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Journal of Scholastic Inquiry: Special Edition

Special Edition, Volume 8, Issue 1 Fall 2017

Published by: Center for Scholastic Inquiry, LLC ISSN: 2330-6564 (online) ISSN: 2330-6556 (print)


ISSN: 2330-6564 (online) ISSN: 2330-6556 (print)

Journal of Scholastic Inquiry: Special Edition

Fall 2017

Volume 8, Issue 1

www.csiresearch.com


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Journal of Scholastic Inquiry: Special Edition The Center for Scholastic Inquiry (CSI) publishes the Journal of Scholastic Inquiry to recognize, celebrate, and highlight scholarly research, discovery, and evidence-based practice. Academic research emphasizing leading edge inquiry, distinguishing and fostering best practice, and validating promising methods will be considered for publication. Qualitative, quantitative, and mixed method study designs representing diverse philosophical frameworks and perspectives are welcome. The JOSI publishes papers that perpetuate thought-leadership and represent critical enrichment. The JOSI is a rigorously juried journal. If you are interested in publishing in the JOSI, feel free to contact our office or visit our website. Sincerely,

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JOURNAL OF SCHOLASTIC INQUIRY: Special Edition Fall 2017, Volume 8, Issue 1

Managing Editor Dr. Tanya Yerigan

Editor-in-Chief Dr. Dennis Lamb

General Editor & APA Editor Jay Meiners

EDITORIAL ADVISORY BOARD Shirley Barnes, Alabama State University Joan Berry, University of Mary Hardin-Baylor Brooke Burks, Auburn University at Montgomery Timothy Harrington, Chicago State University Michelle Beach, Southwest Minnesota State University Kenneth Goldberg, National University Linda Rae Markert, State University of New York at Oswego Lucinda Woodward, Indiana University Southeast Arina Gertseva, Washington State University Robin Davis, Claflin University

PEER REVIEWERS Marie Kraska Michelle Beach Joan Berry

Cathyann Tully Tanya McCoss Yerigan Linda Rae Markert Brooks Poole Robin Davis Betsye Robinette


TABLE OF CONTENTS Publication Agreement and Assurance of Integrity Ethical Standards in Publishing Disclaimer of Liability Research Manuscripts

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Teen Mothers Graduating from an Alternative School: A Counter Discourse to Prevailing Negative Perceptions Olivia Panganiban Modesto, Texas A&M University-Kingsville

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Effective Kindergarten Readiness: What About Collaborative Preschool Interventions? Julie A. Hentges, University of Central Missouri Nancy Montgomery, University of Central Missouri

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Using Brand Equity and Personality Metrics to Predict the 2016 U.S. Presidential Election Richard J Monahan, American Public University

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Security Price Impact of Cash Flow Estimates Versus Accounting Accruals Across Industries Ronald Stunda, Valdosta University

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“Data is Extremely Useful!” Preservice Teachers’ Growth in Literacy Assessment and Instruction Catherine M. Kelly, St. Catherine University

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Manuscript Submission Guide

105

Why Read Our Journals

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PUBLICATION AGREEMENT AND ASSURANCE OF INTEGRITY By submitting a manuscript for publication, authors confirm that the research and writing is their exclusive, original, and unpublished work. Upon acceptance of the manuscript for publication, authors grant the Center for Scholastic Inquiry, LLC (CSI) the sole and permanent right to publish the manuscript, at its option, in one of its academic research journals, on the CSI's website, in other germane, academic publications; and/or on an alternate hosting site or database. Authors retain copyright ownership of their research and writing for all other purposes. ETHICAL STANDARDS IN PUBLISHING The CSI insists on and meets the most distinguished benchmarks for publication of academic journals to foster the advancement of accurate scientific knowledge and to defend intellectual property rights. The CSI stipulates and expects that all practitioners and professionals submit original, unpublished manuscripts in accordance with its code of ethics and ethical principles of academic research and writing. DISCLAIMER OF LIABILITY The CSI does not endorse any of the ideas, concepts, and theories published within the JOSI: E. Furthermore, we accept no responsibility or liability for outcomes based upon implementation of the individual author’s ideas, concepts, or theories. Each manuscript is the copyrighted property of the author.


Teen Mothers Graduating from an Alternative School: A Counter Discourse to Prevailing Negative Perceptions Olivia Panganiban Modesto Texas A&M University-Kingsville Abstract Teen pregnancy and childbirth are important societal concerns in the United States because of the prevalence and difficulties associated with these phenomena. While the teen birth rate has decreased, the United States still has the highest number of teen childbirths among industrialized nations. Many studies support the recurring theme that due to early childbearing, the education of teen mothers is jeopardized. Negative stereotypes towards them also prevail representing the view that teen mothers are wayward, deviant, and burdensome to society. However, there is support from the literature that the majority of them maintain career and educational aspirations. With this in view, the researcher explored the educational experiences of teen mothers, particularly those who chose to enroll in and eventually graduated from an alternative public school that exclusively serves this population. A hermeneutic phenomenological approach was used in interviewing seven teen mothers who graduated from an alternative school. This qualitative method was useful in understanding subjective experiences, forming insights about individuals’ motivations and actions. The participants were selected by purposive sampling. Inductive analysis of the data indicated that attending an alternative school provided academic reengagement, structure, motivation, and a safe and caring learning environment for the participants. This study makes a contribution to the scant literature about the educational experiences of teen mothers, providing evidence that they strive to succeed and can succeed educationally when given support and access to academic services. The conclusions serve as a counter discourse to the prevailing negative perceptions towards this challenged population. Keywords: teen mothers, alternative education, hermeneutic phenomenology


Background The United States has the highest number of adolescent childbirths among industrialized nations (United Nations Statistic Division, 2015). In 2014, there were 249,078 live births to mothers ages 15-19 years or 24.2 live births per 1,000 females in this age group (Hamilton, Martin, Osterman, & Curtin, 2015). In the state of Texas, which has the second highest teen pregnancy rate, and where this study was conducted, the highest number of teen births was among Latinas, totaling to 30,257 births in 2010 (National Campaign to Prevent Teen and Unplanned Pregnancy [NCPTUP], 2013). Approximately 77% of teen pregnancies are unplanned, which means, they are unwanted or occurred “too soon,� according to a national survey of adolescents (Mosher, Jones, & Abma, 2012). This situation is a public concern because it has been documented that adolescent pregnancy increases the risk of public assistance use and lower educational attainment (Casares, Lahiff, Eskenazi, & Halpern-Felsher, 2010). Adolescent childbearing is a multisystemic problem strongly associated with behavioral, social, and environmental factors. Adolescents who are most vulnerable to early childbearing come from unstable and impoverished homes, have exhibited antisocial behavior, and have used controlled substances (Cavazos-Rehg et al., 2010; Tanner et al., 2015). Most adolescent parents are already socially disadvantaged and have faced adversities as children (Cavazos-Rehg et al., 2010). In addition, most adolescent mothers already had high levels of psychological distress even before becoming pregnant (Mollborn & Morningstar, 2009). Thus, pregnant teens and adolescent mothers are among the most challenged population in American society today. The challenges adolescent mothers face are multifaceted, one of which is their educational attainment. A student who becomes pregnant is at-risk of educational failure. In a study that used national survey data to examine high school diploma attainment among women who were teen mothers, results indicated that only 51% who had teen births earned a high school diploma by the age of 22, compared to 89% who did not have teen births (Perper, Peterson, & Manlove, 2010). Empirical evidence suggests that having a child as a teenager reduces the probability of attaining a high school education by five to ten percentage points and reduces income as a young adult by $1,000 to $ 3,000 per year (Fletcher & Wolfe, 2009). These studies


support a recurring theme in the literature: Due to early childbearing, the education of adolescent mothers is jeopardized. Literature Review Despite the disadvantageous conditions that beset adolescent mothers, the majority maintain career and educational aspirations. The admission of pregnant and parenting students into the public school system began in the early 1960s (Scholl, 2007). By the 1990s, attendance of pregnant students in school became socially acceptable (Nelson, 2011). Historically, U.S. public schools were geared towards serving unmarried adolescents; adolescents who did not conform to the accepted norms of conduct, including adolescent pregnancy and motherhood, were forbidden to attend public schools (Atkyns, 1968). However, today, access of pregnant and parenting students to public education is guaranteed by law. Schools receiving federal money cannot discriminate in their admissions policies on the basis of marital or parental status as guaranteed by the Title IX of the Education Amendments of 1972 (106.40.b): A recipient [of federal funding] shall not discriminate against any student, or exclude any student from its education program or activity, including any class or extracurricular activity, on the basis of such student's pregnancy, childbirth, false pregnancy, termination of pregnancy or recovery therefrom, unless the student requests voluntarily to participate in a separate portion of the program or activity of the recipient. (National Archives and Records Administration, 2000, p. 52872) While Title IX protects adolescent mothers against discrimination and exclusion from schools no longer occurs, more subtle forms of discrimination are committed against this population, and bias is not prevented (Gough, 2011). For example, pregnant and parenting students have been excluded from extracurricular and honors programs. Some have been forced to attend alternative programs to make them disappear from regular schools (Ducker, 2007). Moreover, inconsiderate policies pertaining to attendance occur, such as the refusal of an excused absence for a sick child (Gough, 2011). In reality, pregnant teens and adolescent mothers are stigmatized, which limits their educational opportunities (Rogers, 2010; Whiteley & Kilmayer, 2008).


There is also a propensity for viewing adolescent mothers as deviant, wayward, and burdensome to society (Pillow, 2006; Fletcher & Wolfe, 2009). Teen parenting is constructed in research and public discourse as a social problem with disadvantageous outcomes for both the teen mother and her child (Hindin-Miller, 2012). Rarely is adolescent mothering seen as (a) an opportunity to exhibit resilience (Easterbrooks, Chaudhuri, Bartlett, & Copeman, 2011), (b) a transformative experience that gives the adolescent mother a chance for personal growth and the renewal of family relationships (Spear, 2004), or (c) a source of motivation to aspire for higher education (Phipps, Salak, Nunes, & Rosengard, 2011). Furthermore, there has been little academic discussion about the education of this population. Pillow (2006) analyzed this silence as coming from three discourses or beliefs surrounding adolescent pregnancy: (a) adolescent pregnancy as a disease with the female student as a corruptor of moral ideals; (b) education as a responsibility, not as a benefit, of the adolescent mother to reform her waywardness; and (c) pregnancy as a temporary condition, which reinforces the idea that adolescent mothers need no intervention or support. The silence surrounding the education of adolescent mothers reinforces their marginalization. Without understanding the experiences of adolescent mothers as individual students in schools, negative stereotypes may endure and serve as obstacles in addressing their needs. Attending alternative schools is one avenue by which adolescent mothers can succeed, but school districts battle with negative stigmas of alternative schools as “dumping grounds or warehouses for at-risk students� (Herrington, 2012, p. 2). None of the research on alternative schools highlight any success achieved by teen mothers. This study fills a gap in the literature by presenting the meaning of this phenomenon. Methodology The focus of this research was the participants’ viewpoints on the shared phenomenon of attending an alternative high school as teen mothers. As a researcher with a constructivist view, I was interested about their individual realities. For this reason, I followed a hermeneutic phenomenological approach.


The hermeneutic approach begins with the notion that human experiences are imbued with meaning, gained from socio-historical contexts and founded on experience. A hermeneutic phenomenological researcher assumes that people function within the world of language and social relationships (Finlay, 2009). The researcher and participants are co-constructors of meanings, where “inter-subjective understanding” (Standing, 2009, p. 21) about lived experiences may be gained. This means that the researcher and the participants may come to an agreement of the meaning of the characteristics or essence of the phenomenon of interest. The researcher involves the participants to reflect on the meaning of their experiences. In this process, the researcher is involved in what is termed as the “hermeneutic circle” (Guignon, 2012, p. 98). It begins with what the researcher understands about the phenomenon, uses this understanding to interpret the phenomenon and, on the basis of this interpretation, goes back to his or her original understanding to revise it. The study took place at a campus where I used to teach, New Horizon Alternative School (NHAS), a pseudonym, and an alternative education program recognized by the Texas Education Agency (TEA). I taught English language arts in NHAS for 11 years. I was closely in touch with the phenomenon under study. I knew enough about the workings of an alternative school, which enabled me to ask relevant interview questions. I was curious to study the uniqueness of this student population and wondered about their motivations and feelings as students striving to finish high school while also fulfilling their roles as young mothers. I also conducted this study because of the limited available research about students and graduates of alternative schools for pregnant and female parenting students. The average number of students in NHAS from 2010 to 2013 was 130. Ninety-nine percent of the student population is Hispanic, and 96% are identified as economically disadvantaged. Enrollment in this school is transitional and completely voluntary. Pregnant and parenting students in this school voluntarily attend classes as an alternative to attending the schools zoned to their homes to access self-paced, individualized instruction and home instruction during their period of recovery from childbirth. Certified teachers and home instructors make up the faculty of NHAS. Home instructors are certified teachers who do not hold classes in the school building but go to students’ homes to deliver instruction during the students’ period of recovery from childbirth.


