation cycle imagesby seem to equate with doing while others haveusing no place foranother. experiencing at all. This is unfortunate since the networks of neurons in the neo-cortex constructed through and it in experiencing mode of the learning cycle has particular significance learning from experience. Learning from experience results for learning. All modes of the learning cycle are experiences, but in modification, growth, and pruning of neurons, synaps2.

Experiencing is necessary for learning it is here-and-now experiencing that initiates learning. Everyday Aexperience Google and image search of ‘learning cycle’ or ‘experiential es and neuronal networks; thus learning physically changbehaviour are notoriously conservative and es the brain and educating is the art of changing the brain. learning Concrete Experience, automatic,cycle’ being shows habitualthat and the culturally mediated by many a.k.a. previous Zull says: ‘The learning cycle arises from the structure of the Experiencing of the ELT cycle, widely mistrips around themode learning cycle.

Anlearning experience mayisappear fresh and understood.

A number theinterpretations cycle imagesofseem to equate brain’ (Zull 2002, pp. 18-19; Zull 2011). While acknowlnew, but it is saturated withofthe past generations.

John Dewey emphasised that to initiate reflection this edging the greater complexity of brain functioning, he proexperiencing with doing while others haveand nolearning place for normal flow of experience must be interrupted by deep experiencing, experiencing at all. This is unfortunate since the experienc- posed that the regions of the brain described below were suchmode as when arelearning ‘stuck’ with a problem or difficulty or ‘struck’ heavily, but not exclusively involved in the modes of the ing ofwethe cycle has particular significance by the strangeness of something outside of our usual experience. for learning. All modes of the learning cycle are experiences, learning cycle (see Figure 3). Their respective functions of William James (1977) called this ‘pure experience’. but it is here-and-now experiencing that initiates learning. sensing (CE), remembering (RO), theorising (AC) and actWhile many have stressed critical reflection is of primary Everyday experience andthat behaviour are notoriously conser- ing (AE), he called the four pillars of learning: importance for learning from experience, we see here that a • Concrete experience and sensing in the sensory cortex. vative and automatic, being habitual and culturally mediconcrete ‘pure’ experience that violates the expectations of previous The sensory cortex receives information from the ated by many trips around the learning convictions andprevious habits of thought is necessary to activatecycle. such An outside world through the senses. experience appear butprobably it is saturated reflection in may the first place.fresh Whileand somenew, learning occurs • Reflective observation and remembering in the back with the interpretations past generations.

John Dewey from everyday experience, itof is probably the kind that reinforces previous conclusions refinesreflection thought orand behavior in small integrative cortex. The back integrative cortex inteemphasised that to or initiate learning this ways. norFor bigger changes in beliefs andbe behaviour, a ‘shock’ that disrupts grates sensory information to create images and mal flow of experience must interrupted by deep experi- life may be required. meaning. encing, such as when we are ‘stuck’ with a problem or difficulty or ‘struck’ by the strangeness of something outside • Abstract conceptualisation and theorising in the front of our usual experience. William James (1977) called this integrative cortex. The frontal integrative cortex uses ‘pure experience’. short term memory to choose, plan, problem solve and make decisions to accomplish a goal.

While many have stressed that critical reflection is of primary importance for learning from experience, we see • Active experimentation and acting in the motor cortex. here that a concrete ‘pure’ experience that violates the expecAction closes the learning cycle and reconnects the processing inside the brain with the world. It genertations of previous convictions and habits of thought is

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Eight Important Things To Know About the Experiential Learning Cycle

James uses the analogy of a pair of scissors – in the same way we need both blades to cut, we need both concrete experience and abstract thinking to make sense of the world.

Reflecting and acting are similarly opposing ways of transforming understanding. The great educator Paulo Freire (1992) stressed 4.thisThe dialectic poles of the learning the importance of naming one’s own experience in dialogue cycle are what motivate learning with others, emphasising praxis, the transformative dialectic What makes the learning go?

What motivates us to between reflection and action.cycle When either action or reflection is learn?

The answers to these questions lie in the dialectic overemphasised, dialogue becomes impossible.

poles of opposing modes of the learning cycle. Concrete These opposing dialectic poles give us a ‘stereo’ perspective that sense experience and abstract thinking are two fundamenmotivates learning. When one pole dominates the other, learning tally different ways of understanding experience. ceases.

Hyper-activity or withdrawal into reflection bothWilliam inhibit James (1977) called these percepts and concepts.

Perceplearning. Dogmatic beliefs leave us closed to new experience while tion exists in the here and now; conceptions point the total immersion in experience clouds clear thought. On thetoother past orthe future. usesof the analogy of a paircan of cause scissors – hand, ‘shockJames and awe’ an intense experience an need entrenched a new canboth reshape inreconsideration the same wayofwe both belief, bladeswhile to cut, weidea need the way we experience things.

Reflection on the consequences concrete experience and abstract thinking to make senseofof action can serve to correct errors and refine future actions while the world. acting on reflections can stop incessant rumination.

Reflecting and acting are similarly opposing ways of

86 • Mensa Research Journal

Experience

AE Active Experimentation

Transform

• •

• •

Experience Grasp

A tip for educators: Zull’s books are filled with implications and recommendations for educators and learners. Here are a few related to experiential learning: • The opportunities for deep learning are enhanced with a balanced use of all four learning modes and their corresponding parts of the brain.

• The learning cycle’s four modes give the brain four times the chance to remember. It is metacognitive and produces episodic memory central to future deliberate transfer of learning.

• Emotion influences thinking more than thinking influences emotion. Positive emotions (e.g. joy) enhance learning.

• Physical changes occur in the brain when we learn.

Begin with existing neuronal networks which are the physical form of prior knowledge and build on it.

• Learning how to learn should be a focus of education.

• It is better to start with concrete examples rather than abstract principles. Abstract principles are where we are, not where the learners are.

• Real experiences that flood all the senses are the best for learning. Rich experiences, such as those which change and surprise, are more memorable.

• Be careful to not overload the limited capacity of working memory. Shoving information in at one end only pushes out information at the other.

• Always provoke an active reaction from learners. A safe environment for failure can help in this.

T in le fo ea d P u

•

CE Concrete Experience

ates consequences that create new experiences that begin the cycle anew.

tr in d L o S T a en

RO Reflective Observation

• • •

AC Abstract Conceptualisation

•

Figure 4. The motivating dialectic poles of the learning cycle A tip for educators: Design educational programs to engage the

transforming this understanding. The great educator Paulo dialectic polarities of the cycle, e.g. add systematic reflection and Freire (1992) stressed importance of internship naming one’s own conceptual analysis to athe concrete and active program. experience in stimulate dialoguecuriosity with others, emphasising praxis, Activities that and active problem solving are the transformative between reflection and action.one great motivators for dialectic learning. Avoid designs that only emphasise learning mode such as or field trips with no de-briefing.

When either action orlectures reflection is overemphasised, dialogue becomes impossible.

5.These Learning stylesdialectic are different ofagoing around the opposing poles ways give us ‘stereo’ perspeclearning cycle tive that motivates learning. When one pole dominates the Learning style is ceases. another Hyper-activity popular concept inorExperiential Learning other, learning withdrawal into Theory. It both is important it emphasises that individuals reflection inhibitbecause learning.

Dogmatic beliefs leave learn us in different ways and that educators can better facilitate their students’ closed to new experience while total immersion in experilearning if they understand the unique way that they learn. ence clouds clear thought. On the other hand, the ‘shock and awe’ of an intense experience can cause reconsideration of an entrenched belief, while a new idea can reshape the way we experience things. Reflection on the consequences of action can serve to correct errors and refine future actions while acting on reflections can stop incessant rumination.

A tip for educators: Design educational programs to engage the dialectic polarities of the cycle, e.g. add systematic reflection and conceptual analysis to a concrete and active internship program. Activities that stimulate curiosity and active problem solving are great motivators for learn-

F cy

problem solutions and courses of action.

•

AC Abstract Conceptualisation

ing. Avoid designs that only emphasise one learning mode

The Acting style – a strong motivation for goal-directed action that integrates people and tasks.

Eight Important Things To Know About the Experiential Learning Cycle • The Balancing style – adapting by weighing the pros and cons of acting versus reflecting and experiencing versus thinking.

such 4.asThe lectures or field trips poles withofnothede-briefing.

Figure motivating dialectic learning cycle A tip for educators: Design educational programs to engage the 5. Learning styles are different ways dialectic polarities of the cycle, e.g. add systematic reflection and of going around the learning cycle program. conceptual analysis to a concrete and active internship Learning style is another popular concept in ExperienActivities that stimulate curiosity and active problem solving are great learning.ItAvoid designs that only emphasise one tialmotivators Learningfor Theory. is important because it emphasises learning mode such aslearn lectures field trips ways with noand de-briefing. that individuals inordifferent that educators

can better facilitate their students’ learning if they under-

5. Learning styles are different ways of going around the stand the unique way that they learn. learning cycle

The idea is much discussed in education today and

Learning style is another popular concept in Experiential Learning there Itisisconsiderable confusion about itsindividuals usefulness, ininpart Theory. important because it emphasises that learn because there has been a proliferation of over 100 learndifferent ways and that educators can better facilitate their students’ learning if they understand the unique that they learn. conceptual ing style instruments that varyway widely in their

basis and psychometric soundness. Criticism of the concept has tended to lump all of these approaches together (Scott 2010), resulting in some misunderstanding of the unique nature of the ELT learning style concept.

As a result, ELT learning style has been mischaracterised as a static trait and not a dynamic state in the learning cycle process. Styles in ELT are habitual preferences for the interdependent poles of the dialectics of action and reflection and experiencing and thinking. Learning style is a habit of learning that is formed when one or more of the learning modes are preferred over others to shape experience. Seen this way, learning style loses its static stereotype prone character. The recognition of a style opens the possibility of learning flexibility and the challenge of full cycle learning – to develop the ability to engage all modes of the learning cycle in a holistic and fluid manner.