I used a purposive and homogeneous method of sampling because the participants were made up of individuals who shared common characteristics. The criteria for selecting the participants included mothers, 18 years and above, attended NHAS for at least one semester, and graduated from NHAS from school year 2011- 2012. The names of the qualified participants were randomly selected. According to Starks and Trinidad (2007), the usual sample size for phenomenological research is between one to 10 persons. This is because an individual can generate hundreds of ideas and thousands of words, so large samples are not needed to produce large amounts of data (Starks & Trinidad, 2007). For this study, seven adolescent mothers participated. I collected data by conducting a one-time interview session with each participant. The recorded interviews were transcribed verbatim and pseudonyms were used to maintain anonymity. In addition, I remained open and attentive to the participants’ words, gestures, and even silence. After each interview session, I recorded my observations and reflections in my research journal. I analyzed the data by carefully reading the interview transcripts several times to get a sense of the whole interview and to determine texts relevant to my research topic. The next step was in-text coding, which is the labeling of meaningful sections of the interview transcript using category names (Van Manen, 1990; Lodico, Spaulding, & Voegtle, 2010). Both the language of the participants and terms that describe the information guided the development of the codes. I brought together the data with the same code names into separate computer files. Then, I summarized the content of each file. Each summary was examined to generate initial themes. The themes represented what was learned from the study. With the repeating items grouped, I looked for linkages between themes to form a rich, descriptive narrative of the participant’s perspective about the research topic. Thus, the analysis went beyond breaking down the collected data into segments, but was an iterative process of abstracting meaning from the data. This process led to the product of hermeneutic phenomenological research: a descriptive text which explains the phenomenon.


Results/Findings Seven participants were interviewed, with the following pseudonyms and ages at the time of the interview: Bianca (19 years old), Denise (20), Nora (19), Cynthia (20), Karen (20), Jasmin (19), and Crystal (18). Three themes were derived from the data analysis: getting help, having the opportunity to graduate early, and learning in a supportive environment. To explain the themes, I used the exact words of the participants. Theme 1: Getting Help The alternative school provided resources that supported the adolescent mothers’ education. These resources were: (a) home instruction, (b) onsite daycare, (c) transportation for both the student and her child, and (d) material incentives. Home instruction is a mode of learning where a certified teacher goes to the students’ home while recovering from childbirth. Bianca recounted her experience of home instruction as a mode of learning where she felt comfortable and made her focused on her assignments. She could go to the restroom anytime and eat while doing her schoolwork. The home instructor went to her house twice a week for two hours. The home instructor brought materials, like modules and textbooks, for Bianca’s use. For Bianca, doing home instruction was a way to advance in acquiring the credits she needed to graduate. In fact, she completed credits for three subjects while she was on home instruction for one month. Another specialized resource that NHAS has is an onsite daycare for its parenting students. The provision of a daycare gives an adolescent mother a compelling reason to continue her education and denies her an excuse to drop out. Denise confirmed this idea when she stated that if students “have no one to take care of their child, there’s daycare…they wouldn’t have to drop out. They could just go to Horizon.” The participants, even those who did not bring their babies to the daycare, indicated that the daycare was an important support in completing their high school education. Two students, Nora and Crystal, emphasized that without the daycare, they would not be able to finish their high school degrees because no one was available to care for their children while they attended school.


The daycare teachers taught “listening and learning skills,” according to Nora. The babies also have a schedule for napping and playing inside or outside the facility. If the adolescent mothers were breastfeeding, or if the babies needed medication, there were specific times for mothers to go into the daycare and attend to these needs. Crystal mentioned that during the school year, mothers and babies also participated in some special celebrations. For example, during Dr. Seuss’ birthday, the mothers went into the daycare to make little Dr. Seuss hats and to read to their babies. The adolescent mothers described their experiences of bringing their babies to the daycare as a positive experience for themselves and their babies. Nora expressed that at the time she was going to NHAS, both of her parents were working, and she did not have a job to enable her to pay for daycare. Her statements showed that she genuinely valued the daycare as an important factor that supported her diploma attainment. Some of the participants used the bus transportation for them and their children. In fact, Denise considered this resource as a major reason she chose to enroll at NHAS. When I asked her what made her decide to enroll at NHAS she responded: The transportation because I didn’t think they had transportation until I went to go to see how it was and everything, and they told me that yeah there was transportation, that they would take me, pick me up and take me back home. So, I go, ok, so I have transportation and with the baby also they would let us take the babies in the bus. Data revealed that because the alternative school has a daycare, the school also provided the means of transporting their children from their homes to the daycare via riding the school bus equipped with car seats for babies. Data also revealed that the adolescent mothers received material incentives through a point system that rewarded on-task behavior, successful test performance, perfect attendance, and early credit completion. Bianca stated that she never had to buy diapers while she was enrolled at NHAS: “After I left school, that’s when I bought my first diaper box, but during school, I never bought diapers.” She felt that the reward system was important. According to Bianca: Some students, they live in low society, and they don’t really have enough money to buy diapers, and diapers nowadays are so expensive. So, if you do good in your classes, and


they give you the points, you get the free diapers, and you won’t have to worry about your baby, not having diapers, not having wipes. Data revealed that the provision of home instruction, daycare, bus transportation for the student and her child, and material rewards supported the participants’ schooling. These resources helped them in practical ways to continue going to school and eventually finish. Theme 2: Having the Opportunity to Graduate Early All the participants identified alternative schooling as an opportunity to accelerate credit accrual and to graduate early. The participants repeatedly used phrases such as “finishing early,” “finishing faster,” “advance more,” and “progress” to signify the idea that attending NHAS was a way to finish high school earlier than their peers who were enrolled in the regular schools. This idea was also the major differentiating point in their perception of the alternative school in relation to a regular school. Jasmin explained: In a regular campus, it’s not only you. You’re with the whole class that their teaching, and everybody’s at the same pace, doing the same thing. In the alternative school, you’re at your own pace. You have to learn by yourself. They’ll help you out or whatever, but actually, you’re on your own. This self-paced mode of learning allowed students to get their credits for the courses any time during the semester. After finishing one class, they take the next class that they need. Crystal recalled, “I would finish my classes, some of them fast.” Then, she moved on to another class “as soon as [she] was done.” Jasmin was particularly proud of the situation that she “finished way before time, in April” and “had two months off.” Because they graduated, the participants developed positive feelings towards themselves. Nora described this feeling: “Now I feel a bit more positive, a little bit better, now that I have something that supports me [speaking of her high school degree]. I’m not like another pregnant girl there that just, you know? You feel better.”


Theme 3: Learning in a Supportive Environment All the participants consistently articulated that the teachers were helpful and caring. Words that participants used to describe their teachers were: “nice,” “good,” “great,” “fun,” “supportive,” “positive,” “friendly,” “persevering,” “more one on one,” and “willing to help.” The participants gave descriptions of how teachers specifically helped them in class. For example, Karen talked about how teachers “will answer all of your questions and will help you during lunch and after school.” Also, Crystal recounted that her math teacher helped her review lessons and that “she would teach different techniques to solve the problem. She’ll give you extra work to practice”. Furthermore, Denise mentioned that although learning was self-paced, “teachers help you when you don’t know the subject you’re in.” The data also pointed to the strong sense of connection between students and teachers in the alternative school. The adolescent mothers felt they have a family in the alternative school. Cynthia commented that “you can talk to a teacher, talk about your problems, and [she’ll] understand you.” This bonded relationship was depicted by Nora who stated that “teachers are really friendly, and they’re real positive, and they care about you. You’ll see a teacher in a store. They’ll say ‘hi’ to you. You feel like a family. You feel close”. Not only did participants value the teachers but also the staff and administrators. Participants emphasized that no one mistreated or looked down on them due to their pregnancy or situations they faced as teen mothers. Bianca synthesized her view of the alternative school as this: “Everyone there was really helpful… I wished I would have gone earlier from my junior year, so I could’ve start and advance more ‘cause I started in my senior year when I was like six already months pregnant.” Likewise, Karen summarized her view when I asked her if she wanted to say anything more beyond the responses to questions I asked. She emphasized, “When you go there, you feel that they will help you, and you feel that they’re helping you”. Lastly, Bianca narrated in detail a time when the principal showed the students kindness by treating them at a fast food restaurant: The principal also helps you a lot. Mr. Smith took us on a field on the old mall. They had a book convention and on our way back....He asked the bus driver if he could stop there (McDonald’s)…he bought everyone combos and ice cream.


Another important point that the data revealed was peer support. The participants’ classmates and friends in the alternative school gave them support in different ways. One way a participant experienced support from a classmate was when her classmate graduated from NHAS but continued to communicate with her by sending text messages offering help. Jasmin expressed that the students who already delivered their babies shared their experiences of childbirth and childcare to those who were still pregnant. In addition, Nora described that merely seeing the pictures of students who already graduated, posted on one of the school’s bulletin boards, made her feel good about going to the alternative school. In sum, adolescent mothers learn in the alternative school in a supportive learning environment. The support came from teachers, administrator, staff, and classmates. The faculty and staff were described as caring and helpful. Discussion The research question addressed how adolescent mothers gave meaning to their educational experiences in an alternative school. The participants viewed their alternative education as a positive experience due to their feelings of safety, security, and satisfaction with the resources that were available in the alternative school. Small class size, low teacher to student ratio, individualized instruction, daycare, home instruction during the postpartum period, bus transportation, and material rewards for academic performance contributed to the participants’ perceptions of the alternative schooling as another “opportunity” to obtain a high school diploma. The findings for the research question are consistent with previous research that indicated that pregnant and parenting students who have access to a wide range of services integrated into a stand-alone alternative school display improved academic performance. Compared to those who were not enrolled in the alternative school, the researchers found that alternative school students had higher educational aspirations, better reproductive health outcomes, higher contraceptive use, and better breast-feeding practices (Amin et al., 2006). Additionally, other researchers had previously concluded that students enroll in alternative schools in order to accelerate, graduate, and pursue postsecondary education (Flower, McDaniel, & Jolivette, 2011;


Lagana-Riordan et al., 2011). The participants attended NHAS because they were aware that if they had stayed in their regular schools, it would have been difficult to obtain their diplomas because of their status as pregnant and parenting students. In addition, a participant who stopped attending school because of the absence of childcare saw an opportunity to complete her education via the alternative school because of its daycare. The participants also highlighted the value of individualized instruction which is often the strongest source of acceleration in alternative schools. Thus, access to services not available in the regular campuses, such as childcare, transportation for the student and her child, individualized attention, and home instruction contributed to the participants’ conviction that being in the alternative school was the best route towards high school completion. The teen mothers in this study achieved their diplomas. The participants perceived NHAS as responsive to their unique needs as pregnant and parenting students. From this study, it can be posited that how a pregnant or parenting student views alternative schooling might influence her decision and motivation to continue her education through this route. If a pregnant student or adolescent mother is well-informed and understands opportunities available for her in an alternative school, she may become motivated to enroll. A pregnant student or adolescent mother who may have considered dropping out or had stopped attending school because of childcare, transportation, or academic problems might gain a feeling of hope and decide to reengage with school in knowing that there are resources and tangible help available to meet her needs in an alternative school. Given the appropriate resources, relevant instruction, and a supportive environment within the alternative school, the teen mothers exhibited a heightened engagement with schooling that enabled them to succeed. This phenomenon of teen mothers attending an alternative school serves as a counter-discourse to the common perceptions on teen mothers as a problem in society. The research literature and popular media have often portrayed the lives of teen mothers as problematic and ridden with obstacles to educational success. However, in interviewing them and hearing their voices, I saw the value of knowing their success, a notion that is contradictory to the prevailing attitudes towards them. I learned to highly respect and admire the participants as individuals who succeeded educationally despite the unique circumstances that challenged their aspirations.


In the light of the findings, I suggest two recommendations. The first recommendation is for educational leaders to reaffirm the value and contribution alternative schools may give to dropout prevention, especially among pregnant and parenting students. When educational leaders and stakeholders see the value of alternative education for pregnant and parenting students, negative feelings about attending an alternative school may be lessened. Also, the provision for funding and other forms of support may be facilitated for the benefit of the alternative schools’ students. The second recommendation is to energize efforts of informing pregnant and parenting students in the regular schools about the resources available in the alternative school. Some participants indicated that they were not aware of the services offered by the alternative school before enrolling. They did not know about the provision of home instruction, transportation, and daycare services. As a result, there was hesitation, fear, and uncertainty regarding the decision to transfer to an alternative school. If nurses, counselors, and administrators fully explain the characteristics of the alternative school and the resources available to students, a clearer and more informed decision-making process may allow pregnant or parenting students to resolve their dilemmas more quickly. As a means of extending this study, it may be interesting to conduct a longitudinal survey, specifically a trend study. A researcher might be interested in the post-secondary education of the NHAS graduates. He or she may select a sample each year from a current listing of the graduates. Although the population may change, if random selection were used to obtain the samples, the responses obtained each year could be considered representative of the graduates. Also, a comparative, mixed methods study may be conducted between adolescent mothers who are enrolled in an alternative school with those that chose to remain in their regular schools. Author Biography Olivia Panganiban Modesto, EdD is an Assistant Professor of Teacher and Bilingual Education at Texas A&M University-Kingsville. She teaches undergraduate and graduate literacy and bilingual education courses. Before joining the university, she taught at a public


school district in South Texas for 12 years. She completed her Bachelor of Secondary Education major in English at the University of Santo Tomas (Manila, Philippines) and Master of Education in ESL from the University of the Philippines. She received her doctorate degree, with a concentration in Teacher Leadership, from Walden University, Minneapolis, MN. References Amin, R. A., Browne, D. C., Ahmed, J., & Sato, T. (2006). A study of an alternative school for pregnant and/or parenting teens: Quantitative and qualitative evidence. Child and Adolescent Social Work Journal, 23(2), 172-195. doi:10.1007/s10560-0050038-1 Atkins, G. C. (1968). Trends in the retention of pregnant students. Sociology of Education, 41(1), 57-65. Casares, W. N., Lahiff, M., Eskenazi, B., & Halpern-Felsher, B. L. (2010). Unpredicted trajectories: The relationship between race/ethnicity, pregnancy during adolescence, and young women’s outcomes. Journal of Adolescent Health, 47, 143-150. doi:10.1016/j.jadohealth.2010.01.013 Cavazos-Rehg, P. A., Spitznagel, E. L., Krauss, M. J., Schootman, M., Bucholz, K. K. Cottler, L. B., & Bierut, (2010). Understanding adolescent parenthood from multisystemic perspective. Journal of Adolescent Health, 46, 525-531. Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed method approaches (3rd ed.). Thousand Oaks, CA: Sage. Ducker, B. (2007). Overcoming the hurdles: Title IX and equal educational attainment for pregnant and parenting students. Journal of Law and Education, 36(3), 445-452. Easterbrooks, M. A., Chaudhuri, J. H., Bartlett, J. D., & Copeman, A. (2011). Resilience in parenting among young mothers: Family and ecological risks and opportunities. Children and Youth Services Review,33(1), 42-50. Finlay, L. (2009). Exploring lived experience: Principles and practice of phenomenological research. International Journal of Therapy and Rehabilitation, 16(9), 474 - 481. Fletcher, J. M., & Wolfe, B. L. (2009). Education and labor market consequences of teenage childbearing. Journal of Human Resources, 44(2), 303-325.