The Kolb Learning Style Inventory (KLSI) describes the unique ways individuals spiral through the learning cycle.

In the KLSI, a person’s learning style is defined by their unique combination of preferences for the four learning modes defining a ‘kite’ shape profile. Because each person’s learning style is unique, everyone’s kite shape is a little different. Our latest research with the KLSI 4.0 (Kolb & Kolb 2011; Peterson & Kolb 2017) has identified nine style types that individuals use (see Figure 5): • The Initiating style – initiating action to deal with experiences and situations.

• The Experiencing style – finding meaning from deep involvement in experience.

• The Imagining style – imagining possibilities by observing and reflecting on experiences.

• The Reflecting style – connecting experience and ideas through sustained reflection.

• The Analysing style – integrating ideas into concise models and systems through reflection.

• The Thinking style – disciplined involvement in abstract reasoning and logical reasoning.

• The Deciding style – using theories and models to decide on problem solutions and courses of action.

Figure 5. The nine learning styles and their place on the learning cycle

• •

The Acting style – a strong motivation for goal- 11 directed action that integrates people and tasks.

The Balancing style – adapting by weighing the pros and cons of acting versus reflecting and experiencing versus thinking.

A tip for educators: Because of the learning style differences in the way individuals apply the learning modes, the learning cycle should be considered an idealised depiction of the learning process that can vary widely in application.

Learners may begin with their preferred style and engage the learning modes in their own way regardless of the educator’s plan.

The idea that learning must always begin with concrete experience and proceed through the other stages around the cycle is not an iron law, although a number of our experiential educator friends are strong advocates of beginning learning experiences with a direct concrete experience. They have strong arguments for the practice. They argue that beginning with a shared direct experience ‘brings the subject into the room’, democratising the learning process between educator and learners. In addition, the puzzles or problems presented by direct experience involve learners and motivate inquiry and reflection, initiating the learning cycle.

6. Full cycle learning increases learning flexibility and development

When one can engage all learning styles in their learning process, they are using the most powerful form of learning that we call full cycle learning. Full cycle learning is the ability to engage all of the learning style types in a holistic and fluid manner in a given situation. This requires learning flexibility. Many individuals feel that their learning style accurately describes how they learn most of the time. They are consistent in their approach to learning. Others, however, report that they tend to change their learning approach depending on what they are learning or the situation they are in. They may say, for example, that they use one style in the classroom

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Eight Important Things To Know About the Experiential Learning Cycle

and another at home with their friends and family. These are flexible learners. Studies show that some learners are able to flex their learning styles according to the demand of different learning tasks and some suggest that students can shift their learning style to match the learning demands of a particular discipline.

A tip AEL for40educators: To increase learning flexibility and Issue 3 full cycleLead learning capacity when planning educational activiArticle ties, it is useful to consider the specific learning style skills that you want to develop in students for each activity. The A tip for educators: Because of the learning style differences in the KLSI 4.0 includes a measure of learning flexibility and idenway individuals apply the learning modes, the learning cycle should tifies thebe‘back-up’ styles that considered anlearning idealised depiction of theindividuals learning processuse thatto canlearn widely in application. Learners may begin with their preferred differentvary things.

This can be useful information for learners style and engage the learning modes in their own way regardless of to knowtheineducator’s order to set meaningful learning flexibility develplan. opmental Thegoals. idea that learning must always begin with concrete experience and proceed through the other stages around the cycle is not an iron law, although a number of our experiential educator friends are strong advocates of beginning learning experiences with a direct concrete experience. They have strong arguments for the practice.

They argue that beginning with a shared direct experience ‘brings the The confusion learning styletheliterature has between resulted in subject intoin thethe room’, democratising learning process educator and learners.

In addition,that the puzzles or problems presented the oversimplified prescription educators should match by direct experience involve learners and motivate inquiry and their teaching style and methods to the learning style of the reflection, initiating the learning cycle.

7. Teaching around the learning cycle with dynamic matching of teaching role

learner. The dynamic matching model of ELT is a more comFull cycle learning increases flexibility and pracplex but6. more realistic model forlearning guiding educational development tice. In addition to considering the relationship between When one can engage all learning styles in their learning process, educatortheyand learner, one mustform also consider thecallmatch of are using the most powerful of learning that we full learning. Full cyclethe learning is the matter. ability to engage all of teachlearningcycle approach with subject Matching learning style types in a holistic and fluid manner in a given ing stylethe with learning style has been shown to be important situation. This requires learning flexibility. Many individuals feel initiallythat to their connect with engage learners, but most learnlearning styleand accurately describes how they learn most of the time.

Theythey are consistent in their learning.around Others, the ing requires that continue to approach activelyto move however, report that they tend to change their learning approach learningdepending cycle using to acquire on whatother they arelearning learning or styles the situation they are in.increasThey mayknowledge say, for example,and that skills. they use one style in the classroom ingly complex and another at home with their friends and family. These are flexible We have created role framework learners.

Studies an showeducator that some learners are able to flex(see theirFigure 6) learning styles according to the demand of different learning tasks to assistand educators in the application of the ELT concepts of some suggest that students can shift their learning style to match the learning cycledemands and learning stylediscipline. in the dynamic matching the learning of a particular

Figure 6. Educator Role Profile 12

88 • Mensa Research Journal

model of teaching around the learning cycle. It describes four common educator roles – Facilitator, Subject Expert, Standard-Setter/Evaluator and Coach. Most of us adopt each of these roles to some extent in our educational and teaching activities. While the role profile model depicts an idealised sequential progression through the educator roles and the learning cycle, in most cases a curriculum design will be based on a sequence of activities and instructional techniques that fit the subject matter and learning objectives that may or may not occur in such an orderly progression.

A tip for educators: To increase learning flexibility and full cycle • The Facilitator role: When facilitating, educators learning capacity when planning educational activities, it is useful to consider the specific learning skills that you want to develop help learners get style in touch with their personal experiin students for each activity. The KLSI 4.0 includes a measure of ence and reflect on it.

They create personal and trustlearning flexibility and identifies the ‘back-up’ learning styles that individuals use to learn different This can be useful ing relationships withthings. learners. information for learners to know in order to set meaningful learning • The Subject Expert role: In their role as subject flexibility developmental goals. expert, educators help learners organise and connect 7. Teaching around the learning cycle with dynamic their reflections to the knowledge base of the subject matching of teaching role matter. This knowledge is often communicated The confusion in the learning style literature has resulted in the overlectures and should texts.match their teaching simplifiedthrough prescription that educators style and methods to the learning style of the learner. The dynamic • The Standard-Setter/Evaluator role: As a standardmatching model of ELT is a more complex but more realistic model for guiding educational practice. In addition to considering the setter and evaluator, educators help learners master the relationship between educator and learner, one must also consider application of knowledge and skill in order to meet the match of learning approach with the subject matter. Matching teaching style with learning requirements. style has been shownThey to be important performance create performance initially to connect with and engage learners, but most learning activities for learners evaluate their learning. requires that they continue to actively to move around the learning cycle using other learning styles to acquire increasingly complex • The Coaching role: In the coaching role, educaknowledge and skills. tors help learners apply knowledge to achieve their We have created an educator role framework (see Figure 6) to assist They assist the creation personal developeducatorsgoals. in the application of thein ELT concepts of the of learning cycle andment learningplans style inand the dynamic matching of teaching provide waysmodel of getting feedback on around the learning cycle. It describes four common educator roles – performance.

Facilitator, Subject Expert, Standard-Setter/Evaluator and Coach. Most of us adopt each of these roles to some extent in our educational and A tip for educators: Using the Educator Role framework teaching activities. While the role profile model depicts an idealised tosequential teach around learning cycleroles is and a high art; and you, the progressionthe through the educator the learning cycle, in most cases a curriculum design will be based on a sequence educator are its prime instrument. How can we best promote of activities and instructional techniques that fit the subject matter learning forobjectives our students? we inbesuch learner-centred and and learning that may or Should may not occur an orderly progression.

Eight Important Things To Know About the Experiential Learning Cycle

draw out their budding interests? Should be we subjectcentred and deliver our special knowledge, developing learners’ capacity for reflective thinking about our field? Should we focus on the pragmatic applications and implications of the ideas; or should the emphasis be on the deep meaning of these ideas and concepts, their origins and connections to other ideas and fields of study? In the abstract, we would probably answer all four questions affirmatively, but in a practical context there are very real constraints that require tradeoffs between the learner and subject focus and the action and meaning focus – time limitations, learner needs, the amount of subject matter to be ‘covered’, its complexity and required evaluation standards, to name a few, as well as your own teaching role preferences and skills. (To assess your educator role preferences, take the free Educator Role Profile at: http:// survey.learningfromexperience.com/).

8. The learning cycle can be a rubric for holistic, authentic assessment

The multidimensional teaching and learning strategies of experiential learning require equally diverse and complex assessment methods that adequately and fairly evaluate students’ effective integration of the affective, perceptual, cognitive, and behavioural dimensions of learning. Assessment becomes holistic when the focus is on all four of the learning modes.

Authentic assessment means learners should demonstrate knowledge and skills in their real-life context. The goal of authentic evaluation is to draw education close to real life.

If we want our assessment of students to be authentic, the subject-centred question, ‘What should my students know?’ can only be appropriately addressed in conjunction with the learner-centred question: ‘How can I help my students learn skills and knowledge and be able to transfer what they have learned in a real life context?’

A tip for educators: Try using the Personal Application Assignment (PAA) available at: https://learningfromexperience.com/research-library/evaluating-experiential-learningthe-personal-application-assignment.md/. PAA is an essay/ journal based holistic, authentic assessment rubric using the learning cycle framework.

In the PAA, participants: • select an experience, occurring either in or out of the training session, and chronicle the actual events of the experience • review their thoughts and feelings about the experience, making observations about it from a fresh perspective • develop concepts or theories that make sense of the experience • create future action plans based on what they have learned from the experience.

The rubric includes a scoring system for grading the essays.

References

Eagleton, S & Muller, A 2011, ‘Development of a model for whole brain learning of physiology’, Adv Physiol Educ, vol. 35, no.

4, pp. 421-426.

Freire, P 1992, Pedagogy of the oppressed, Continuum, New York.

James, W 1977, ‘Percept and concept: The import of concepts’, in J McDermott (ed.), The writings of William James, University of Chicago Press, Chicago.

Kolb, AY & Kolb, DA 2011, Learning style inventory version 4.0–online, Korn Ferry, <http://store.kornferry.com/ store/lominger/en_US/list/categoryID.4836644000/ parentCategoryID.4836643700>.

Kolb, AY & Kolb, DA 2017, The experiential educator: Principles and practices of experiential learning, EBLS Press, Kaunakakai, HI. Kolb, DA 2015, Experiential learning: Experience as the source of learning and development, 2nd edn, Pearson Education, New Jersey.

McCarthy, B 1987, The 4-mat system: Teaching to learning styles with right/left mode techniques, Excel, Inc., Barrington, IL. New Zealand Ministry of Education 2004, The Curriculum in Action–Making meaning: Making a difference, Learning Media Limited, <www.tki.org.nz/r/health/cia/make_meaning/ index_e.php>.

Palmer, P 1998, The courage to teach: Exploring the inner landscape of a teacher’s life, Jossey-Bass, San Francisco.

Peterson, K & Kolb, DA 2017, How you learn is how you live: Nine ways of learning that can transform your life, Berrett-Koehler, San Francisco.

Singapore Ministry of Education 2015, Handbook for the Cocurriculum, <http://cchb.opal.moe.edu.sg>.

Zull, J 2002, The art of changing the brain, Stylus, Sterling, VA. Zull, J 2011, From brain to mind: Using neuroscience to guide change in education, Stylus, Sterling, VA.

*** Dr. Alice Kolb and Professor David Kolb are the principals of Experience Based Learning Systems (EBLS), an experiential learning research and development organisation. For nearly 40 years, in collaboration with an international network of researchers, practitioners and learning partners, EBLS has facilitated and curated research on the theory and practice of experiential learning with a current bibliography listing over 4500 articles on experiential learning theory.

Their recent works include the new version 4 of The Kolb Learning Style Inventory (KLSI) and The Kolb Educator Role Profile, an inventory designed to help educators apply experiential learning principles in their work. Their latest book, The Experiential Educator: Principles and Practices of Experiential Learning, provides educators with a complete review of the latest research on experiential learning and a practical guide to the use of experiential learning in education.

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A Few Thousand Words, on ‘A Thousand Brains’: A Book Review on Jeff Hawkins’ New Theory of Intelligence

By Ryan Donlan, Ed.D. WE MIGHT ASK ourselves, as author, computer pioneer, and neuroscientist Jeff Hawkins suggests, “If no brains were around to perceive the universe, would the universe exist?”

While the question may seem unreal, consider the possibility that the reality that we all perceive today is simply a constructed reality, as Richard Dawkins muses in the book’s forward, when referring potentially to “a model, updated and informed by bulletins streaming in from the senses” (p. ix).

These and other provocative notions are addressed in the book A Thousand Brains: A New Theory of Intelligence, in which author Hawkins presents answers to the question, “How do brains create intelligence?”

Hawkins’ book is divided into three parts building smartly upon one another, first presenting his theory regarding a new understanding of the human brain, A Thousand Brains Theory. It is a result of decades of his team’s work as theoretical scientists, developed in the context of findings of experimental scientists worldwide. Hawkins then applies his theory in the context of artificial or machine intelligence, discussing how current research and development is moving in the wrong direction and offering how alternate approaches in the use of intelligent machines could benefit humanity. Finally, Hawkins discusses the future of human intelligence, particularly in confronting existential risks to human life and our planet’s existence—and what we might do to preserve knowledge of humanity once we cease to exist, no matter how far off in the future.

In terms of style and audience, Hawkins writes for the layperson interested in human intelligence, with due respect to field experts. For the latter, he provides citations for suggested readings. I was able to access quickly 19 out of 23 references provided through typical university search engine channels.

Hawkins launches Part 1 of his book by conceding that the way in which simple cells create intelligence is still largely a mystery, we are learning more all the time.

He likens the work of brain researchers to a jigsaw puzzle project but notes that, unlike puzzles at home, their work does not include a picture of the finished product on the box’s cover. Hawkins’ hope is to apply a new framework of discoveries regarding the biology of the brain to build more intelligent machines. The first discovery he gleans from scientists is the human brain learns a model of the world, noting his 2016 discovery that the neocortex stores incoming knowledge through reference frames, much as

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grid lines work to denote latitude and longitude on a map.

Reference frames tell our brains where things in the world are located relative to other things. Hawkins uses an example of how we perceive a bike, knowing how the things on a bike are arranged and fit together to make such a thing we can identify. I now detail the chapters in this first section of the book.

Chapter 1, Old Brain–New Brain, explains how in brain development, new parts are added on top of older parts, such as the neocortex, or “new outer layer” (p. 12). Typical of his lay-interest writing style and with the metaphor of a dinner napkin and wine glass, Hawkins provides thoughtful detail regarding the form and function of the part of us that is the organ of intelligence, and as well, how that part interacts with its older companion part, much as roommates living amicably together need to cooperate. He moves through a discussion of what many of us have learned from science about regions of the brain, juxtaposing scientific interpretations of the brain as a hierarchical flowchart of knowledge acquisition with his own assertion that the brain is not hierarchical. Hawkins suggests local circuitry is complex, where “connections between the regions . . . seem to have little order, suggesting that information goes all over at once” (p. 19), and regions look similar to each other. The chapter offers an interesting departure in terms of new theories gleaned from science.

Chapter 2, Vernon Mountcastle’s Big Idea, presents the notion that the neocortex grew over time by “making copies of the same thing: a basic circuit” (p. 22). Hawkins proposes

A Thousand Brains: A New Theory of Intelligence, a Book Review

from Mountcastle’s work that all things regarding intelligence—“from seeing, to touching, to high-level thought” (p. 23) are much the same and based on a fundamental unit, the “cortical column.” Hawkins notes the human brain is composed of 150,000 of these cortical columns, 2.5 mm in thickness, stacked side by side like pieces of spaghetti. He argues they all have the same fundamental algorithm responsible for every aspect of intelligence.

The challenge we have is to understand just how cortical columns work. Fitting well in this chapter is imagery, again derived from metaphor, that a layperson can use in conversation.

Chapter 3, A Model of the World in Your Head, focuses on prediction as a key function of our neocortex— multiple, simultaneous predictions in all sensory modalities from even the smallest stimuli registering. Hawkins notes the neocortex learns the world by making predictions based on an ever-developing model. He states the neocortex cannot turn off the model’s development, as the world is constantly moving and we are constantly moving within it. To explain this, Hawkins provides what I liken to a Neuron 101 lesson, particularly in how at any given time some neurons spike and others do not. Further, the more often neurons spike together, the stronger their connections, which lead to memories. He closes with a notion of how learning occurs between neurons that were not previously connected and are then so co-joined, via spiking. He provides a rapid, microscopic drill-down to similar points in literature, such as why the 10,000 rule is posited and how brain circuitry can develop into a neural superhighway. For the layperson such as me, Hawkins might have started with a highway description and thereafter taken a deeper dive into detail.

Chapter 4, The Brain Reveals Its Secrets, showcases three key moments Hawkins and his team developed their understanding of the brain over the years, when their discoveries moved forward more rapidly. The first discovery had again to do with the brain’s predictive modeling of the world, which led to the question, “How?” The second was that prediction occurred inside neurons—it has to do with the job descriptions of the cortical columns. Hawkins zeroes in on what happens when predictions take place; it is almost as if a pump of the brain’s predictive state is primed by dendritic activity. Bringing this all together, Hawkins notes the relationship between cortical columns and reference frames. He observes this is a far cry from former scientific beliefs that the neocortex processes sensory input sequentially. Hawkins concludes by describing the difference between former theories and his own and makes an argument that even with a lack of experimental evidence for his synthesis within the model, the fact that his model satisfies and solves most constraints is compelling, indeed.

Chapter 5, Maps in the Brain, introduces readers to the constructs of grid cells and place cells and to how the two

of them work to create a model of the world’s environment as we interact with the world. Also situated within each cortical column are cells that provide direction and orientation mapping. Hawkins notes, interestingly, that each of these types of cells originated in our old brain yet has taken up residency in our new brain with a more sophisticated system of interdependence that allows us to make meaning of the reality around us as we interact with it.

Chapter 6, Concepts, Language, and High-Level Thinking, harkens back to Vernon Mountcastle’s proposal that all high-level cognitive abilities are really composed of the same types of cerebral structures. The chapter extends these notions to how knowledge is created, stored, and retrieved. Hawkins’ hypothesis is four-part: (1) “Reference Frames Are Present Everywhere in the Neocortex”; (2) “Reference Frames Are Used to Model Everything We Know, Not Just Physical Objects”; (3) “All Knowledge Is Stored at Locations Relative to Reference Frames”; and (4) “Thinking Is a Form of Movement.” Further, two types of grid cells provide reference—one that attaches reference frames to outside objects and another that attaches them to your body. Thinking for Hawkins is defined as mentally moving directionally through a reference frame, which explains why two people experiencing a particular circumstance might “arrange the facts differently” (p. 81). He notes that common to everyone and to all perception and cognition is an algorithm that exists in cortical columns, where “each column is a learning machine” (p. 89).