Flower, A., McDaniel, S., & Jolivette, K. (2011). A literature review of research quality and effective practices in alternative education settings. Education and Treatment of Children, 34(4), 489-510. Gough, M. (2011). Parenting and pregnant students: An evaluation of the implementation of the “other” Title IX. Michigan Journal of Gender and Law, 17(2), 211-270. Guignon, C. (2012). Becoming a person: Hermeneutic phenomenology’s contribution. New Ideas in Psychology, 30, 97-106. Hamilton, B. E., Martin, J. A., Osterman, M. J. K., & Curtin, S. C. (2015). Births: Final data for 2014. Hyattsville, MD: National Center for Health Statistics. Retrieved September 8, 2016, from http://www.cdc.gov/nchs/data/nvsr/nvsr64/nvsr64_12.pdf. Hamilton, B. E., & Ventura, S. J. (2012). Birth rates for U. S. teenagers reach historic lows for age and ethnic groups. (National Center for Health Statistics data brief, No. 89.) Hyattsville, MD: National Center for Health Statistics. Hatch, J. A. (2002). Doing qualitative research in education settings. Albany, NY: State University of New York. Herrington, T. S. (2012). Student perceptions of the alternative school. (Doctoral dissertation). Available from ProQuest Dissertations and Theses Database. (Publication No. 3505666). Hindin-Miller, J. M. (2012). Re-storying identities: Young women's narratives of teenage parenthood and educational support. (Doctoral thesis). Retrieved from http://www.ir.canterbury.ac.nz/bitstream/handle/10092/7228/Thesisfinalcopy.pdf?sequence=1&isAllowed=y Lagana-Riordan, C. Aguilar, J. P., Franklin, C., Streeter, C. L., Kim, J. S., Tripodi, S. J., & Hopson, L. M. (2011). At risk students’ perception of traditional schools and a solution-focused public alternative school. Preventing School Failure, 55(3), 105-114. doi:10.1080/10459880903472843 Lodico, M. G, Spaulding, D. T., & Voegtle, K. H. (2010). Methods in educational research: From theory to practice (2nd ed.). Hoboken, NJ: Jossey-Bass. Mollborn, S., & Morningstar, E. (2009). Investigating the relationship between teenage childbearing and psychological distress using longitudinal evidence.


Journal of Health and Social Behavior, 50(3). 310-326. Mosher, W. D., Jones, J., & Abma, J. C. (2012). Intended and unintended births in the United States: 1982-2010. National Center for Health Statistics. Vital Health Stat (55). Retrieved September 8, 2016, from http://www.cdc.gov/nchs/data/nhsr/nhsr055.pdf. National Archives and Records Administration. (2000). Nondiscrimination on the basis of sex in education programs or activities receiving federal financial assistance; Final Common Rule. Retrieved from https://www.dol.gov/oasam/regs/fedreg/final/29_fedreg_36(final).htm National Campaign to Prevent Teen and Unplanned Pregnancy. (2013). Teen pregnancy and childbearing among Latinas. Retrieved from http://www.thenationalcampaign.org/resources/pdf/FastFacts_TPChildbearing_Latinos.p df Nelson, T. (2011). Hispanic dropouts and pregnancies in Texas public high schools (Doctoral dissertation). Available from ProQuest Dissertations and Theses Database. (Publication No. AAT 3375963) Patton, M. Q. (2002). Qualitative research and evaluation methods (3rd ed.). Thousand Oaks, CA: Sage. Perper, K., Peterson, K., & Manlove, J. (2010). Diploma attainment among teen mothers (Child Trends Publication No. 2010-01). Retrieved from http://www.childtrends.org/Files/Child_Trends2010_01_22_FS_Diploma Attainment.pdf Phipps, M. G., Salak, J. R., Nunes, A. P., & Rosengard, C. (2011). Career aspirations and pregnancy intentions in pregnant teens. Journal of Pediatric and Adolescent Gynecology,24(2), e11-5. doi: 10.1016/j.jpag.2010.12.001 Pillow, W. (2006). Teen pregnancy and education: Politics of knowledge, research and practice. Educational Policy 20(59), 59-84. doi:10.1177/0895904805285289 Rogers, A. (2010). Silence no more: A transformative transcendental phenomenological study investigating the experiences of teen mothers who go to college in the rural Southeast (Doctoral dissertation). Retrieved from ProQuest Dissertations and Theses Database.


(Publication No. AAT 3402547) Scholl, M. F. (2007). Educating adolescent parents: Proactive approaches by school leaders. Delta Kappa Gamma Bulletin, 73(3), 28-32. Spear, H. J. (2004). A follow-up case study on teenage pregnancy: “Having a baby isn’t a nightmare, but it’s really hard”. Pediatric Nursing, 30(2). 120-126. Standing, M. (2009). A new critical framework for applying hermeneutic phenomenology. Nurse Researcher, 16(4), 20-30. Starks, H., & Trinidad, S.B. (2007). Choose your method: A comparison of phenomenology, discourse analysis, and grounded theory. Qualitative Health Researcher, 17(10). 13721380. doi:10.1177/1049732307307031 Tanner, A. E., Ma, A., Roof, K. A., Rodgers, C. R., Brooks, D. N., & & Paluzzi, P. (2015). The “kaleidoscope” of factors influencing urban adolescent pregnancy in Baltimore, Maryland. Vulnerable Children and Youth Studies, 10(3), 257-269. http://dx.doi.org/10.1080/17450128.2015.1046534 United Nations Statistics Division. (2015). Demographic Yearbook 2013. New York, NY: United Nations. Retrieved September 8, 2016, from http://unstats.un.org/unsd/demographic/products/dyb/dyb2013/Table10.pdf. Van Manen, M. (1990). Researching lived experience. New York, NY: SUNY Press. Whiteley, L., & Brown, L. (2010). Clinical perspective: Understanding psychosocial complexities of pregnant and parenting teens. The Brown University Child and Adolescent Behavior Letter, 26(6). 1, 4-6. doi:10.1002/cbl.20117


Appendix The following questions were asked during the interview session with the participants: 1. Before becoming a student at New Horizon Alternative School (NHAS), what were your thoughts and feelings about it? 2. How long were you a student there? How did you find out about the school? 3. What made you decide to enroll at NHAS? 4. Now that you are a graduate of NHAS, what are your thoughts and feelings about attending NHAS? 5. If you were to describe to someone what it is like to be an adolescent mother to attend an alternative campus, what would you say? 6. Please describe a typical day for you—beginning at home, then, the time you are at school until you get back home again. 7. How did people react when they found out you were a student at NHAS? 8. How has attending NHAS affected your life? 9. What did being a student at NHAS mean to you? 10. Tell me about a time you felt you learned something from a class or from a teacher. 11. How do you compare learning or studying in a regular campus with studying at an alternative school? 12. How did you motivate yourself to finish your high school education? 13. How did you deal with the challenges of being a mother and a student at the same time? 14. Is there anything else you would like to say about your experiences at NHAS?


Effective Kindergarten Readiness: What About Collaborative Preschool Interventions? Julie A. Hentges University of Central Missouri Nancy Montgomery University of Central Missouri

Abstract The focus for this research study is to explore effective kindergarten readiness initiatives as it pertains to collaborative preschool interventions. Notably, researchers whose work is reviewed in this paper recommend that young children should be prepared for kindergarten through prekindergarten settings. Language and literacy support at an early age can influence the child’s success in kindergarten. Specifically, researchers recommended children in a pre-kindergarten literacy program should be provided with rich, hands-on learning opportunities. To begin with the organizers of this project acknowledge the importance for stakeholders who work with preschool students to engage in a collaborative service learning project. The purpose of this research was to determine the perceived impact of these intervention sessions. After the sessions, research participants reflected on the influence of the collaborative opportunities by responding to an open-ended survey. This summary will present research findings of effective interventions with a preschool partnership initiative. Keywords: Collaborative, preschool, interventions Many educators agree that early childhood intervention helps to support preschool learners. This research study began as a collaborative initiative with the University of Central Missouri undergraduate and graduate students, preschool parents, and teachers and faculty of


preschool students. This plan was created in an effort to promote literacy and language opportunities for early learners. Schonkoff and Meisels stated (2009) with the goal to promote long-term outcomes for developmental achievement, it is important to consider parents’ support for services provided to their young children. Just as important, is a strong focus to enhance parents’ understanding of children’s developmental needs (2009, p. 376). When stakeholders are included in the process to promote student learning, researchers recommend it should be done by fostering collaborative initiatives to enrich academic success for young learners (Lonigan & Shanahan, 2009). Parents are an important component in students’ success (Hara & Burke, 1998). Because of this, they are considered to be strong advocates and stakeholders for their children’s success. Flouri and Buchanan (2004) state “father involvement and mother involvement at age 7 independently predicted educational attainments by age 20” (p. 141). This is important to note pertaining to collaborative pre-school and parent partnership interventions. If parent involvement results in educational achievement, then every effort should be made to form positive relationships with parents to promote student success. Research Study Outcome Goals This study sought to accomplish the following outcome goals: (a) to promote collaborative preschool interventions, and (b) to identify effective Kindergarten readiness intervention structures. To address these outcome goals, researchers for this study identified an area of need in federally funded pre-school programs in their geographic area (Central Missouri). Through various interactions with these programs, it was determined there was little evidence of current preschool collaborative initiatives. Although each group was organized to support the early learner, there were few, if any, opportunities for these groups to work together to support kindergarten readiness. As a result of this, the researchers decided an appropriate research goal to be a collaborative initiative to identify an effective kindergarten readiness intervention structure. This study was designed to encourage adults in these young children’s lives to participate in readiness workshop events. The researchers determined it was possible to generalize the


research results to promote effective preschool experiences for young students in other geographical areas. Therefore, the research study approach was planned with that in mind. Ultimately, the focus was to provide learning opportunities that would promote kindergarten readiness in a very real and authentic way. The researchers began “with the end in mind” (Covey, 2004, p. 104). They considered, would a collaborative intervention focus provide effective kindergarten readiness opportunities? Once it was determined a valid focus, the researchers worked to gain partners in this process. The primary goal for the project was to determine effective kindergarten readiness skills through a collaborative preschool partner initiative. Opportunities to Promote Kindergarten Readiness The investigators of this study were able to secure consent to participate in the research from a local charter school, a local Head Start preschool, university students, and preschool teachers and/or faculty. The next step was to request permission to conduct the research through the University’s International Review Board (IRB). The researchers received authorization to begin. Then, they began to plan for intervention sessions. The first step in the actual research plan was to determine interested stakeholders for the study. Stakeholders Influence on Preschool Students’ Achievement Research revealed children in a pre-kindergarten literacy program should be provided with hands-on, engaging activities. These opportunities should promote rich vocabulary and language development (Gunn, Vadasy, & Smolkowski, 2011). Just as importantly, reading and writing should be addressed in the early years. Lonigan and Shanahan (2009) suggested that, ‘interventions designed to improve young children’s oral language skills have been effective “(p. 222). These early learners should have the opportunity to engage in activities, so they can begin to make connections with early learning literacy skills. Essential to an early learner’s success is his or her ability to observe and grasp an understanding of language. Vygotsky (1934/1986)


states that “the only good kind of instruction is that which marches ahead of development and leads it� (p. 188). Key stakeholders (Figure 1) were identified early and included throughout the process. In Figure 1, the key stakeholders for this Collaborative Preschool Intervention initiative are identified. Each role included here is represented in a balanced chart to represent an equally valued and important role in the study. First, it was determined preschool teachers would be very important members of the community of stakeholders. Next, preschool teachers and faculty discussed ways to support an intervention initiative. These Head Start and Charter School preschool teachers offered suggestions for other important stakeholders to include with this research study. The preschool teachers suggested it would work well to offer kindergarten readiness workshop sessions and invite parents of preschools to various locations (i.e. local library and/or preschool sites). During this communication, parents of preschoolers were recognized as valuable participants. Their input and role to support the developmental learning needs of their students is very important. At that point, they were recognized as part of the community of support for early learners. Consequently, parents of preschoolers were invited to participate in the study. Sessions were held at Head Start and Charter School Parent site meetings and Saturday Stories & Slices events at the local public library. Then, it was determined it would be important to engage undergraduate and graduate students (Figure 1) in the intervention learning opportunities. These stakeholders are also considered very important in this study. These college coeds planned and presented the workshop intervention sessions. From a collective group of age-appropriate graduate and undergraduate students several were invited to participate in the research study. Only elementary education majors and communication disorder majors were asked to join as a base source of university student participants. The groups were determined by convenience. Specifically, subjects participating in Kappa Delta Pi International Education Honor Society and the National Student Speech-Language-Hearing Association were queried to participate in volunteer as part of a service learning initiative. Each of these college students’ ages varied, but all were over the age of 18. Discussions with each group of individual stakeholders proved to be enlightening. Each group determined they were eager to bond together to support the needs of preschool learners.