Chapter 7, The Thousand Brains Theory of Intelligence, brings together these discoveries with Hawkins’ assertion that his theory makes more sense than hierarchical theories that include feature detectors, with incoming stimuli passing through various regions that detect more finely what is being perceived. He also shares why prior theories have not yet been discounted in the scientific community.

His theory states, “Knowledge in the brain is distributed.

Nothing we know is stored in one place. Nor is anything stored everywhere, like in a hologram. Knowledge of something is distributed in thousands of columns, but these are a small subset of all the columns” (p. 97). Provocative in Hawkins’ theory is the notion that among these thousands of storage areas of knowledge, the columns actually get to vote to bring their representations together. They communicate horizontally across the network.

What was refreshing in the way this chapter concludes was Hawkins’ description of how his Thousand Brains Theory addresses point by point, the shortcomings inherent in the more mainstream and still-embraced hierarchical theories of cognitive processing. Back to the puzzle metaphor, Hawkins concedes that his theory only finishes the puzzle’s border, with much of the puzzle still undone.

We now move into Part 2 of the book, Machine Intelligence. Hawkins begins by stating the future of machine intelligence—if it is to work to benefit humanity—needs

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to be much different than current efforts working with artificial intelligence (AI). The work, rather, will need to be based on principles that align with Hawkins’ Thousand Brains Theory.

Chapter 8, Why There Is an “I” in AI, poses that current technologies based on deep learning of certain skills—such as recognizing languages and playing board games—fall short, in that once machines are trained to do what they will do and are deployed, they are not designed to learn anything else; conversely, humans continually learn. To benefit humanity, a long-term goal would have machines learning many things, even to solve problems, a term Hawkins presents as artificial general intelligence (AGI).

Hawkins contends that this will be possible only when machines—like our neocortex—learn map-like reference frames of our world and design novel solutions to unanticipated problems. Making relevant his point, Hawkins asks the reader to imagine what a team of robot workers would need to be able to do on Mars to build a habitable environment for humans. Hawkins concludes by offering four criteria or attributes a machine will need to possess to be considered truly intelligent: learning continuously; learning via movement; utilizing a many-models design like the neocortex; and using reference frames to store knowledge.

He states, “We are intelligent not because we can do one thing particularly well, but because we can learn to do practically anything” (p. 134).

Chapter 9, When Machines Are Conscious, begins with an explanation of what makes us aware, which is to form moment-to-moment memories of our actions and thoughts. Machines doing this would be aware and conscious of their existence, Hawkins notes. That said, the whole notion of consciousness has two scientific perspectives—one that considers it beyond the realm of scientific explanation and the other that believes we will understand it when we are able to understand better the mechanisms involved. Hawkins then introduces an ethical discussion of whether or not it would be appropriate to unplug a machine if it had the ability to be conscious. Would it be like murdering someone if you never plugged it in again, he ponders? As fears and emotions are situated in the old brain, Hawkins does not believe this would be the case yet concedes that for the humans who know the machine, they might become sad, borne of attachment. While this chapter presented interesting topics for an academic discussion, I found it more of a scenic overlook on a journey, rather than an integral part of the book’s pathway.

Chapter 10, The Future of Machine Intelligence, notes the reasons thus far we have not been able to create machines with flexible intelligence are that we neither understand fully what intelligence is nor the mechanisms that create it. Hawkins opines on the importance of this understanding, noting, “Machine intelligence will transform our lives and our society. I believe it will have a larger impact on

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the twenty-first century than computing did on the twentieth” (p. 145). He then offers perspective on how much of the human being we should attempt to replicate in creating intelligent machines, noting the neocortex as necessary, as well as certain parts of the old brain. Hawkins offers a recipe for designing an intelligent machine, including embodiment, with sensors and the ability to move them; an old-brain equivalent, in terms of basic movements, safety features, and goals and motivations; and a neocortex equivalent. He then offers commentary on such topics as brain capacity, cloning, and the currently unknown future applications that will most certainly arise.

Chapter 11, The Existential Risks of Machine Intelligence, begins with Hawkins’ assertions that many of us view artificial intelligence as a threat to humanity, noting its ability to “track people, influence elections, and spread propaganda. These kinds of abuses will get worse when we have truly intelligent machines” (p. 162). Hawkins notes two perceived risks at the forefront: (1) machines will outpace human beings in intelligence acquisition and will get rid of us because they no longer need us, and (2) machines will have goals that run counter to ours, and we will be unable to stop them. The chapter then devotes time to assuaging the fears of those who have these concerns and offers a counterargument wherein Hawkins argues that intelligent machines “do not pose an existential threat to humanity” (p. 168).

We then move into Part 3 of the book, Human Intelligence. Hawkins begins by stating that human intelligence is the cause of the rapid changes we currently experience on our planet, such as climate change and species extinction. He notes that with the success of the human species come problems such as a growing population, ecological damage, and the “potential for a small number of people to kill billions of others” (p. 172). Human intelligence is our existential threat, in other words. He then details his arguments about such problems in the remaining chapters of the book.

Chapter 12, False Beliefs, begins by noting again the world we live in is not real, rather a simulation in our brain: a place with no sensors in itself . . . a place that is “sitting in the dark, isolated from the world outside” (p.

173). This was a refreshing return to the content in Part 1.

I believe the point Hawkins was making is that the physiological processes through which we perceive the world can lead us to false beliefs, which are a danger to humankind. Hawkins offers tangible examples of how this works with visual images that cause incorrect perceptions, as well as descriptions of the phenomenon of phantom limbs in amputees. Today, he notes, false beliefs are more pervasive than ever before with the advent of the internet and the ability to surround ourselves with others who have the same false beliefs, which can be viral. He ends with an assertion that billions hold beliefs that have been proven false, stat-

A Thousand Brains: A New Theory of Intelligence, a Book Review

ing “For example, three hundred years after the beginning of the Enlightenment, the majority of humans still believe in mythical origins of the Earth. These origin myths have been proven false by mountains of contrary evidence, yet people still believe them” (p. 184). I was a bit confused about what Hawkins meant by “mythical origins” and did not know if he was referring to fables, stories in mythology, or something else such as biblical creationism. He also made quick reference to the “fake history book” in describing how behaviors are controlled to further an interest. I would have liked to see him expand on these examples for strength of argument and reader clarity.

Chapter 13, The Existential Risks of Human Intelligence, begins with Hawkins’ notion that “Intelligence itself is benign . . . Human intelligence, however, is not as benign” (p. 185). He notes a risk that while the new human brain has created technologies with the potential to change our world, human behavior is actually controlled by our old brain, which is in itself “selfish and shortsighted” (p.

186). Hawkins then deploys an example of our having the opportunity to eat a tempting piece of cake, with our neocortex cautioning us against it and our old brain wanting to devour it. He states, “In the battle between the old brain and the neocortex, the old brain usually wins. We eat the cake” (p. 189). This is where the existential risk lies, he notes, in terms of such human-created phenomena as population growth and climate change. Hawkins poses that we know the big picture of what is happening, yet we make short-term choices that perpetuate the problem. Noting how our neocortex can be fooled with false beliefs, Hawkins offers three ways this can come about: having something presented to us we cannot experience, ignoring contrary evidence, and experiencing a viral spread of misinformation. Three illustrative examples: the belief that vaccines cause autism, the belief that climate change is not a threat, and a belief that there is an afterlife. My concern in examining Hawkins’ arguments is that the third example is not parallel, in that he then states, “Belief in an afterlife, on its own, is benign . . . The threat arises if you believe that the afterlife is more important than the present life” (p. 195). His point seems to be the risk of extremism, and his message could have been presented more directly as such. It would be interesting to have a panel conversation with Hawkins and another neuroscientist who is also a theologian.

Chapter 14, Merging Brains and Machines, presents the notion of whether human beings should consider uploading their brains to computers for the betterment of humanity’s survival, or rather merging our brains with computers. Hawkins notes uploading would be the equivalent of living inside the computer, while merging would allow us to access all information available via the internet just by thinking. He then details the necessary parts of both our brain and body we might consider uploading, with one

issue being the need to somehow recreate our eyes inside of the computer so we could see. Hawkins notes other challenges, such as what to do with our body once things are uploaded, and the fact that what we really have done is split ourselves into two people—one that would live potentially indefinitely and one that would age and die. Merging one’s brain with computers is actually already being done, Hawkins notes, such as with those who are using robot arms with electrodes implanted into their brains. Hawkins concludes that neither of these strategies would eradicate the existential risks to humanity we currently face. This chapter struck me as one more of philosophy than biology, light in style and engaging in content.

Chapter 15, Estate Planning for Humanity, touches upon a point similar to the universal question I presented at the beginning of this book review, where Hawkins asked, “If our species becomes extinct, will anyone know that we once existed, that we once lived here on Earth?... If no one finds our remains, then everything we have accomplished—our science, our arts, our culture, our history— would be lost forever. And being lost forever is the same as never existing.” Hawkins then presents the notion of estate planning for humanity, much as we do for ourselves and our families individually. He talks about three different strategies in doing this, including his own version of a message in a bottle, leaving the lights on, and creating a Wiki Earth. These are interesting topics with potential to engage both the ethicist and historian inside each of us.

Chapter 16, Genes Versus Knowledge, Hawkins’ final chapter, presents three ways humans may prevent their demise. The first is becoming a multi-planet species, which would depend upon the creation of flexibly intelligent robots. The second is choosing our future, in terms of making better decisions as stewards of our own planet and species, which will involve our new brain winning its battle over our old brain. The third is by modifying our genes, which in reading through the argument, is probably one that would bring about a more spirited debate. Hawkins discusses each of the three in terms of his theories about the human brain, providing effective closure in terms of how his theories inform practice. Finally, Hawkins calls for the creation of intelligent machines to transcend physically our orbit so as to preserve knowledge of humanity and spread our contributions across the galaxy. He also hopes they would acquire new knowledge, possibly uncovering deep mysteries about the universe.