Their united goal was to rally around as shareholders to influence preschool students’ achievement. Collaborations across Educational Structures Selden, Sowa, and Sandfort (2006), state it is important to reach “across sectors, collaborations and other inter-organizational structures” in order to “find, new solutions to complex problems” (p. 412). Once the stakeholders were determined and committed to the goal, there was an opportunity to create a strong alliance across several educational structures. This association was unique because the level of support was not limited to one type of setting. Out of the representative sample of research participants (Figure 2), one fifth were university students (undergraduate and graduate), preschool teachers or faculty, and three fifths were parents of preschoolers. As Figure 2 reveals, parents of preschoolers participation was more than double that of each of the other interested parties. Although each of the key stakeholders were important to components to encourage young learners’ literacy learning success, the researchers for this study regarded parent participation in these sessions as invaluable and determined special attention must be given to promote participation. However, the researchers recognized that it might be difficult for parents to attend a meeting at the end of the work day. They ascertained one method to achieve increased participation was to offer food during the sessions. They determined that it would be important to create a safe and nurturing environment where even very busy parents would be encouraged to participate in the events. The events were organized after school or on Saturday mornings at local venues such as a public library facility, a charter school setting, and a preschool site. Pizza was provided for the participants at each event. Over the two-year span of the project, participants grew to expect slices of pizza with their literacy kindergarten readiness events. As noted in Figure 2, the added attention to encourage parent participation paid off with high parent attendance and participation throughout the term of the study. Communication between the preschool faculty, the university students, and instructors was consistent and clear throughout the process. Typical queries were as follows: How can we


create collaborative interventions? How can we make certain these collaborations work to support preschool students’ kindergarten readiness? Over a span of two years, workshops were developed and presented to parents of preschoolers, their young children, and preschool faculty. These workshops were held at elementary and preschool sites, as well as library commons. The method to collect research data included an open-ended question based survey. After each session, the participants were asked to complete the questionnaire on a voluntary basis. Questions on the survey were designed to give research participants an opportunity to reflect and respond on their individual experiences of the collaborative intervention initiative. Effective Reading Intervention Focus Because it is important for teachers to determine where the needs of the students lie, they should be ready to offer effective instruction that complements those needs and leads the learning process. Specifically, Gunn et al. (2011) recommended that children in a federally funded literacy program should be provided with an explicit and comprehensive hands-on experience to accelerate the impact of structured learning episodes. To create these learning experiences, university education and communication arts majors were encouraged to create literacy and language intervention lessons to promote explicit kindergarten readiness skills. Equipped with a background in early childhood education, speech, language development, these students were eager to identify the learning needs of the preschool students’ kindergarten readiness. The area of focus included but was not limited to early learning speech and language experiences, cognition, phonological awareness, print knowledge, physical development (gross and fine motor) and, eye-hand coordination activities. Prior to and throughout the intervention experience, university faculty encouraged and supported university students to develop each workshop. These instructors were awarded grant funding, which provided the university students with needed books and workshop materials. These scholars planned and organized the learning activities for the preschoolers using ideas gained from university instruction. The actual workshop sessions were organized and coordinated by the university faculty. Coeds were given this authentic learning opportunity to


enhance their instructional and clinical techniques. This study allowed for the university students, parents of early learners, and preschool teachers to use a collaborative approach across these entities to investigate solutions that promote student engagement and achievement. Specific attention was placed on interactive lessons designed around seasonal themes. Each lesson included reading, writing, speaking, and listening instruction as a literacy focus. The young leaners had many opportunities to listen to stories read out loud. They had chances to use fine motor skills (i.e. print the letters of their names in shaving cream) as they learned to write. They had occasions to speak about the stories they heard. Every event ended with the early childhood student choosing a book to take home and ‘read’. Often other materials were sent with the young ones, as well. The university students organized take-home bags filled with crayons, markers, playdoh, and paper. Parents were encouraged to extend the learning interventions once the children were at home. Observations of Student Learning During these early years, Hara and Burke (1998) concluded that students should be given opportunities to learn while parents observe their learning (p. 14). From observations, the university students were able to determine areas to support students’ developmental learning. They paid close attention to preschool students’ speech and language. The college students offered their ideas about levels of support for the preschool students’ learning to the preschool parents. The young learners were encouraged to speak clearly and to complete sentences during the events. The students allowed preschool children to engage in interactive learning experiences. Then, they observed the students’ fine motor and eye-hand coordination skills. Additionally, they observed children’s engagement with the activities. They invited students’ participation during each intervention session. Parents observed during the learning activities and asked questions. Preschool teachers watched the children and offered important insight to provide a safe and fun environment for the young students. The university students provided effective instruction to support the educational activities. After these intervention opportunities, the researchers asked participants to reflect and respond about their perceptions in an open-ended question survey.


Participants in this study revealed an eagerness to become more adept at examining the individual needs of the preschool student. They noted they were interested in promoting and accelerating student kindergarten readiness in the early years. Additionally, they enjoyed the opportunity to observe students’ behavior during the intervention sessions. They included these observations helped them to gain a clearer insight to support the needs of the young learner. At the end of the intervention sessions, the university instructors shared their notes about the young learners’ active participation with the preschool parents and teachers. They made recommendations to consider as follow-up activities to the interventions. Data Collection, Questionnaires The method to collect research data included an open-ended question prompt survey. After each intervention workshop, participants were encouraged to complete the surveys on a voluntary basis. Prompts pertained to the impact of the strategies used during the intervention sessions to increase students’ kindergarten readiness. Specific attention was given to a focus on what did the child and/or parent gain from the collaborative initiative. These questions were designed to give research participants an opportunity to reflect and respond on their individual experiences of the parents as partners’ sessions. Findings Patterns Revealed from the Questionnaires This study sought to accomplish the following outcome goals to promote collaborative preschool interventions and identify effective Kindergarten readiness intervention structures. Noticeable patterns were revealed from the survey question responses which suggest these goals were achieved. Interestingly, all of the participants of the study responded in a positive way. There was no evidence to suggest any problems identifying and supporting the needs of young learners in the learning workshops. There were strong indicators of successful collaborations that revealed an effective kindergarten readiness initiative.


Specifically, participants responded positive to language learning and literacy opportunities. Additionally, there were high levels of responses to acknowledge strong student engagement during the sessions. These areas were perceived to yield the highest level of impact on kindergarten readiness. Parents offered they would continue using the effective strategies when the students were at home. University students responded they would use the successful strategies to engage parents and students in future learning episodes. Most importantly of all, the parents noted their children really enjoyed the learning opportunities. As a result of this, they wanted their children to continue to participate in these collaboratively organized sessions. Researchers stated that when parents participated in early intervention sessions, they valued most of all the opportunity to have “a supportive and interested figure: someone to talk to, someone who provided encouragement, who listened, and who could be trusted.” (Schonkoff & Meisels, 2009, p. 376). There is evidence that the parents who participated in this research study valued the collaborative intervention focus. Conclusion Data Collection Process Summary From the data collection process, several patterns appeared pertaining to the questionnaire responses. Parents noted that their children considered the sessions to be positive learning experiences. Additionally, they noted their preschool students’ mood was positive during the events. The results revealed a notion that the reading sessions with their peers were enjoyable and engaging. Literacy learning, language experience, and student engagement were all identified as areas beneficial to the preschool students’ achievement. There was clear evidence that research study participants identified student engagement during the sessions. Overall, the research participants noted the impact of Kindergarten Readiness intervention learning workshop opportunities as positive. The collaborative nature of the events was considered as an effective way to promote effective kindergarten readiness.


Research Recommendations Because of this study, the present investigators see areas for future research. It is apparent that including parents support toward early learners’ academic success (Flouri & Buchanan, 2004), is imperative, future initiatives must include their participation to advance their children’s learning at a very young age. Notably, several strands (Figure 3) emerged from the data collection process. Specifically, as depicted in Figure 3 there are areas that stand out as relevant to pursue for further research. Respectively, percentages included on Figure 3 for the data analysis of the study exposed three areas of strength for the intervention sessions: Literacy, Language, and Reading. Because of an acknowledged success of this initiative, additional research will be considered to enhance these three areas for future Kindergarten Readiness Intervention sessions. Although there were other identified areas appropriate to support the young learners, these areas appear to be the most advantageous to address for further investigation. As long-range planning is considered, the interventions must be organized to support the needs of the early learner over an extended period of time. Gottfried (2015) stated, “researchers, policymakers, and practitioners must base future” research on “address(ing) children’s outcomes across multiple years of care, rather than simply focus exclusively on one year’s influence” (p. 2). With future study proposals in mind, researchers will extend the timeline for the intervention workshops. Continued collaborations with the educational structures will be considered. Also, the researchers will continue dialogue with the stakeholders from this study to contemplate researching alternative readiness projects (i.e. computer technology and Kindergarten Readiness) which were not reviewed with this research study. Author Biographies Dr. Julie Hentges, Dr. Julie Hentges, Associate Professor of Education, is the Program Coordinator for the MSE Elementary Education/Curriculum & Instruction Degree Program at the University of Central MO. She has been there nine years. Dr. Hentges is a certified teacher and a certified K-12 reading specialist in Missouri. Most recently, she was honored as the University of


Central Missouri’s Learning to a Greater Degree Award recipient and the Regional Counselor/Advisor of the Year Award Recipient for Kappa Delta Pi International Education Honor Society. Dr. Hentges holds a Bachelor’s and Master’s degree in Education as well as an earned Doctorate with an emphasis in teacher education. Dr. Hentges has submitted proposals and presented instructional strategies to enhance comprehensive literacy for several Missouri State Conferences; such as, the Missouri International Reading Association Conference, the Missouri Write to Learn Conference, Missouri State Reading Recovery Conference, the Missouri Primary Conference, and the Missouri State Charter School Conference. In addition to presenting at state conferences, Dr. Hentges has submitted proposals and presented at conferences on the national and international level; such as, the Professional Development Schools (PDS) Conference, Teaching & Learning Conference (GA), Center for Scholastic Inquiry (CSI) Conference, American Association of Teacher Educators (ATE) Conference, and Southeast Regional Association of Teacher Educators (SRATE) Conference. Dr. Hentges’ current research interest addresses teaching reading to accelerate student achievement. She plans to continue her research working to meet the needs of students in K-12 classrooms. Dr. Nancy Montgomery is an associate professor in the Communication Disorders Program at the University of Central Missouri in Warrensburg, Missouri. She earned her PhD in Special Education from the University of Kansas and her master of science in speech-language pathology from Central Missouri State University. She has worked as a speech-language pathologist for the past 29 years and has presented at state and national conventions. She has collaborated with colleagues on many community early language and literacy events

References Bagnato, S., Elliott, S. N., & Witt, J. C. (2007). Authentic assessment for early childhood intervention best practices. New York, NY: Guilford Publications. Covey, S. (2004). The 7 habits of highly effective people: Powerful lessons in personal change. New York, NY: Simon & Schuster, Inc.


Flouri, E., & Buchanan, A. (2004). Early father's and mother's involvement and child's later educational outcomes. British Journal of Educational Psychology, 74(2), 141–153. doi: 10.1348/000709904773839806 Gottfried, M. A. (2015). Prekindergarten and kindergarten center-based child care and students’ early schooling outcomes. Teachers College Record, 117(11), 1-28. Retrieved http://www.tcrecord.org/Content.asp?ContentId=18117 Gunn, B., Vadasy, P., & Smolkowski, K. (2011). Instruction to help young children develop language and literacy skills: The roles of program design and instructional guidance. NHSA Dialog, 14(3), 157-173. Hara, S. R., & Burke, D. J. (1998). Parent involvement: The key to improved student achievement. School Community Journal, 8(2), 9-19. Lonigan, C., & Shanahan, T. (2009). Executive summary developing early literacy: Report of the national early literacy panel. Washington, D.C.: National Institute for Literacy. Schonkoff, J., & Meisels, S. (2009). Handbook of early childhood intervention (9th Ed). Cambridge University Press, NY, NY. Selden, S. C., Sowa, J. E., & Sandfort, J. (2006). The impact of nonprofit collaboration in early child care and education on management and program outcomes. Public Administration Review, 66, 412-425. doi:10.1111/j.1540-6210.2006.00598.x Sheridan, S., Edwards, C., Marvin, C., & Knoche, L. (2009). Professional development in early childhood programs: Process issues and research needs. Early Education Development. 20(3), 377-401. Vygotsky, L. (1986). Thought and language. Cambridge, MA: MIT Press. (Original work published 1934)


Figure 1. Effective Kindergarten Readiness collaborative preschool intervention stakeholders.

Figure 2. Effective Kindergarten Readiness study participants.

Figure 3. Effective Kindergarten Readiness questionnaire/data collection summary.