Hawkins concludes in his Final Thoughts, “If it wasn’t for brains, then nothing would know that anything exists,” and a question, “If there is no knowledge of something, can we say that the thing exists at all?” (p. 241). He ends the book with intentional lay style—a list of things all of us need to know about the brain and what might be possible on the road forward with this understanding.

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From Phonetics to Sci Fi: Dr. Francis Cartier

By Tomiko Breland

DR. FRANCIS CARTIER not only has an impressive background but has also applied his considerable talents in support of the Mensa Foundation. I first met him in 2001 when he was a Trustee on the Foundation board, on which he served from 1988–2010. His sharp mind was a welcome asset in discussions. Not surprisingly, he served as President of the board from 1992–1995.

In 2008, he began writing a regular column in the Mensa Research Journal—his insight and curiosity yielding a thought-provoking column. In addition, he’s been a member of the Editorial Advisory Board, retiring from both roles in 2021 at the age of 97.

A long-time volunteer in many capacities, he has received the President’s Call to Service Lifetime Achievement Award, American Mensa’s Distinguished Service Award, and the Margot Award for the rendering of exceptional service to Mensa.

It’s been my pleasure to have had the opportunity to work with Dr. Cartier and to craft an introduction to this article that captures his spirit so well.

The following article was edited with permission from the original that appeared in TESOL Connections magazine.

To see the article in its entirety, visit bit.ly/cartier-profile.

—Marie Mayer, Past Interim Editor *** DR. FRANCIS CARTIER has stories. He has stories within stories, and stories built on top of stories—and nearly all of them are based on (or in the neighborhood of ) the English language. Many of them, actually, are rooted in English for specific purposes, something he was practicing years before it was recognized as a legitimate field in English language teaching.

We meet for lunch in the quaint ocean town of Pacific Grove, in California, USA, a beautiful little haven with no highway access on the Monterey Bay Peninsula, brimming with colorful historic homes and charming bed and breakfasts. I know that Dr. Cartier is in his nineties, but I would not have guessed this upon meeting him. He’s dressed in a dark gray suit jacket and crisp white shirt (what my mother would have called “smart”), a bolo clasped with a shiny jade ornament, and a red pin that looks like a dragon gleaming on his lapel (though he later tells me it is an English lion). As we pass through his retirement community, several ladies smile and tell him he looks dapper.

I’m a little nervous; Dr. Cartier boasts an impressive CV. He’s a doctor of speech pathology, a former editor for sever-

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al academic journals and professor and director of multiple language programs, and a past president of the Mensa Education & Research Foundation.

We sit and I become acutely aware of my posture, perhaps because Dr. Cartier’s is superb; this is no surprise when I learn that he was a soldier. Before the war (he refers to World War II always as “the war”), he’d been a radio announcer and radio playwright, but, as he says, “I talked myself into it, and before I knew it I was a bombardier.”

After the war, the Air Force paid for Dr. Cartier’s education, and he was burdened with the decision of what field to pursue. At the University of Southern California, he began in the Drama Department, which was a subdivision of the Speech Program, to become an actor. He was required to take some speech science courses (phonetics, mechanics of speech, etc.). The science pulled at him, though, and he ended up with a PhD in speech pathology—a far cry from the theater work he’d once aspired to.

A lifelong career with the military began when Dr. Cartier was recruited from his teaching position at the University of Florida to write textbooks for the Air Force. In 1947, leading into World War II, the Army Air Corps was becoming the Air Force, and they needed new materials. Dr. Cartier cowrote Introduction to the Air Force, in which he was responsible for the technical vocabulary section for recruits who might not know the terms they needed—“about how planes fly” (or aerodynamics).

When I ask him what he knew during this time about English for specific purposes (ESP), he waves it off with his hand, “It was an incipient field back then.” However, he’s being modest. ESP as a field wouldn’t show up for nearly two more decades, “emerging out of Halliday, MacIntosh, and Strevens’ (1964) groundbreaking work” (Hyland, 2007, p. 391).

And yet, in the late ‘40s and throughout the ‘50s, Dr. Cartier was applying many of today’s ESP principles (needs analysis, ethnography, discourse analysis) to his work. He leans over his plate of spaghetti and meatballs and says, “Back then, people who didn’t speak English in universities weren’t helped—their instructors didn’t know how to help them.” He tells me the following story to illustrate his point.

In the mid-’50s, Dr. Cartier was sent by the Air Force to the University of Puerto Rico to address an issue. (He was a fixer. If there was a language problem anywhere in the world on a base, they sent him to figure out what it was and address it.) Entire classes were graduating from the Reprinted with permission from TESOL Connections, copyright 2018, by TESOL International Association, Inc. All rights reserved.

From Phonetics to Sci Fi: Dr. Francis Cartier

Reserve Officers’ Training Corps (ROTC) unable to speak comprehensible English. The instructors had been letting the students speak Spanish in class and then they had just lumped all of these graduates into Spanish-speaking units in the Air Force, but this was less than desirable and not optimal for communication. “They could read English but they couldn’t speak—it was all phonetics!” he said (a little gleefully). Phonetics is something Dr. Cartier has plenty of experience in, luckily: His first textbook was titled The Phonetic Alphabet, he considers himself a phonetician, and even his past training to become a stage actor at the University of Southern California would come in handy (hours of practicing various accents in front of a mirror, deliberate noticing of pronunciation). He conducted research on technical Air Force terms (wing, propeller, pilot) and on the phonetics of the local context, studying the dialect in the city and even on the university campus. He came up with a glossary of words that had to be properly pronounced for successful Air Force communication and wrote out the glossary using the International Phonetic Alphabet. The first word he put on the glossary was adjective—a purposeful challenge, because it used several sounds/phonemes that were difficult for Spanish speakers. Apparently, he was practicing in the field of ESP before it even existed. *** Dr. Cartier’s home is small and neat and crowded with little statuettes, trinkets, and mementos from his travels. There is, among many others, a small black bust from Africa, a traveler carved out of some rust-colored stone from Italy, and— what he’s most proud of—an ornate, golden container gifted to him in Thailand, reserved for those who have done something great in that country. He’s well traveled; his job with the Air Force took him around the country and the world, solving language curriculum problems wherever they arose.

The most important thing he learned from all those problems was this: “If you don’t know what the issue is, you’re just not asking the right questions.”

And when it comes time to answer the questions, Dr. Cartier has learned to take a creative approach—to curriculum problem-solving specifically and to education in general. Greatly influenced by Applied Imagination, a 1964 book

by Alex Osborn about organized creativity, Dr. Cartier believes that “training is about teaching what is known, but education is where there’s room for creativity.” He is passionate that the greatest challenge in English language education today is to insist that teaching people who need English... is not a matter of education, it’s a matter of training. They do not need an academic understanding of English. You have to ask the student what he or she wants to use the language for.

Of the several books he wrote for the Air Force, his favorite was The Air Force Staff Officer, because, after much obser-

vation, he truly got at the heart of what staff officers needed the most out of language. He realized that the most crucial thing staff officers do is make changes to policy, but that they couldn’t make the changes themselves: They only had the authority to convince their commanding officer of what changes should be made. So, Dr. Cartier focused the book on communication and creative problem-solving, which was a big change in the way officers at the time thought.

In Dr. Cartier’s home, I peruse his bookshelves, though he says he’s had to consolidate in the past few years. Books are crammed onto the bookshelves, titles ranging from Psycholinguistics to Customs and Crises in Communication and An Elizabethan Song Book to Asimov’s Guide to the Bible.

Dr. Cartier is a science fiction writer and poet as well as an educator and phonetician; he’s published in TQ, in the very first volume of the journal in 1967 (“Some Important Oddities of English Phonetics”) and later in the same issue as TESOL giants James Alatis, John Swales, and Elliot Judd (vol. 21, issue 1). In his fiction, he emphasizes that he always preferred to stick to the “hard science” science fiction, things you could research and prove or that weren’t yet refutable. His fiction writing was heavily influenced by his profession; it focuses on communication, especially when the speakers don’t come from the same place and speak the same language, and the misunderstandings that can arise— in science fiction, sometimes with disastrous or devastating results. His fiction writing, too, has influenced his career.

He’s learned that a similar principle is true for both: Whatever you’re trying to communicate, it must be clear, or it won’t be understood.

When I asked Dr. Cartier what he valued most about his lifelong membership in TESOL, he said it was the conventions. He’s presented at numerous conventions and attended too many to count. “When I go to a TESOL convention, each person I talk to has an idea I’ve never thought of before…each of them has solved problems, some of which I didn’t know existed.” Indeed, a conversation with Dr. Cartier makes the field of TESOL sound adventurous, even glamorous: It is populated with inquisitive world travelers, brave problem-solvers, and creative thinkers—with Dr. Cartier himself as concrete proof and a delightful example.

REFERENCE

Hyland, K. (2007). English for specific purposes: Some influences and impacts. In J. Cummins & C. Davison (Eds.), International handbook of English language teaching (vol. 15, pp. 391– 402). Boston, MA: Springer.

Tomiko Breland is TESOL project editor. She received her BA in English from Stanford University, her MA in writing from the Johns Hopkins University, and her certificate in TESOL from Anaheim University. In her free time, she writes and edits fiction.

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Random Samples and Standard Deviations Jeff Papa, Ph.D., and Ryan Donlan, Ed.D.

WE, LIKE YOU, have oft-enjoyed the final few moments of time spent in the Mensa Research Journal, where a quick turn of a page would invite respite in strolling through the contributions of Dr. Francis A. Cartier, who, as much to our delight brought a bit of himself in terms of his own food for thought to each issue. One might say Dr. Cartier’s poignant observations, uncommon sense, and genuine affability will live on generationally in our minds and hearts.

We plan to continue in due respect, with an intentional stream-of-consciousness perspective, including from time to time (hopefully) a relevant theme materializing in what we present. In such, we will strive to stay open to what we find and publish, a product of how we think and live, yet within the lane paved by our giant, Dr. Cartier, as reflected in our new title, “Random Samples and Standard Deviations.”

Yes, we hope to remain open (random), and within our lane (standardly referenced), as expected. ***

Standard Deviations

First, let’s deviate standardly. As this issue’s theme is Experiential Learning, we ponder how experience not only empowers us yet can humble us as well.

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There was once a young boy who wanted to learn how to sail. He finally talked his father into buying him a small sailboat to use on the lake, next to which they built a cabin. The boat was modest and marginally seaworthy, made of polystyrene with one sail just large enough to catch wind. The keel was short, and the rudder was thin and wooden.

A seaworthy vessel, proclaimed the boy.

On a day of whipping winds and blustery conditions, the boy and his father went to the lakeshore and set the boat in water. Upon settling into the vessel, the boy looked at his father with hopeful eyes, firm hand on sail—wind whipping his backside, keeping taut the line. He waited nervously, and inquisitively, for instructions.

His father asked, “Son, do you know our telephone number?”

The boy responded, “Yes, dad.”

At that, the father gave the boat a shove with his foot and off jettisoned the boy in his boat, moving quickly across the waves, the wind picking up, his vessel moving farther and farther from the dock and shoreline.

Getting far from home was easy on a lake that seemed big. Turning and returning was quite a bit more difficult,

Random Samples and Standard Deviations

as moving against the wind required one to tack, or use angles smartly to outflank the wind’s onslaught.

No textbook was referenced; this was Experiential Learning with a capital “E,” dad-style.

Granted, the boy’s experience is not classic Experiential Learning (EL) as Kolb would describe it, yet certainly it leans heavily on experience as a necessary, if not sufficient, ingredient for learning. Or, in this case, survival (said tongue in cheek).

We’ve run across some other items recently that offer a life look at the “E” in Kolb’s “EL” combination, and we’ll share.

Consider any given trip to the ski slope, where we might find our optimal glide both in form and speed about twothirds of the way through the day, yet with an ill-timed glance left or right (e.g., in seeing someone we wish to impress as we pass), might we get a bit too far out over our skis at times?

Considering such as a springboard to further thought, and with a risk of mixed metaphor, might we at times get too fat on Experiential Learning, or in touting its advantages to those more in the keeping of books?

Let us consider those who bloviate...

“We all learn from experience, and by engaging in the [Kolb] four-phase learning cycle, we can learn almost any— D. Christopher Kayes thing.”

At times, they may thereafter experience due humility...

“Every well-born child is originally geniused, but is swiftly degenuised by unwitting humans and/or physically unfavorable environmental factors.” —Buckminster Fuller

We find that Experiential Learning transcends formal classrooms; it can be applied to daily interactions. To life.

We’re never short on its lesson plan, or its pop quiz, as we cycle.

Many of us build wisdom as we look at an old condition—humanity. Reminds us of the lyrics—whether credited to Bill Staines; Peter, Paul, and Mary; Celtic Thunder, or others—sung roughly, “All God’s creatures/critters have a place in the Choir; some sing low [and] some sing higher . . .”

As the MRJ audience is a wise group, we’ll chat first of the opposite for sake of heterogeneity, of those who society often considers by contrast, unwise. Our low-hanging examples are those with low formal education, or those who have foregone conventional offers for gainful employment or civic contribution.

Life’s lesson plan of Experiential Learning might invite a certain compassion within us to say, “These folks are possibly wiser than we give them credit for—living their lives with what they have, in the best way they know how. And in this, might they be in actuality happier than the rest of us?” Not sure, but consider this...

The Competency Continuum. We saw it published by Collignon, Legrand, and Parr, where the following is depicted, in terms of how we navigate life and learning (in doing so, read from the left to the right, as the Continuum is typically pictured as a hierarchy from the bottom up): Unconscious Incompetence . . . [then] Conscious Incompetence . . . [then] Conscious Competence . . . [then] Unconscious Competence . . . [then] Conscious Unconscious Competence [at the top, or pinnacle].

When learning new skills experientially—one might personally or professionally—we often start with the state of being Unconsciously Incompetent. Yet in the case of those we referred to just prior, isn’t this really a blissful place? After all, if we’re not conscious of how bad we are at something (whether at a skill we are supposed to have, or in general intelligence in life), we’re pretty much content, as is. Some might call us, “Happy Idiots.”

Where the rub occurs is when we have that “Aha! Moment”—when we realize how incredibly untalented (or awful) we are at something, how shortsighted our wisdom/ intelligence might be, or how difficult it will be to become good at something we’re not. That is Conscious Incompetence at its finest, and this sometimes can sting, when we realize.

Of course, as we ascend the Continuum, we go to a place where we can be good at something most of the time with attention, to doing something that appears to be effortless, then at the apex, to being able to discern how we are able to do things as if through cerebral muscle memory and then teach others to ascend the continuum as well.

This is from Conscious Competence all the way through Conscious Unconscious Competence.

All this is really to say that we might marry our wisdom with some compassionate humility, as we judge those who are not judging themselves by the same set of guidelines, either by choice, interest, or aptitude.

Experiential Learning has taught us that those who think they are at the upper end (or right end) of the Competency Continuum, and thus gifted in a broadscale way, may not be. Depends on the delimitation, really. Many are simply, yet sadly, repeating the mantra until they, themselves, believe it. Note this supposition is in good company: “The ability to speak does not make you intelligent.”

—Qui-Gon Jinn “The fundamental cause of the trouble is that in the modern world the stupid are cocksure while the intelligent are full of doubt.”

— Bertrand Russell

Experience teaches us that.

Experience can also teach us that how we define “having it,” meaning intelligence or wisdom, may need to be rethought.

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Random Samples and Standard Deviations

What if those who are truly intelligent possessed—as, admittedly, the strangest of outliers seem to do—a performance-enhancing ingredient for their brain smarts, via nature or nurture, yet ALSO a related yet different supplement that had the collateral damage of providing a bit of strange world navigation to the mixture. We have found some who might agree, such as: “No great mind has ever existed without a touch of madness.”

— Aristotle “The distance between insanity and genius is measured only by success.” — Bruce Feirstein, a line from character Elliot Carver in the James Bond movie Tomorrow Never Dies “There is a fine line between genius and insanity. I have erased that line.”

— Oscar Levant “There is in every madman a misunderstood genius whose idea, shining in his head, frightened people, and for whom delirium was the only solution to the strangulation that life had prepared for him.” — Antonin Artaud

Or as wisdom might invite, we can choose to understand, as more reasoned heads might, that we can all work to get along and accomplish great things, despite initial differences, first impressions, or even the occasional insult, with a belief that if we put smart people together in the same room, quite often, all can be good ! Note the Mensaworthy (by definition) exchange: “Is that the Hansard that you are reading, young man?” asked Roland Berrill “Obviously,” replied Lancelot Lionel Ware. *** Let’s turn from Experiential Learning’s influence on human life to Experiential Learning’s influence on organizational life. What can Experiential Learning provide in terms of organizational health and wellness, or in explanation of the organizational culture within?

Today’s workforce is diverse. Some might say that the workforce that we envision and interview isn’t necessarily the workforce that shows up on the job. Oftentimes, this is because we project our own values as hiring officials when offering the transaction of employment. Unintentionally, we do not realize that until we experience our new colleagues, we might not understand what they need, where they are coming from, and how they may best contribute to what we’re doing organizationally.

Only our own Experiential Learning can provide us this understanding, might we say?

What we may find is that our new employees are experiencing dissonance between the selves they personally know themselves to be and the role they are being asked to assume organizationally. While this may be navigable at first, over time, necessitating their code-switching will

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result in their own dissatisfaction, lost productivity, challenged professional relationships, and possibly even difficulties in retention. What might we do?

Providing them their own Experiential Learning may help.

Have you heard of counterspaces?

Counterspace comes out of studies of student affairs in institutions of higher education. Micere Keels in the book Campus Counterspaces: Black and Latinx Students’ Search for Community at Historically White Universities, describes counterspaces as “. . . safe spaces that simultaneously validate and critique one’s interconnected self and group identity—that would enable radical growth. Radical growth can be understood as the development of ideas and narratives that challenge dominant representations of and notions of their marginalized identities” (p. 2).

Stick with us here ... a connection is sneaking up, we hope ...

Providing counterspace as an employer is akin to providing space and time in an organization’s workday for those who are new and trying to figure out their workplace identities to be with others who are doing likewise in a way that forges relationships, a sense of being, and kinship. It’s not a stretch to say that all this takes place in the context of learning from each other, quintessentially an Experiential Learning journey, held in-house.

It’s fascinating that Kolb’s theories can cast such a wide umbrella, marry themselves with others, even some that are forced-fitted, as we have tried, whether sociologically or even anthropologically, in terms of an organization’s culture. Imagine for a second the toxic organizational culture, where glimmering hopes of subcultures are provided time and space for their own growth and development through Experiential Learning in their own counterspaces.

Could goodness become the dominant influence? Could EL empower? *** Ok ... enough of that experiential levity ... let’s get random.

Random Samples

■ A recent study, titled “Behavioral and Neuronal Representation of Numerosity Zero in the Crow,” published in the Journal of Neuroscience, “suggests that the conception of the empty set as a cognitive precursor of a zero-like number concept is not an exclusive property of the cerebral cortex of primates.” This study purports to show “that crows can grasp the empty set as a null numerical quantity that is mentally represented next to number one.”

■ Buckminster Fuller’s grave marker says “CALL ME TRIMTAB”; during World War II, Fuller was asked by the US Navy to find a solution to the difficulty arising from

Random Samples and Standard Deviations

the great power needed to turn larger and larger rudders.