Using Brand Equity and Personality Metrics to Predict the 2016 U.S. Presidential Election Richard J Monahan American Public University Abstract In this study, a multidimensional brand equity and a brand personality construct were employed to compare the brand strength of two candidates for the U.S. presidency in 2016 (i.e., Hillary Clinton and Donald Trump) among registered voters. The study was conducted to judge the predictive quality of these two metrics. Clinton scored higher than Trump on brand equity and personality, but the margins were relatively slim especially with Independent voters. Keywords: Brand equity, brand personality, candidate brands, political marketing, candidate valuation, and political branding. Introduction Brands are powerful symbols that provide meaning to consumers, which influences their purchase intentions (McCracken, 1993). In terms of political candidates and political parties, brand strength has been considered in marketing for many years (Luntz, 1988). Brand equity is the intangible value added to a product, such as Tide laundry detergent simply by the brand name itself, (Aaker, D.A., 1991, 1996; Keller, 1993). Strong brands act to increase trust and loyalty, decrease the possibility of switching to competitive brands, and make marketing efforts much more effective (Aaker, D.A., 1991; Keller, 1993; Yoo & Donthu, 2001). Additionally, a brand can be a person, name, sign, symbol, or design. It is intended to identify products or services and differentiate them from competitors (Kotler, 1991). Brands provide their customers with emotional and experiential beneďŹ ts (Keller, 1993), and these beneďŹ ts are essential to building strong brand equity. Brand personality is a significant


component of brand differentiation, which strongly influences purchase intention (Aaker, J.L. 1997). Studies have demonstrated a positive correlation between brand equity and personality ratings of political candidates and intention to vote (Monahan, 2015, 2016). In this study, a consumer brand equity model and a brand personality construct were applied to measure the brand equity and brand personality strength of two candidates for the U.S. Presidency in 2016: Hillary Clinton and Donald Trump. The results will be used to evaluate the predictive properties of these two measures. Literature Review Brand Equity Aaker, D.A. (1991, 1996) defined brand equity as ‘‘a set of brand assets and liabilities linked to a brand, its name, and symbol, that add to or subtract from the value provided by a product or service to a firm and or to that firm’s customers.’’ He further proposed a fivedimensional model of brand equity that includes name awareness, brand associations, perceived quality, brand loyalty, and other key assets. This study used Yoo and Donthu’s (2001) customerbased brand equity scales, developed to gauge four of the five (i.e., excluding other proprietary assets, patents, trademarks and channel relationships) dimensions proposed by D.A. Aaker. Brand knowledge is a vital element in consumer decision making and greatly affects the success of branding efforts (Keller, 1993). Brand knowledge is composed of brand name awareness and brand associations (Aaker, D.A., 1996). Brand name awareness is the strength of a brand in the memory of the consumer, a necessary condition for brand equity development on the other three dimensions (Keller, 1993). Brand associations are pieces of positive and negative information related to a brand in consumer memory. Brand associations are critical in the overall management function of branding because they represent the content of brand knowledge and provide brand meaning to consumers (Keller, 1993). Research also supports that both perceived brand quality and brand loyalty are strongly related to brand equity. Perceived brand quality is the consumer’s judgment about a brand’s overall excellence (Aaker, D.A., 1996; Zeithaml, 1988). Aaker, D.A., (1996) also pointed out


that perceived brand quality is an important point of differentiation. Brand loyalty is the level of attachment that a customer has to a brand, considered the single most reliable assessment of brand equity (Reichheld, 2001). Loyal consumers provide a company with a competitive advantage that helps establish barriers of entry, gives the company time to respond to competitive offerings, and allows the company to demand premium prices (Aaker, D.A., 1996). Consumer loyalty ultimately results from value and trust derived from the brand name (Chaudhuri & Holbrook, 2001; Riley, 2004). Brand Personality Brand attitude is deďŹ ned as the expression of a consumer’s positive or negative evaluation or feelings toward a brand (Berger & Mitchell, 1989; Kotler & Armstrong, 1996). Brand attitude and brand image have been shown to have positive relationships with brand equity (Chang & Liu, 2009; Faircloth et al., 2001). Brand equity is essential because brands with higher levels of brand equity generate higher levels of customer brand preference, purchase intentions Chang & Liu, 2009; Senthilnathan & Tharmi, 2012), and repurchase intention (Hellier, Geursen, Carr, & Rickard, 2003). Brand personality as a component of brand imagery helps to create brand equity (Batra, Lehman, & Singh, 1993; Biel, 1993). Candidate Brands Branding is concerned with creating a distinctive identity, for a product, service, or individual (Aaker, J.L., 1997; Plummer, 2000). Individuals themselves can actually be brands. For example, Lebron James and Eli Manning serve as primary sources of identity. Candidate brands are similar to the latter, where political leaders and their associations define the brand. The present focus is on brand equity derived from the candidate’s name (e.g., Barack Obama), which is the part of a brand that can be verbalized and is the primary indicator of brand value (Cobb-Walgreen, Ruble, & Donthu, 1995; Keller, 1993). The name of the candidate, like product brand names, provides the voter with an experience-based technique for quick problem solving that provides voter orientation and influences voter choice (Needham, 2006; Schneider,


2004). The act of voting is like a ‘‘consumer choice,’’ for which voters use small amounts of information received during the campaign to facilitate their choice between candidates (Parker, 2012; Popkin, 1994). A great deal of research has examined different aspects of political branding (Lauro, 2000; Needham, 2005, 2006; Reeves, 2006; Westen, 2007). Industry strategists suggest that the use of different branding tactics developed in commercial markets (e.g., personality, trust, connectivity, and performance) can also be used in politics for comparing the image and or brand positions of candidates (i.e. Draper, 2000; Parker, 2012; Westen, 2007). Despite that most of the research on political branding is relatively new, there have been sufficient studies to support the concept that candidate brands can be treated as units of empirical analysis and observation. Candidate traits taken from the D. A. Aaker’s brand equity scale were used to analyze the results of the 2006 Presidential election in Mexico (Guzman & Sierra, 2009). A recent outgrowth of the study of the human brand is political marketing. The role of the political leader is clearly considered part of the marketing offer (Speed, Butler, & Collins, 2014). It also seems that the U.S. news media has long recognized the existence of political branding (Milewicz & Milewicz, 2014). Multidimensional Brand Equity Scale Yoo and Donthu (2001) developed a series of validated psychometric scales that measure aspects of customer-based brand equity. Yoo and Donthu (2001, p. 2) defined brand equity as the ‘‘measurement of cognitive and behavioral brand equity at the individual consumer level through a consumer survey.’’ Scale indicators were factors analyzed from an original pool of scale items from a wide range of validated measures of each dimension and eventually reduced to 10 items that make up the multidimensional brand equity scale (MBE) (Yoo & Donthu, 2001). The four-dimensional scale items capture attitudinal loyalty, brand recognition awareness, perceived quality, and the ‘‘perceptual strength’’ of brand associations. The MBE has been shown to be parsimonious in brand survey research, highly reliable across product categories and brands, and free of cultural bias. However, it is important to note that the MBE measure only captures the perceptual strength of brand associations.


Brand Personality Scale Brand personality is measured by five dimensions that uniquely apply to consumer brand characterization (Aaker, J.L., 1997). Jennifer Aaker’s research developed a reliable scale to assess brand personality (Koebel & Ladwein, 1999). Aaker, J.L. (1997) developed a theoretical framework of the brand personality construct by determining the number and nature of dimensions of brand personality traits. These five brand personality dimensions desired by many companies for their products are sincerity, excitement, competence, sophistication, and ruggedness. Brand equity and personality and purchase intention. Brand attitude is defined as the expression of a consumer’s positive or negative evaluation or feelings toward a brand (Berger & Mitchell, 1989; Kotler & Armstrong, 1996). Brand attitude and brand image have been shown to have positive relationships with brand equity (Chang & Liu, 2009; Faircloth et al., 2001). Brand equity is essential because brands with higher levels of brand equity generate higher levels of customer brand preference, purchase intentions (Berry, 2000; Chang & Liu, 2009; Senthilnathan & Tharmi, 2012), and repurchase intention (Hellier et al., 2003). As a component of brand imagery, brand personality helps to create brand equity (Batra et al., 1993; Biel, 1993). In two studies conducted by this author, both brand equity and brand personality demonstrated a positive correlation with voting intention (Monahan 2015, 2016). Purpose of the Study Since prior research has focused mainly on analyzing past elections, the purpose of this study was to evaluate the predictive power of the MBE construct and D.A. Aaker’s brand personality scale in determining the outcome of the 2016 U.S. election.


Methodology The study design used survey research to assess candidate brand equity, and brand personality of U.S. presidential candidates (i.e., Hillary Clinton [D] and Donald Trump [R], from a sample of registered voters. Respondents were registered voters recruited from various parts of the country. Respondents were asked a series of statements taken from the brand equity and personality scales and to indicate their agreement on a five-point Likert scale. Candidate Brand Equity Measurement Yoo and Donthu’s (2001) MBE served as the measure of candidate brand equity. It was necessary to modify the wording of some items to use the MBE in the context of political candidates voted for rather than brands purchased. The modified 10-item MBE measure has two items for candidate name awareness (‘‘I am aware of candidate x’’ and ‘‘I can recognize candidate x among other competing candidates’’), three items for brand association strength (‘‘some characteristics of candidate x come to my mind quickly,’’ ‘‘I can quickly recall the symbol or logo of candidate x,’’ and ‘‘I have difficulty imagining candidate x in my mind’’), two items for perceived candidate quality (‘‘the likelihood that candidate x would be a quality president is extremely high’’ and ‘‘the likelihood that candidate x would be a functional president is extremely high’’), and three items for candidate brand loyalty (‘‘I consider myself loyal to candidate x,’’ ‘‘for U.S. president candidate x would be my first choice,’’ and ‘‘I will not vote for another candidate if candidate x runs in the general election’’). The MBE (Yoo & Donthu, 2001) is a three-factor model that combines recognition awareness and perceptual strength of associations into one memory-based factor while treating perceived quality and brand loyalty as independent factors. Respondents indicated their agreement to each item statement using five-point Likert scales. Candidate total brand equity ratings and scores for each dimension were the focal point of analysis. Averaged items for each scale dimension produced for each candidate an awareness-association strength score, perceived candidate quality score, and candidate loyalty score. A candidate’s total brand equity rating consisted of an average of the dimension scores across all scaled items.


Candidate Brand Personality Measurement Brand personality was measured using the dimensions developed by Jennifer Aaker in 1997. In this study, she identified 15 aspects of brand personality: down to earth, honest, wholesome, cheerful, daring, spirited, imaginative, up to date, reliable, intelligent, successful, upper class, charming, outdoorsy, and tough. These were then combined into five major components of brand personality: honest, wholesome, and cheerful came under the category of sincerity, daring, spirited, imaginative and up to date came under the category of excitement, reliable, intelligent, and successful came under the category of competence, upper class, and charming came under the category of sophistication, and outdoorsy and tough came under the category of ruggedness. Using the above methodology, a survey was composed of 15 questions where respondents were asked to describe their agreement on a five-point Likert scale about how each of the personality traits describes the personality of the two candidates for the 2016 U.S. presidency. In addition to the questions on brand equity and personality, each of the respondents was asked a series of demographic questions: age, gender, political party affiliation, household income, location in the United States, and what they considered the biggest problem that America currently faced. The choices were the economy, immigration, terrorism, race relations, and crime. Sample There were 490 surveys sent out and 415 were usable for analysis. The sample was split between 178 males and 237 females. The political party affiliations were 150 Democrats, 152 Independents, 98 Republicans, and 15 represented other parties. The ages of the respondents ranged from 18 to over 65; there were 44 respondents aged 18-29, 102 aged 30 to 44, 115 aged 45 to 59, 154 aged 60 or over. The education of the respondents ranged from high school graduates to postgraduate and higher degrees. There were 39 high school graduates, 109 respondents had some college, 143 were college graduates, 22 had some postgraduate education, and 102 had postgraduate or higher degrees. The annual family income of the sample ranged


from less than $10,000 to over $200,000 per annum. There were 10 respondents that earned less than $10,000, 21 respondents earned $10,000 to $24,999, 74 earned $25,000 to $49,999, 82 earned $50,000 to $74,999, 56 earned $75,000 to $99,999, 37 earned $100,000 to $124,999, 34 earned $125,000 to 149,999, 21 earned $150,000 to 174,999, 4 earned $175,000 to 199,999, 20 earned over $200, 000 and 56 preferred not to answer. There were 50 respondents from New England, 69 came from Middle Atlantic States, 95 from South Atlantic States, 84 from East North Central States, 19 from West North Central States, 23 from East South Central States, 26 from West South Central States, 15 from Mountain States, 34 from Pacific States. In terms of the most important issue facing the United States, 190 respondents thought that the economy was the most important issue, 83 thought that race relations was the most important issue, 71 saw terrorism as the most important issue, 36 indicated crime as being the most important and 35 saw immigration more important. Results Candidate Brand Equity Scores Displayed in Table 1 are candidates’ overall MBE scores (i.e., a composite mean of candidate awareness-association strength, perceived quality, and loyalty scale items). Clinton had the highest brand equity score (3.27) and Trump had (2.81). The scores by party are listed in Table 2. The scores for Clinton are (4.09) with Democrats, (2.59) with Republicans, and (3.01) with independents. The scores for Trump are 2.35 with Democrats, 3.54 with Republicans, 2.83 with independents. Table 3 lists the brand equity score in terms of important issues. Those respondents who thought that the economy was the most important issue facing America scored Clinton at (3.24) and Trump at (2.74), respondents who considered immigration the most important issue scored Clinton at (2.56) and Trump at (3.64). Respondents who considered terrorism the most important issue scored Clinton at (3.25) and Trump at (3.02). Those respondents who considered race relations scored Clinton at (3.49) and Trump at (2.49), and finally, those respondents who considered crime the most important issue scored Clinton at