Fuller’s solution, the Trimtab, was a small piece of metal attached to the rudder, which when forced into the path of oncoming water, creates pressure that assists the much larger rudder in making its turn. Fuller believed that, in a similar way, individuals can do unique things and create unique solutions against the grain of prevalent thought and change the course of society.

■ In the book How to Create a Mind: The Secret of Human Thought Revealed, Ray Kurzweil examines the process of reverse-engineering the human brain, how the human mind and consciousness arise from the brain’s structure and function. Writing in 2013, Kurzweil predicted that inexpensive home computers would have similar capabilities as the human brain by 2029.

■ A 2020 study titled, “Human Intelligence Just Got Less Mysterious” looks at “pattern separation” in the hippocampus—the idea that memories are stored in the hippocampus by separate neuron groupings in order to avoid confusion and mixing. This study claims that while this phenomenon has been well-documented in other species, it has not been demonstrated in humans. Using new methods, the study finds that the human brain stores this information differently—storing all memory in the same group of neurons, rather than storing discrete memories only within their own context. The authors believe that this may explain the human ability to think in the abstract, and to imagine creative solutions.

■ New particle discovery that’s pretty cool to conceive: Quantamagazine, in a Condensed Matter Physics article titled “The ‘Weirdest’ Matter, Made of Partial Particles, Defies Description,” describes a new state of hypothetical matter, the fracton, that has the world of physicists in a tizzy. It appears that they could be interesting little buggers, with as one possibility their microscopic features continuing to exist in all scales. To envision how this might differentiate them from current knowledge of physics, consider how typically subatomic particles smooth themselves out in appearance as they comprise larger objects, such as a table, chair, or even our human bodies. We don’t continue to see electrons spinning around, in other words.

Well, these guys behave differently, or that is what is posited hypothetically.

■ “We must recognize that we value the upside of our preferred learning style so much that we overtolerate its downside. We tolerate the downside of our preferred learning style because we fear the downsides of other styles.”

—Kay Peterson and David Kolb

■ Nearly 30 years ago in the Winter 1992 edition of Contemporary Education, Dr. Robert Estabrook suggested using Constellation Building in leadership. He noted as stars form constellations in the night sky—some twinkling more brightly than others—leaders might seek guidance from various theorists as points of knowledge, as their discoveries can inform what leaders do, or do next. Estabrook wrote, “No single star is sufficiently intense to bring light to comprehensive darkness” (p. 91). Pondering Estabrook’s wisdom, “The need for constellations proceeds at a brisk rate...” (p. 92), we suggest as one leads from different vantage points, new arrays will catch one’s glance, if looked upon with intelligence.

■ Do you know of a great teacher who could use a booster shot of brain science application in the classroom? Just found one of the better reads titled in “Neuroscience of Learning,” Chapter 2 of Dale Schunk’s Learning Theories: An Educational Perspective, Eighth Edition, Pearson 2020. A quick read: scientific, research-based, practical, and succinct. A great Sunday afternoon read for anyone’s favorite teacher, just before students return to class on any given Monday.

MENSA FOUNDATION INTELLECTUAL BENEFITS TO SOCIETY AWARD

Honoring the application of a Mensan’s intellectual abilities that resulted in a tangible benefit to society.

F O U N D AT I O N Nominations due by March 1.

Apply at MensaFoundation.org/IntellectualBenefits Volume 52, Issue 3 • 99

2021 Mensa Foundation

Award Recipients Mensa Foundation Prize Dr. Danielle Posthuma Laura Joyner Award Literacy Now of Houston Lifetime Achievement Award Dr. Joseph S. Renzulli Distinguished Teacher Award Kristina Tons Gifted Education Fellowship (Doctoral) Michelle Falanga Fabio Andres Parra-Martinez Gifted Education Fellowship (Non-doctoral) Katie Lee Awards for Excellence in Research (Senior Division) Jennifer Riedl Cross Tracy L. Cross David Lubinski Kate Snyder Awards for Excellence in Research (Junior Division) Lisa Bardach Brian Bernstein Darya L. Zabelina

Mensa Foundation Prize

For the best scientific discovery in the field of intelligence or creativity Statistical geneticist Dr. Danielle Posthuma of the Netherlands has been awarded the third Mensa Foundation Prize for her research directly identifying, for the first time, hundreds of human genes highly correlated to variations in intelligence.

“Genetic science and engineering is currently the hottest topic in biology — witness its impact on Covid-19,” Prize Committee Chair Dr. Harry Ringerm-

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acher said. “Dr. Posthuma’s studies of genetic correlation with intelligence are the first to succeed in identifying specific genes within the human genome. Her credentials, visibility in her field, and publications were also excellent.”

As head of the Department of Complex Trait Genetics at the VU University Amsterdam and Amsterdam University Medical Centre, Dr. Posthuma leads a group of 30 researchers from diverse fields, including statistics, stem cell biology, and bioinformatics. She has led two large-scale genetic discovery studies into intelligence. The first, whose results were published in 2017, led to the discovery of 52 genes linked to intelligence. A year later, in an even larger study of more than 200,000 people, Dr. Posthuma was able to identify another 939 genes associated with intelligence.

She is the lead author on innovative statistical tools such as MAGMA (for gene-set analyses) and FUMA (for postgenome-wide association studies annotation), which she has also used on largescale studies for Alzheimer’s disease, insomnia, and neuroticism.

“Intelligence is one of the most highly investigated traits in psychology and also one of the most heritable traits in humans,” Dr. Posthuma said. “Heritability estimates range from 40 percent in childhood up to 80 percent in adulthood.

Despite these high estimates of heritability, the actual genes have long remained elusive. Initial large-scale genetic discovery studies were mostly underpowered but did show that intelligence is highly polygenic and influenced by many genetic variants each of small effect.”

Dr. Posthuma estimates that the current genetic results explain up to about 10 percent of heritable traits related to intelligence, with future stud-

ies expected to expand the knowledge even further.

“I’ve always been intrigued to know why it’s so easy for some people to learn something, to study, and why it’s much more difficult for other people,” Dr. Posthuma said. “I would really like to understand, what is the underlying mechanism? […] So it’s like with other complex traits; it’s still something that we have to sort out. And so that requires a lot of biological knowledge — connecting the dots between the different genes, sorting out what these genes are doing in a human cell and how they connect to each other or how they form protein complexes. And that’s actually work that’s still ongoing, not only in our lab but also in other labs around the world.”

The prestigious Mensa Foundation Prize, which is awarded biennially and includes a $10,000 prize, is endowed by the estate of Kenneth Douglas Thomson.

Laura Joyner Award For outstanding work, theoretical or applied, in education, literacy, or work with the gifted or identifying threats to or preventing the loss of intelligence Literacy Now of Houston is the recipient of the 2021 Laura Joyner Award for outstanding work in supporting human intelligence in the area of literacy development. Executive Director Jacque Daughtry received the honor on behalf of the 15-year-old nonprofit organization at the 2021 World Mensa Gathering in Houston.

Literacy, a marker of general human intelligence, impacts our species in diverse ways: It’s foundational for early learning experiences and protective of cognitive functioning later in life, ameliorates systemic inequities, promotes cultural and economic development — and who doesn’t love a good story?

Indeed, some of our uniquely human intelligence is grounded in our species’ capacity for comprehending, responding to, and constructing narratives.

Literacy serves us in all areas of our lives, and those with low literacy skills face a cascade of obstacles across their lifespan. “Forty-one percent of our students are coming to kindergarten without the skills they need to learn to read,” Daughtry reports. “There are studies upon studies that show that if your child is not a proficient reader by the end of third grade, they are four times more likely to not graduate from high school.”

Daughtry also highlights the correlation between illiteracy and incarceration, with 85 percent of youth in Houston’s juvenile justice programs being functionally illiterate and 70 percent of Texas’ adult prison population reading at a fourthgrade level.

Founded to address the significant disadvantages children from low-income families face, Literacy Now bridges an impasse between public school services and traditionally underserved families through programming that includes small-group reading interventions, afterschool skills-building opportunities, family literacy outreach events, reading readiness classes for parents and toddlers, and more. The organization’s partnerships and programs instill an appreciation of reading as a lifelong habit, beginning as early as infancy and continuing through high school, for more than 2,000 Houston-area children annually.

“I truly appreciate the opportunity to shine a light on the monumental challenges faced by those struggling with illiteracy and the critical role early intervention plays in eradicating illiteracy and a lifetime of negative outcomes,” Daughtry said.

Lifetime Achievement Award

Presented every other year in recognition of a lifetime of contributions to the field of intelligence and related subjects For more than 40 years, the research and advocacy of Dr. Joseph S. Renzulli have reverberated across classrooms nationwide, revolutionizing curriculum development, teaching techniques, and learning models. With a

focus on the identification and development of creativity and giftedness in young people, his organizational models and curricular strategies have resulted in numerous pedagogical breakthroughs.

Positing that creativity is inextricably linked with giftedness and “viewing giftedness as a displayed behavior rather than a possessed trait,” Dr. Renzulli’s efforts have for decades led to the development of new strategies to identify students for participation in gifted and talented programs. His impact has extended through his advocacy, emphasizing the need to apply the pedagogy and strategies common in gifted education to improve learning environments for all students.

His 1978 publication in Phi Delta Kappan, “What Makes Giftedness?

Reexamining a Definition,” would “blaze the trail for what is now a hallmark of gifted education, talent development,” according to Dr. Melissa Mitchell. Later, his groundbreaking work on The Three Ring Conception of Giftedness, the Entrenchment Model, and curriculum compacting and differentiation would all be viewed as pioneering education efforts.

“Dr. Renzulli’s lifetime of pioneering research has led to substantial, positive changes in the theory and practice of pedagogy for all,” Mensa Foundation President Charlie Steinhice said.