(3.54) and Trump at (2.68). The brand equity scores by gender are listed in Table 4. Men scored Clinton at (3.21) and Trump at (3.01). Females scored Clinton at (3.32) and Trump at (2.66). Candidate Brand Personality Scores Displayed in Table 5 are the candidates’ overall personality score (i.e. the composite mean of candidate personality ratings for sincerity, excitement, competence, sophistication, and ruggedness). Clinton has the higher brand personality score of 2.90 and trump was 2.30. The scores by party are listed in Table 6. Clinton scored (3.69) among Democrats and Trump scored (1.73). Clinton scored (2.17) with Republicans and Trump scored 3.05. Clinton scored (2.68) with independents and Trump scored (2.40), Clinton scored 2.51 with other party and Trump scored 2.14. Table 7 lists the brand personality scores in terms of important issues. Clinton scored (2.85) and Trump scored (2.74) with people who thought that the economy was the most important issue. Clinton scored (2.21) and Trump scored (3.64) among respondents who thought that immigration was the most important issue. Clinton scored (2.83) and Trump (3.02) with respondents who thought that terrorism was the most important issue. Clinton scored (3.19) and Trump (2.49) with respondents who thought that race relations was the most important issue. Clinton scored (3.21) and Trump (2.68) with respondents who thought that crime was the most important issue. The brand personality scores by gender are listed in Table 8. Men scored Clinton at (2.75) and Trump at (2.44). Females scored Clinton at (3.00) and Trump at (2.17). Discussion The brand equity rating for Hillary Clinton was a stronger rating than Donald Trump. This would indicate Mrs. Clinton should be favored to win the election. This was demonstrated in the polling data at the time of data collection. There should be a note of consideration in that the scores are Clinton (3.27) and Trump (2.81). The scores for both candidates are relatively low indicating that there is no strong support for either candidate. If we are to consider past elections, we can foresee that the results of a presidential election are heavily dependent on the voting of independent voters. There were 152 independent voters in this study and the results of


indicated that there is no statistically significant difference between Clinton (3.01) and Trump (2.83). This is indicated by a Levene's Test for Equality of Variances which is displayed in Table 9. This would indicate that the race is much closer than the polls are currently indicating. The majority of respondents indicated that the economy was the single most important issue facing the United States. This appears to be good news for Clinton in that the brand equity scores for respondents that placed a higher importance on the economy was Clinton (3.24) to Trump (2.74). The scores for the second most important issue was race relations, which was also favorable to Mrs. Clinton; the scores were (3.49) and Trump (2.49). The issue of terrorism is third in importance and it is somewhat even among the two candidates but once again Clinton is higher. The scores were (3.25) for Clinton and (3.01) for Trump. The issue of crime also supports Mrs. Clinton with a score of (3.54) to Trump (2.68). The only score that Mr. Trump was well ahead on was immigration, which was (3.64) to Mrs. Clinton’s (2.56). Another indicator in Mrs. Clinton’s favor is the difference in brand equity rating for men and for women. Men scored Mrs. Clinton (3.21) and Trump (3.01). Women scored Trump at (2.66) and Clinton at (3.31). The brand personality ratings were also in Mrs. Clinton’s favor. The total rating for Clinton was (2.89) and (2.29) for Trump. Once again, the ratings by independent voters was much closer in value, Clinton with (2.67) and Trump (2.39). In a past study (Monahan, 2015) it was determined that the personality factor sincerity had the greatest relationship to voting intention. While Clinton is still higher with independent voters on this factor, the scores are very close, Clinton (2.67) and Trump (2.39). In terms of excitement, which is an indicator of voter enthusiasm, Trump was higher among independents with (2.87) to Clinton’s (2.58). This aspect was surprising in the it was thought that there would be more excitement for Mrs. Clinton because of the historic nature of Mrs. Clinton’s candidacy as the first woman nominee for President from a major political party. In terms of the issues, Clinton’s brand personality ratings were higher than Trump on all issues with the exception of immigration. Respondents thinking the economy was important scored Clinton with a (2.85) and Trump with (2.13). Those respondents who considered race relations the most important issue scored Clinton (3.18) and Trump (1.93). Those who considered terrorism the most important issue scored Clinton at (2.82) and Trump at (2.54).


Respondents who considered crime the most important issue scored Clinton at (3.02) and Trump at (2.18). In terms of gender, men gave Mrs. Clinton a personality rating of (2.75) and Trump at (2.44). Alternatively, women scored Clinton at (3.0) and Trump at 2.17). Future Research Future research could track the actual winner of this close race. A one-year, two-year, and three-year study could be used to further evaluate any changes in the brand indicators of the winner. In studies such as this, the republicans evaluate the republican candidate favorably and the democrats do the same. For this reason, future studies should focus on changes in the evaluation of the winner by independent voters. Conclusion This study gives Hillary Clinton the advantage in the upcoming presidential election. The point that is worth noting is that independent voters do not appear to vigorously support either candidate. Independents score both candidates the same for brand equity and Clinton is ahead in brand personality, but the ratings are relatively close. These scores do indicate the possibility that voters could still be swayed one way or the other between now and the election. Since this election is historic, it was expected that there would be more enthusiasm for Mrs. Clinton in that she is the first women to win the presidential nomination from a major political party in the U.S. The lack of enthusiasm and the relatively low scores for both candidates indicate that a powerful event between now and the election could change the dynamic. Since the respondents overwhelmingly communicated that the economy is the most important issue facing the country, a sudden downturn in the economy could change the dynamic. In addition, a superior performance in any of the upcoming debates by either candidate could also change the dynamic. Mrs. Clinton could solidify her lead or Mr. Trump could close the gap.


This study clearly gives candidate Clinton the advantage in this election but her advantage with the very important independent voter is slim to nonexistent. This study demonstrates that the election is much more competitive than the current polls would indicate. Author Biography Richard Monahan is an adjunct professor at American Public University. He has presented his work in different international and national conferences. His most recent publication is Measuring Xenophobia in the U.S. Electorate, presented at the 24th Annual Conference on International Business held in Rapid City, South Dakota October 4 to 6 2017. References Aaker, D. A. (1991). Managing brand equity: Capitalizing on the value of a brand name. New York, NY: The Free Press. Aaker, D. A. (1992). The value of brand equity. Journal of Business Strategy, 13(4), 27-32. Aaker, D.A. (1996). Building strong brands. New York, NY: The Free Press. Aaker, J. L. (1997). Dimensions of brand personality. Journal of Marketing Research, 34(3), 347-356. Batra, R., Lehmann, D., & Singh, D. (1993). The brand personality component of brand goodwill: Some antecedents and consequences. In D. Aaker and A. Biel (Eds.). Brand equity & advertising: Advertising’s role in building strong brands (pp. 83-95). Hillsdale, NJ: Lawrence Erlbaum. Berger, L. E., & Mitchell, A. A. (1989). The effect of advertising on attitude accessibility, attitude confidence, and the attitude-behavior relationship. Journal of Consumer Research, 16(3), 269-279. Biel, A. (1993). Converting image into equity. In D. Aaker and A. Biel (Eds.). Brand equity & advertising: Advertising’s role in building strong brands (pp. 67-82). Hillsdale, NJ: Lawrence Erlbaum.


Chang, H. H., & Liu, Y. M. (2009). The impact of brand equity on brand preference and purchase intentions in the service industries. The Service Industries Journal, 29(12), 1687-1706. Chaudhuri, A., & Holbrook, M. B. (2001). The chain of effects from brand trust and brand affect to brand performance: The role of brand loyalty. Journal of Marketing, 65(2), 81-93. Cobb-Walgreen, C. J., Ruble, C., & Donthu, N. (1995). Brand equity, brand preference, and purchase intent. Journal of Advertising, 24(3), 25-40. Draper, D. (2000). Candidate brands are key to mayoral battle. Marketing, March(2), 7. Faircloth, J.B., Capella, L.M. and Alford, B.L. (2001), “The effect of brand attitude and brand image on brand equity”, Journal of Marketing Theory and Practice, 9 (3), 61- 75. Hellier, P. K., Geursen, G. M., Carr, R. A., & Rickard, J. A. (2003). Customer repurchase intention: A general structural equation model. European Journal of Marketing, 33(11/12), 1762-1800. Guzman, F., & Sierra, V. (2009). A political candidate's brand image scale: Are political candidates brands? Journal of Brand Management, 3(12), 207-217. Keller, K. L. (1993). Conceptualizing, measuring, and managing customer-based brand equity. Journal of Marketing, 57(1), 1-22. Koebel, M.-N., & Ladwein, R. (1999). ‘L’échelle de personnalité de la marque de Jennifer Aaker. Adaptation au contexte français’, Décisions Marketing, 16(Jan-April), 81-88. Kotler, P. H. (1991). Marketing management: Analysis, planning, and control, (8th ed.). Englewood Cliffs, NJ: Prentice-Hall. Kotler, P. H., & Armstrong, G. (1996). Principles of marketing. Mahwah, NJ: Prentice-Hall. Lauro, P. W. (2000). According to a survey, the Democratic and Republican parties have brandname problems. New York Times, (Late Ed.). (East Coast), Nov17, C10. Retrieved from http://proquest.umi.com.ezproxylocal.library.nova.edu Luntz, F. I. (1988). Candidates, consultants, and campaigns: The style and substance of American electioneering. New York, NY: Wiley-Blackwell. McCracken, G. (1993). The Value of a Brand: An Anthropological Perspective. In D. Aaker and A. L. Biel. Brand equity and advertising. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc.


Milewicz, C., & Milewicz, M. (2014). The branding of candidates and parties: The U.S. news media and the legitimization of a new political term. Journal of Political Marketing, 13(4), 233-263. Monahan, R. (2015). Brand equity evaluation for prospective candidates in the 2016 U.S. presidential race. Mustang Journal of Management and Marketing, 6, 70-78. Monahan, R. (2016). Brand personality and voting intention of political candidates for the 2016 U.S. presidential election. National Business and Economic Society Conference Proceedings, Los Cabos, Mexico, March 2016. Needham, C. (2005). Brand leaders: Clinton, Blair and the limitations of the permanent campaign, Political Studies, 53, 343-361. Needham, C. (2006). Special issue papers: Brands and political loyalty. Journal of Brand Management, 13(3), 178-187. Parker, B. T. (2012) Candidate brand equity valuation: A comparison of U.S. presidential candidates during the 2008 primary election campaign. Journal of Political Marketing,11(3), 208-230. Plummer, J. T. (2000). How personality makes a difference. Journal of Advertising Research, 40(6), 79-82. Popkin, S. L. (1994). The reasoning voter: Communication and persuasion in presidential campaigns (2nd ed.). Chicago, IL: The University of Chicago Press. Reeves, P. (2006). Building a political brand: Ideology or voter-driven strategy. Brand Management, 13(6), 418-428. Reichheld, F. F. (2001). Loyalty rules: How today’s leaders build lasting relationships. Boston, MA: Harvard Business Review Press. Riley, C. (2004). Mapping out a path to hidden treasure of customer loyalty. Media, Feb. 27, 16. Schneider, H. (2004). Branding in politics: Manifestation, relevance and identity-oriented management. Journal of Political Marketing, 3(3), 41-67. Senthilnathan, S., & Tharmi, U. (2012). The relationship of brand equity to purchase intention, The Journal of Marketing Management, 11(2), 7-26.


Speed, R., Butler, P., Collins, N. (2014). Human branding in political marketing: Applying contemporary branding thought to political parties and their leaders. Journal of Political Marketing, 13(4), 129-151. Wang, X., & Yang, Z. (2008). Does country-of-origin matter in the relationship between brand personality and purchase intention in emerging economies? Evidence from China’s auto industry, International Marketing Review, 25(4), 458-474. Westen, D. (2007). Branding the Democrats. The American Prospect, 18(5), 44. Yoo, B., & Donthu, N. (2001). Developing and validating a multidimensional consumer-based brand equity scale. Journal of Business Research, 52(1), 1-14. Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: A means-end model and synthesis of evidence. Journal of Marketing, 52(3), 2-22 Table 1 Candidate MBE Brand Equity Scores Candidate

n

SD

Brand Equity

Clinton

210

1.275

3.272

Trump

205

1.191

2.811

Table 2 Candidate MBE Brand Equity Score by Party Candidate

Democrat

Republican

Independent

Other Party

M

N

SD

M

N

SD

M

N

SD

M

N

SD

Clinton

4.09

71

1.10

2.58

48

1.01

3.01

82

1.00

2.77

9

.868

Trump

2.35

79

.818

3.54

50

1.24

2.83

70

1.19

2.51

6

.998


Table 3 Candidate MBE Brand Equity Score by Issue Economy

Immigration

Terrorism

Race Relations

Crime

M

N

SD

M

N

SD

M

N

SD

M

N

SD

M

N

SD

Clinton

3.24

96

1.19

2.56

14

1.24

3.25

42

1.34

3.49

38

1.27

3.54

20

1.38

Trump

2.74

94

1.12

3.64

21

1.39

3.02

29

1.22

2.49

45

0.96

2.68

16

1.14

Table 4 Candidate MBE Brand Equity Score by Gender Males

Females

M

N

SD

M

N

SD

Clinton

3.21

90

1.30

3.32

120

1.26

Trump

3.01

88

1.19

2.66

117

1.14

Table 5 Candidate Brand Personality Scores Candidate

n

SD

Brand Personality

Clinton

210

1.22

2.90

Trump

205

1.28

2.30

Table 6 Candidate Brand Personality Score by Party Democrat

Republican

Independent

Other

M

N

SD

M

N

SD

M

N

SD

M

N

SD

Clinton

3.69

71

1.02

2.17

48

1.06

2.68

82

1.11

2.51

9

1.05

Trump

1.73

79

0.97

3.05

50

1.30

2.40

70

1.31

2.14

6

0.99


Table 7 Candidate Brand Personality Scores by Issue Economy

Immigration

Terrorism

Race Relations

Crime

M

N

SD

M

N

SD

M

N

SD

M

N

SD

M

N

SD

Clinton

2.85

96

1.15

2.21

14

1.10

2.83

42

1.31

3.19

38

1.11

3.21

20

1.46

Trump

2.74

94

1.12

3.64

21

1.39

3.02

29

1.23

2.49

45

0.97

2.68

16

1.14

Table 8 Candidate Brand Personality Scores by Gender Males

Females

M

N

SD

M

N

SD

Clinton

2.75

90

1.27

3.01

120

1.17

Trump

2.44

88

1.19

2.17

117

1.22

Table 9 Levene's Test for Equality of Variances F Equity Equal variances assumed .938 Equal variances not assumed

Sig. .334

t

df

-.746

150 -.741

141.435


Security Price Impact of Cash Flow Estimates Versus Accounting Accruals Across Industries Ronald Stunda Valdosta University

Abstract This study extends the research of Defond and Hung (2003), who found significance between analysts’ forecasts of cash flow and security returns, but failed to find significance between accounting earnings and security returns. Overall results indicate that accounting earnings possess information content to the investor when associated with firms’ security prices, regardless of industry. When assessing the analysts’ forecast of cash flows, industry membership, along with analyst group (i.e., above or below average), seem to have a bearing on strength of information content when relating the forecast to security prices of the firms. Keywords: Forecasts, Accounting accruals, Security markets Introduction Cash flows have been used in many studies to achieve several objectives. Perhaps the most notable cash flow studies are those of Wilson (1986, 1987). In both studies, findings suggest that the cash and total accruals component of earnings have incremental information content beyond earnings themselves. These studies compelled other researchers to evaluate the information content of cash flow components. Livnat and Zarowin (1990) disaggregated cash flow into its operating, financing and investing components. They concluded that the disaggregation of cash flows into operating cash flows and accruals does not improve the relationship between cash flows and security returns beyond the contribution of net income. Further, they find that there is an improved degree of association between financing and operating cash flows and security returns.


Sloan (1996) found that stock prices fail to fully reflect information contained in the accrual and cash flow components of current earnings until that information impacts future earnings. Cash flow is defined in this study as the income from continuing operations less accruals. Again, the uncertainty of the accrual calculations limits the accuracy of this proxy for cash flows. Stunda (1996) found that reported cash flows, when disaggregated by operating, financing and investing components, have a greater relationship with security returns than with disaggregated estimates reported by Livnat and Zarowin (1990). Dechow (1998) disaggregates the accrual components of cash flows and found that some have greater predictive value on security returns than others. Barth, Cram, and Nelson (2002) pick up on the Dechow study and circle back to the findings of the studies from the 1980’s and re-assert that accruals have a greater predictive ability of security returns than do actual cash flows, thereby contradicting the finding of Stunda (1996). These studies are extended by later studies that emphasize the need for stable cash flows. Graham, Campbell, and Rajgopal (2005) finds 97% of corporate executives favor stable, nonvolatile cash flows as being a positive influence on earnings and security prices. Brown and Kapadia (2007) show the rise in cash flow volatility, especially among new public offerings. Bennett and Sias (2007) relate a good deal of the cash flow volatility to small stocks, although Irvine and Pontiff (2008) attribute only 1/3 of the total cash flow volatility to small stocks, and further find that such volatility has increased since 1997. Morck, Yung, and Yu (2009) posit that because of increased volatility in cash flows, perhaps cash flows do not have the predictive ability they were found to have in prior research. The issuance of operating cash flow forecasts by analysts is a relatively recent phenomenon. As documented by DeFond and Hung (2003), analysts’ cash flow forecasts first appear in the IBES database in 1993. The percentage of US firms in the IBES database with at least one cash flow forecast issued by analysts increased from 4% in 1993 to 65% in 2015. This growth trend in cash flow forecast issuance is also observed at the analyst level. Specifically, the percentage of analysts’ earnings forecasts that are accompanied by cash flow forecasts has increased from 1% in 1993 to 77% in 2015.


With regard to cash flow forecasts, DeFond and Hung (2003) report that firms which have cash flow forecasts tend to have greater capital intensity and risk relative to industry peers. Ertimur and Stubben (2005) examine whether analyst characteristics play a role in the supply of cash flow forecasts. They find analysts from bigger brokerage houses, who forecast earnings more frequently and who have more accurate prior earnings forecasts, are more likely to issue cash flow forecasts. In addition, DeFond and Hung 2003, McInnis and Collins 2008, and Call 2008 examine whether investors respond differently to the cash flow forecasts and management’s accrual components of earnings when setting stock prices for firms. These studies provide evidence indicating that investors place relatively more weight on the analysts’ cash forecast, as opposed to the accruals emanating from management. DeFond and Hung (2003) examine the two-day abnormal returns surrounding firms’ announcement of earnings. The authors find no significant relation between unexpected earnings and security prices but a strong positive relation between unexpected cash flows and security prices. This above result contrasts with prior studies that show a strong positive relation between unexpected earnings and security prices without cash flow forecasts (i.e., Ball & Brown 1968, Beaver, Clarke, & Wright 1979, Baginski & Hassell 1990, etc). In examining managerial response to cash flow forecasts, McInnis and Collins (2008) predict that cash flow forecasts increase the transparency of accrual manipulations because cash flow forecasts enable market participants to decompose earnings surprises into their cash flow and accrual components. They find firms with cash flow forecasts are less likely to manipulate reported earnings relative to firms without cash flow forecasts, resulting in better accruals quality and a decreased likelihood of meeting earnings targets. In addition, Call (2008) finds that cash flow forecasts discipline managers to report more informative operating earnings. Thus, existing research indicates that analysts’ cash flow forecasts have important implications for both investors and managers. This study extends the result observed by DeFond and Hung (2003) that is, firms which have cash flow forecasts tend to have greater capital intensity and risk relative to industry peers. Although the Defond and Hung (2003) study assesses similarities among industry firms, it does not attempt to measure any differences across industries. Different industries possess differing amounts of capital intensity and risk. An assessment along this line would give a better


understanding of the effect of cash flow forecasts. In addition, this study also incorporates the finding of extant studies that show a strong positive relation between unexpected earnings (utilizing accounting accruals) and security prices, also across industries. This structured approach facilitates a better understanding of the relationship between accounting earnings, established through management accruals, and cash flow forecasts, estimated by security analysts, and their relationship to the firm’s security price. The result is a more finite analysis of this issue. Literature Review Analysts’ Forecasts Nichols (1989) and Schipper (1991) suggest that the behavior of analysts provides insight into the activities and beliefs of investors that cannot be observed directly. In addition, the effects of increased disclosures, and information surrounding these disclosures, are of interest to accounting professionals who are involved in attesting to firm financials, firm managers, and regulators. Benefits of such information described by the American Institute of Certified Public Accountants (AICPA) Special Committee on Financial Reporting (AICPA, 1993) include reduced uncertainty, lower information asymmetry among market participants, fewer earnings surprises, and a greater investor following. Empirical research provides similar findings, including reduced estimation of risk (Barry & Brown, 1985), increased investor following (Merton, 1997), and reduced information asymmetry (Glosten & Milgrom, 1985). The role of analyst coverage has often arisen in extant research with respect to its ability to enhance the information provided by firm disclosures (both mandatory and voluntary). Clement and Tse (2005) find that firms with a greater following of analysts also contain an increase in the accuracy of the analysts’ forecasts. Brennan and Subrahmanyam (1995) find a positive association between analyst following and liquidity of the firm. Chung, McInish, Wood, and Wyhowski (1995) find a negative association between analyst coverage and information asymmetry. O’Brien and Bhushan (1990) find that analyst following reduces return volatility of the firm.


Prior research has also interjected behavioral characteristics regarding analyst coverage. Hong, Kubik, and Solomon (2000) find that firms with a greater number of analysts following are likely to contain less experienced analysts providing a forecast of the firm. This is confirmed by Trueman (1994) who finds that weaker analysts are more concerned about reputation and are more likely to herd with other analysts in following a firm. McNichols and O’Brien (1997), Rajan and Servaes (1998), Bradley, Jordan, and Ritter (2003), and Cliff and Denis (2004) all find evidence that analysts prefer to cover firms that they view favorably. Lang and Lundholm (1996) find that analysts are more likely to cover firms with more information disclosure policies. Fortin and Roth (2007) find that more analysts are attracted to larger firms as opposed to smaller firms. Obrien (1990) conducted a comprehensive analysis of forecast accuracy among financial analysts in nine industries during the period 1975-1982. The conclusion of this study is that significant differences in the earnings forecast accuracy of financial analysts do not exist. This runs contrary to literature published in such notable investment periodicals as the Institutional Investor and the Wall Street Journal, which have over the years not only asserted that there are differences in financial analysts, but have recognized those who are considered superior analysts. Other extant studies such as Richards (1976), Brown and Rozeff (1980), Obrien (1987), Coggin and Hunter (1989), Butler and Lang (1991), and Stickel (1992) also support the Obrien (1990) finding that supports the absence of analysts who possess the ability to generate more accurate forecasts over time. Sinha, Brown, and Das (1997) re-examine this issue of forecast accuracy among financial analysts during the period 1984-1990, consistent of the fourteen largest industries at the time. Contrary to previous research, the authors find that significant differences do exist in financial analysts’ forecasts, primarily centered in the Utilities industry. The authors define a superior (inferior) analyst as one having a smaller (larger) forecast error in earnings per share forecast. Stunda (2015) provides evidence that certain industries have a higher analyst following, and as a result possess a greater information-enhancing signal to investors. Stunda (2016) finds that forecasts of analysts in certain industries are likely to have less forecast error, and thus are more meaningful to the investor.


Accounting Earnings The association between accounting earnings and security returns was first propounded by Ball and Brown (1968). The premise of the Ball and Brown study was to see whether the magnitude of unexpected earnings (as opposed to merely the sign of unexpected earnings) was related to the magnitude of the stock price response. Beaver et al. (1979) addressed the issue and discovered, in fact, that the magnitude of unexpected earnings was related to the magnitude of the stock price response. Again, they focused on market-adjusted stock returns to facilitate across-firm comparisons and to control for market-wide movements in stock prices. Ball and Brown (1968) and Beaver et al. (1979) show that despite the deficiencies of historical cost accounting, accounting earnings are potentially useful to investors. They also ushered in the socalled information perspective on the decision usefulness of accounting. The information perspective implies that investors’ response to accounting information can provide a guide as to what type of information is or is not valued by investors. The next logical question to ask was whether the market responded more strongly to unexpected earnings in some firms, and less strongly in other firms. This question is quite pertinent to accountants because we potentially would be better able to design financial statements if we knew the factors that predict when and why investors respond more strongly (less strongly) to financial statement information. Consistent with the literature, the term “Earnings Response Coefficient,” or “ERC” is used to describe the strength of the market response to unexpected earnings. To understand this line of research, one needs to have an intuitive understanding of how investors might respond to accounting information in light of single person decision theory, portfolio theory, and efficient market theory. Here is the basic idea: Let’s say that last period’s earnings were $1 and, accordingly, that is the level of earnings an investor expects this year. When this year earnings are announced, the level of earnings are, say, $1.25, implying a $0.25 earnings surprise. If the investor believes this $0.25 level of unexpected earnings is a one-time shot that will not recur into the future, the investor will increase his assessment of stock value by $0.25. However, if the investor believes this $0.25 unexpected increase in earnings is a permanent boost to earnings that will recur in future years, then the investor’s increase in stock price is $0.25 + the present value of receiving $0.25 into


perpetuity. Given this framework for thinking about how investors should respond to unexpected earnings, it can be predicted that investors will respond more strongly to unexpected earnings when those earnings are expected to persist into the future. It can also be predicted that investors’ response to unexpected earnings will be smaller the higher the discount rate they use in discounting those unexpected earnings that are expected to be received into perpetuity. Subsequent numerous studies have tested these predictions, and here is what they found: (a) ERC are increasing in the persistence of earnings. This has implications for accountants because it suggests the importance of clearly identifying on the income statement those transactions that are nonrecurring transactions (Baginski & Hassell, 1990). (b) ERC are decreasing in the riskiness of the firm and the leverage of the firm because both imply that investors demand higher expected returns and thus will use a higher discount rate in discounting the unexpected earnings expected to persist into the future. Thus, accountants should minimize the opportunities for off-balance sheet financing (or make sure the off-balance sheet financing is transparent) (Ajinkya, Atiase, & Gift, 1991). (c) ERC are increasing in the growth opportunities of the firm because unexpected earnings reported by growth firms are expected to persist into the future. Thus, the forward-looking MD&A disclosures are particularly important because they provide information about growth opportunities (Collins & Kothari, 1994). (d) ERC are increasing in the quality of accounting accruals. Thus, detailed information about the components of accounting accruals might be useful to investors (Lev, 1989). Data and Methodology This study extends the research of Defond and Hung (2003), who found significance between analysts’ forecasts of cash flow and security returns, but failed to find significance between accounting earnings and security returns. Past research finds potential for assessing analysts’ forecast of cash flows, and accounting earnings by industry membership, and analyst group (i.e., above or below average). This study will extend the minimal research to date in these areas.


The sample consists of quarterly earnings and security prices during the years 2011-2015. The starting period of 2011 was selected since it represents a complete year not impacted by the latest recession. The ending period of 2015 represents the last full year available at the time of the study. Earnings data are obtained from Compustat and security price information is derived from the Center for Research on Security Prices (CRSP). The analysts’ forecast of cash flow is obtained from the Investment Brokers Estimate Service (IBES), and consists of quarterly point forecasts of cash flows for the given period. Also, the Electronic Data Gathering and Retrieval System (EDGAR), and the Wall Street Journal (WSJ) are used to analyze financial notes and other associated firm information in order to control for such things as change of corporate form, change in ownership, or change in management. If any of these could be documented during the test period, the firm is subsequently eliminated from the study. DeFond and Hung (2003) provide a strong association between analyst cash flows forecast and capital intensity of the firms. A capital-intensive industry refers to an industry which requires substantial amount of capital for the production of goods. In the capital-intensive industries, the proportion of capital is much higher than the proportion of labor. Generally, the capital-intensive industries may produce a higher rate of return, and thus more profit, this leads, in turn, to greater capital investment. Capital intensive industries involve high levels of fixed cost. For this reason, they also involve a higher degree of risk. Three industries which have been consistently rated as capital intensive are; Utilities, Industrials, and Oil/Gas (Economy Watch, 2017). Conversely three industries categorized as being less likely capital intensive are; Healthcare, Banking/Finance, and Technology (Economy Watch, 2017). These two sample subsets form the basis of comparing relatively high capital-intensive industry firms with those not as capital intensive over the test period in order to relate them to cash flow forecasts. Forecasts for firms in these specific industries are then gathered for the test period and are summarized in Table 1.