“But what impresses me the most is his dedication to putting those ideas into action, especially for low-income students with high potential.”

Dr. Renzulli has been recognized with numerous educational and research accolades. He’s the recipient of three Mensa Foundation Awards for Excellence in Research (2003, 2013, and 2019), has been named one of the 25 most influential psychologists in the world by the American Psychological Association, and was honored in 2009 with the Harold W. McGraw, Jr. Award for Innovation in Education — one of the most prestigious honors in the field.

Dr. Renzulli is professor of educational psychology at the University of Connecticut and has served as

the director of the National Research Center on the Gifted and Talented and as a consultant to the White House Task Force on Education of the Gifted and Talented. A founding director of the University of Connecticut’s Neag Center for Gifted Education and Talent Development, the center was renamed the Renzulli Center for Creativity, Gifted Education, and Talent Development in 2016 in his honor.

Distinguished Teacher Award

Recognizing a teacher, professor, or instructor at any educational level who has had an especially positive influence on the education or life of a Mensan “I am a fifth-grade girl, but my teacher has empowered me to believe I ‘can do’ science, that I am good at it, and that I might just do something important with science in my future.”

Those are the words of Mensan Molly Maguire, words that would be rewarding for any teacher to hear but carry extra meaning for Kristina Tons, this year’s Distinguished Teacher Award winner.

Tons, an educator for two decades, teaches science to fourth- and fifthgrade students at St. Matthew School in Franklin, Tenn. In the essay nominating her teacher, Molly said she dreaded science but noted how that changed in fourth grade because of Tons. “You can tell every day that this teacher really does love science and loves teaching fourth and fifth graders to love science too,” Molly wrote.

“Young children love to ask questions, and they are naturally curious about the world,” Tons said. “I try to engage my students with handson activities so they can explore and experience science firsthand. Not all children will become inventors or engineers someday, but I believe that all children need to be able to think scientifically, work with others, problem-solve, know it is OK to make mistakes, and never give up!”

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Tons “turns her passion for teaching science into our passion for learning science,” Molly said. “She really pays attention to everyone’s learning style and accommodates what all of her students need to learn properly.”

“It is an absolute honor to receive this award and know I have touched the life of one of my students,” Tons said. “It is truly a gift when I see science come to life for my students. It has always been my goal as a teacher to inspire my students by creating fun and meaningful lessons. I hope to instill a lifelong love of learning for the students in my classroom.”

Gifted Education Fellowship (Doctoral)

To assist outstanding educators in acquiring a degree in gifted education or a closely related field As a Teacher Resource Specialist for Gifted and Talented in the West Wi n d s o r - Pl a i n s b o ro (New Jersey) school district and an adjunct professor, Michelle Falanga advocates for equitable practices in gifted education and works with students and their teachers, facilitating programming and providing support. Falanga is an active volunteer with several statewide groups focused on gifted education and serves on the board of the New Jersey Association for Gifted Children.

“My goal has been and always will be to shine a light on their human potential and elevate our students’ voices, not just within the classroom but as invaluable members of our everevolving global society,” Falanga said.

“Over the years this work has become more than just a professional objective; it has become a mindset communicated through my words and actions.”

Falanga received a master’s in educational psychology with a focus in gifted education at the University of Connecticut and a graduate certificate in gifted education from Rutgers University. She is currently completing

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her doctoral studies at Rider University, with a focus on the intersectionality of educational professionals trained to work with gifted learners and the execution of appropriate programming to meet their unique cognitive and affective needs.

“Gifted and talented education is in desperate need for creative, synthesizing minds to fully immerse themselves.

Whether that be by leveraging patterns, relationships, and connections or to develop and advocate for shared visions of equitable services across community lines, a focus which has been woven through my upcoming dissertation process,” Falanga said.

Falanga’s accomplishments include partnering with colleagues to develop an advocacy coalition pursuing the establishment of both undergraduatelevel coursework and a graduate-level endorsement in gifted education for the State of New Jersey, and she was a member of the team that received the National Association for Gifted Children 2020 David Belin Advocacy Award for its work championing gifted education in New Jersey.

First awarded in 2019, the Gifted Education Fellowship provides $5,000 per year and is renewable for master’s or non-doctoral students.

Gifted Education Fellowship (Doctoral) Fabio Andres ParraMartinez is a Colombian doctoral candidate in gifted, creative, and talented studies at Purdue University. “My goal and involvement in teaching, leadership, and research is advocating for and supporting gifted youth from minoritized social groups,” Parra-Martinez said. “My doctoral research focuses on a wide scope of interests such as identity, motivation, teacher preparation, and policy development in gifted education, in the U.S. and overseas.”

Parra-Martinez received his bachelor’s degree with honors in English

philology from the National University of Colombia, where he also was an English and Spanish academic writing instructor. He completed his undergraduate thesis at the Gifted Education Research and Resource Institute (GERI) at Purdue — an experience, he said, that “opened my eyes to the value of gifted education to enhance the progress of people and society” and that led to him joining the doctoral program.

Chair-elect of the GLBTQ network at the National Association for Gifted Children, Parra-Martinez advocates for the inclusion of gifted LGBTQ+ and gender-diverse youth. His research interests are the social-emotional development of gifted children, identity development in teachers of gifted children, wisdom, and educational policy.

He has served as dorm life coordinator of the GERI Summer Residential Camp for gifted children and has presented workshops for local teachers on the socioemotional development of gifted learners.

“My research resonates with Mensa’s mission of identifying and supporting gifted youth around the globe,” ParraMartinez said. “For my preliminary examination, I used a systematic review approach to inform the current state of gifted education policies in Colombia. This project was the starting point in a series of ongoing collaborations that include validation of the HOPE scale (Gentry et al.) to the Colombian context to identify talented youth from diverse backgrounds, research on Colombian teachers’ perceptions of gifted learners, and motivation of highability college learners.”

Gifted Education Fellowship (Non-doctoral)

Katie Lee, a STEM educator of gifted math students in Washington, is a passionate advocate and community builder for gifted education who has taught and imple-

mented a variety of integrated math curricula in four schools and three countries.

“Whether I am teaching at a small school like Meadow Green Academy with an intimate community or a prestigious school like Lakeside School with alumni including Bill Gates and Paul Allen, my constant joy has been discovering and fostering students with exceptional aptitude for learning,” Lee said. “This passion and interest in gifted education also became more personal recently as my daughter joined the Highly Capable Magnet Program in Washington public schools.”

Lee is currently pursuing a master’s in gifted education from Johns Hopkins University. She holds bachelor’s degrees in science (actuarial math) and education, and she is an active member of the National Association for Gifted Children, the Northwest Gifted Child Association, and the Washington Association of Educators of the Talented and Gifted.

“I hope to continuously grow in the gifted education field, and I believe the Mensa Foundation Fellowship will accelerate this journey,” Lee said. “I plan to learn from the most recent research and experts in gifted education through my graduate study and apply these learnings in my community.”

That plan includes collaborating with other educators on gifted programs in local education systems to implement national standards.

Lee also wants to design an effective curriculum as a math teacher to support the development of gifted students. In addition, she would like to help increase the representation of historically underrepresented gifted student populations, including English language learner (ELL) students, students from lower-income families, students from a diverse cultural background, and twiceexceptional students.

“As a parent and teacher of gifted children,” Lee said, “I hope to expand my knowledge in gifted education and be a strong advocate in my

community. I hope to spread joy and love of learning by being both an exemplary student and an effective educator. If given the opportunity, I wish to continue fostering gifted students with the support of the Mensa Foundation.”

First awarded in 2019, the Gifted Education Fellowship provides $5,000 per year and is renewable for non-doctoral fellows for one year.

Awards For Excellence in Research Given internationally for outstanding research on intelligence, intellectual giftedness, and related fields Papers must be published in a peerreviewed journal or presented at a peer-reviewed conference. Senior investigators honored have received their degrees more than five years ago and have since been active in their fields. Junior investigators include graduate students, researchers who have earned their degrees within the past five years, and those who have previously earned degrees in other fields and entered their present field within the past five years.

Senior Division Jennifer Riedl Cross “Psychological Heterogeneity Among Honors College Students” Journal for the Education of the Gifted, June 2018 (coauthors Tracy L. Cross, Sakhavat Mammadov, Thomas J. Ward, Kristie Speirs Neumeister, and Lori Andersen) Tracy L. Cross “A Comparison of Perceptions of Barriers to Academic Success Among High-Ability Students from High- and Low-Income Groups: Exposing Poverty of a Different Kind” Gifted Child Quarterly, November 2018 (coauthors Jennifer Riedl Cross, Andrea Dawn Frazier, and Mihyeon Kim)

David Lubinski “Intellectual Precocity: What Have We Learned Since Terman?” Gifted Child Quarterly, July 2020 (coauthor Camilla P. Benbow) Kate Snyder “Interventions for Academically Underachieving Students: A Systematic Review and Meta-Analysis” Educational Research Review, November 2019 (coauthors Carlton J. Fong, Jackson Kai Painter, Caroline M. Pittard, Sebastian M. Barr, and Erika A. Patall)

Junior Division Lisa Bardach “Smart Teachers, Successful Students? A Systematic Review of the Literature on Teachers’ Cognitive Abilities and Teacher Effectiveness” Educational Research Review, June 2020 (coauthor Robert M. Klassen) Brian Bernstein “Psychological Constellations Assessed at Age 13 Predict Distinct Forms of Eminence 35 Years Later” Psychological Science, March 2019 (coauthors David Lubinski and Camilla P. Benbow) Darya L. Zabelina “Unity and Diversity of Executive Functions in Creativity” Consciousness and Cognition, February 2019 (coauthors Naomi P. Friedman and Jessica Andrews-Hanna) Visit MensaFoundation.org/awards for more information about the awards, including nominating details.

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