Hypotheses Development Forecast accuracy In their analysis of forecast accuracy of corporate earnings, Sinha et al. (1997) utilize a matched-pair design in which the forecast accuracy of the same analyst is measured over time. Their study utilizes fourteen industries from the period 1984-1990 to assess accuracy of the forecast. Stunda (2016) uses the same methodology to determine forecast accuracy of groups of analysts by eight specific industries (i.e., four above average growth and four below average growth industries). Results for both studies indicate that forecast accuracy can indeed vary by industry. Although these prior studies assessed the analysts’ forecast accuracy of earnings, this study will attempt to do the same with respect to cash flow forecasts. This gives rise to the first hypothesis, stated in null form: H1:

There is no significant difference in analysts’ forecast accuracy of cash flow when assessed across industries.

Information content of accounting earnings Ball and Brown 1968, Beaver et al. 1979, Baginski and Hassell 1990, and a host of other researchers over the past five decades have found an association between accounting earnings and security returns of the firm. The strength of this association has commonly been described as an “earnings response coefficient” or ERC. To assess the ERC of firms in the selected six industries in the study sample, the model first employed by Ball and Brown in 1968 is used in order to establish that there is a correlation between earnings and security prices. This analysis will also be used to form a baseline comparison against which the information content of analysts’ forecast of cash flow will be measured. The Dow Jones News Retrieval Service (DJNRS) is used to identify the date that each firm released quarterly financial data for the study


periods. This date of data release is known as the event date. This leads to the second hypothesis, stated in the null form: H2:

The information content of accounting earnings is not significantly different for study firms across industries.

Information Content of Analysts’ Forecasts of Cash Flow As previously noted, the DeFond and Hung (2003) study, assesses firms which have cash flow forecasts associated with capital intensity and risk relative to industry peers. Neither the Defond and Hung (2003) study, nor any other study provides this analysis across industries. Different industries possess differing amounts of capital intensity and risk. An industry assessment along this line would give a better understanding of the effect of cash flow forecasts. The basis of this extension leads to the third hypothesis, stated in the null form: H3:

The information content of analysts’ forecasts of cash flow is not significantly different for study firms across industries. Test of Hypotheses and Results

Test of Hypothesis 1- Test of Forecast Accuracy of Cash Flows Across Industries Consistent with the methodology of Sinha et al. (1997), the following model is used to assess forecast accuracy among analysts: rapfeijt=

|Rjt

Fmjt)/Rjt|*100

-

|Rjt

(1) Where:

subscripts i, j, t denote analyst, firm and year, respectively Rjt is the j firm’s cash flows in year t

Fijt)/Rjt|*100


Fijt is the forecast of cash flow by analyst i for firm j in year t Fmjt is the forecast of the average analyst for the firm in question rapfeijt is each analyst’s relative absolute percentage forecast error, which is calculated as the absolute percentage forecast error of the average analyst minus that of the above average analyst. For below average analysts, the order of the two terms on the right hand side are reversed. A pooled, cross-sectional analysis is performed over the study period 2011-2015 and incorporating all analyst forecasts, by industry. Table 2 indicates the results of the analysis. Utilizing the Sinha et al. (1997) model, and breaking down the analysts’ forecast of cash flows by above average analysts and below average analysts, Panel A of Table 2 provides the results for above average analysts. Results indicate that for high capital-intensive industry (and therefore high risk) firms, above average analysts have a smaller average forecast error mean, which is significant at conventional levels. For less capital-intensive industries, the above average analysts have a greater forecast error and results are not significant at conventional levels. This indicates that this group of analysts is more precise in their forecast for high capitalintensive industry firms. Obrien (1990) surmises that the relatively more experienced analysts migrate to firms that not only are they more familiar with but are more difficult to forecast. This may help explain the results for this group of forecasters. Panel B of Table 2 provides results for the below average analysts. Results indicate just the opposite of the results found for above average analysts. This group of analysts has an average forecast error for cash flow that is smaller (and therefore more accurate) for less capitalintensive industry firms. Results are also significant at conventional levels. For high capitalintensive industry firms, the forecast error is greater and also not significant at conventional levels. Again, results might be attributable to the level of expertise within the group and the degree of difficulty associated with forecasts for high capital-intensive industry firms. As a result of these findings, hypothesis one which states that there is no significant difference in analysts’ forecast accuracy of cash flow when assessed across industries, must be rejected.


Test of Hypothesis 2- Test of Information Content of Accounting Earnings Across Industries Using the previously explained Ball and Brown1968 model to determine the ERC, the following model is established for determining information content: (2) Where: CARit

= Cumulative abnormal return firm i, time t

a

= Intercept term

UEit

= Unexpected earnings by specific industry and year in the sample

MBit

= Market to book value of equity as proxy for growth and persistence

Bit

= Market model slope coefficient as proxy for systematic risk

MVit

= market value of equity as proxy for firm size

eit

= error term for firm i, time t

The above regression is run multiple times for each industry and year in the sample. The coefficient “a” measures the intercept. The coefficient b1 is the traditional earnings response coefficient (ERC), found to have correlation with security prices in traditional market based studies (see Ball & Brown 1968). Unexpected earnings (UEi) is measured as the difference between the management earnings forecast (MFi) and security market participants’ expectations for earnings proxied by consensus analyst following as per Investment Brokers Estimate Service (IBES) (EXi). The unexpected earnings are scaled by the firm’s stock price (Pi) 180 days prior to the forecast: (3) Unexpected earnings are measured for each of the sample firms during the test period. The coefficients b2, b3, and b4, are contributions to the ERC for all firms in the sample. To investigate the effects of the information content of earnings on security returns, there must be some control for variables shown by prior studies to be determinants of ERC. For this reason, the variables represented by coefficients b2 through b4 are included in the study.


For each firm sample, an abnormal return (ARit) is generated around the event dates of 1, 0, +1 (day 0 representing the day that the firm’s financials were available per DJNRS). The market model is utilized along with the CRSP equally-weighted market index and regression parameters are established between -290 and -91. Abnormal returns are then summed to calculate a cross-sectional cumulative abnormal return (CARit). Results of correlating the ERC to security returns by industry and year are presented in Table 3. Table 3 provides results similar to extant accounting earnings literature which finds a correlation between accounting earnings and security returns. Each industry represented in the table, regardless of intensity of capital investment, reflects an ERC which is positive and significant at conventional levels in relation to security prices. This indicates that accounting earnings for these groups of industry firms possess information content and therefore have predictive value when correlated with security returns. All other variables in the regression are found not to be significant at conventional levels. For this reason, hypothesis 2, which states that the information content of accounting earnings is not significantly different for study firms across industries cannot be rejected. In addition, whenever regression variables are employed, there is a probability of the presence of multicollinearity within the set of independent variables which may be problematic from an interpretive perspective. To assess the presence of multicollinearity, the Variance Inflation Factor (VIF) was utilized. Values of VIF exceeding 10 are often regarded as indicating multicollinearity. In the test of hypothesis 2, a VIF of 2.2 was observed, thus indicating a nonpresence of significant multicollinearity Test of Hypothesis 3- Test of Information Content of Analysts’ Forecast of Cash Flow Across Industries In their assessment of analysts’ forecast accuracy, Call, Chen, and Tong (2009) determine a mean adjusted forecast error as follows: MAFEijt = -1 x (FEijt – Where:

/

subscripts i, j, t denote analyst, firm and year, respectively

(4)


FEijt is analyst i’s absolute earnings forecast error for firm j in year t is the mean absolute forecast error across all analysts following firm j in year t The equation is multiplied by -1 so that more positive (negative) values indicate that an analyst is more (less) accurate than the average analyst following the firm. Consistent with prior studies, Call et al. (2009) use mean-adjusted absolute forecast errors to enable the comparison of analysts’ forecasts across firms, industries, and time periods (Clement 1999; Jacob et al. 1999; Chen and Matsumoto 2006). Utilizing this same model, mean adjusted forecast errors of analysts’ forecasts of cash flows are determined for each industry. These averages are then regressed against cumulative abnormal security returns (CARs) in a similar regression as was used in hypothesis 2. The following regression model is generated: (5) Where: CARijt

= Cumulative abnormal return firm i, time t

a

= Intercept term

UEijt

= Mean adjusted forecast error by specific industry and year in the sample

Mbijt

= Market to book value of equity as proxy for growth and persistence

Bijt

= Market model slope coefficient as proxy for systematic risk

Mvijt

= market value of equity as proxy for firm size

eijt

= error term for firm i, time t

The above regression is run multiple times for each industry and year in the sample. The coefficient “a” measures the intercept. The coefficient b1 is the response coefficient measuring the correlation between the pooled cash flow forecasts to firms’ security prices. The coefficients b2, b3, and b4, are potential contributions to information content of the model. For each firm sample, an abnormal return (Arit) is generated around the event dates of -1, 0, +1 (day 0 representing the day that the firm’s financials were available per DJNRS). The market model is utilized along with the CRSP equally-weighted market index and regression parameters are established between -290 and -91. Abnormal returns are then summed to calculate a cross-sectional cumulative abnormal return (CARit).


Results of the test for hypothesis 3 are found in Table 4. Table 4 provides results when assessing the response coefficient representing mean adjusted forecast error for the analysts’ projection of cash flows by industry and year. When analyzing capital intensive industries, the response coefficients are positive and significant at conventional levels. This indicates that analysts’ forecasts of cash flow for these groups of industry firms possess information content and therefore have predictive value when correlated with those returns. With respect to industry firms that are not as capital intensive, the response coefficients are still positive, but to a lesser extent. In addition, the coefficients are not significant at conventional levels across all industries and years. This implies that investors tend to discount the analysts’ forecasts of cash flow to a greater extent when it comes to less capital-intensive industries. All other variables in the regression are not significant at conventional levels. Since more capital intensiveness implies more risk, the results may indicate that investors place greater emphasis on the analyst forecast of cash flows for these types of industry firms, thus the greater correlation to security prices. For this reason, hypothesis 3, which states that the information content of analysts’ forecasts of cash flow is not significantly different for study firms across industries is rejected. Also, to assess the presence of multicollinearity, the Variance Inflation Factor (VIF) was utilized. Values of VIF exceeding 10 are often regarded as indicating multicollinearity. In the test of hypothesis 3, a VIF of 2.5 was observed, thus indicating a non-presence of significant multicollinearity Discussion This study extends the research of Defond and Hung (2003), who found significance between analysts’ forecasts of cash flow and security returns, but failed to find significance between accounting earnings and security returns. The later finding contradicts previous extant studies of accounting earnings dating back to Ball and Brown (1968). Defond and Hung (2003) also conclude that firms within similar industry membership exhibit the same similarities as stated above. No mention is made in their study regarding comparison across industries.


The current study focuses on six specific industries, three industries with relatively high capital-intensive investment, and three industries with relatively lower capital-intensive investment. The rationale is that Defond and Hung (2003) infer that capital intensity also is related to risk, and risk is related to the significance of the analysts’ forecast of cash flows. Findings indicate that with respect to accuracy of analysts’ forecasts of cash flow, above average analysts are more accurate in forecasting cash flows for relatively high capital-intensive industry firms, while below average analysts seem to possess an advantage of accuracy for relatively low capital-intensive industry firms. Prior research finds that analysts of the former group tend to have an experience advantage in forecasting for capital intensive, and thus riskier, industry firms. With respect to assessing accounting earnings relationship to security returns, results contradict the Defond and Hung (2003) study and support prior studies of accounting earnings. Accounting earnings for the test periods and across industries studied are found to convey information content to the investor at levels which are significant at conventional levels. Regarding the assessment of information content of the analysts’ forecasts of cash flows, findings indicate that for relatively high capital-intensive industry firms, there is a positive and significant relationship between the analysts’ forecast of cash flow and security prices across all industries and years studied. However, for those industries which are less capital intensive, the relationship, although positive, is not significant across all industries and years studies. Overall results indicate that accounting earnings possess information content to the investor when associated with firms’ security prices, regardless of industry. When assessing the analysts’ forecast of cash flows, industry membership, along with analyst group (i.e., above or below average) seem to have a bearing on strength of information content when relating the forecast to security prices of the firms. These results may be important for investors when choosing whether or not to use an analyst, the industry in which the analyst is proficient, and the expertise of the analyst.


Author Biography Dr. Ron Stunda is Professor of Accounting and Department Chair at Valdosta State University in Valdosta, Georgia. His primary area of interest is market-based financial accounting. He has published in numerous accounting and finance journals and is a reviewer and editorial board member of several academic journals.

References

Ajinkya, B., R. Atiase, & Gift, M. (1991). Volume of trading and the dispersion in financial analysts’ earnings forecasts. The Accounting Review, 66, 389-401. American Institute of Certified Public Accountants (1993). Special Committee on Financial Reporting, June. Baginski, S., & Hassell, J. (1990). The market interpretation of management earnings forecasts as a predictor of subsequent financial analyst forecast revision. The Accounting Review, 65, 175-190. Ball, R., & Brown, P. (1968). An empirical evaluation of accounting income numbers. Journal of Accounting Research, (Autumn), 159-178.

Barry, C., & Brown, S. (1985). Differential information and security market equilibrium. Journal of Financial and Quantitative Analysis, 20, 407-422. Barth, M., Cram, D., & Nelson, K. (2002). Accruals and the prediction of security prices. The Accounting Review, 76, 27-58. Beaver, W, Clarke, R., & Wright, W. (1979). The Association between unsystematic security returns and earnings forecast errors. Journal of Accounting Research, (Autumn), 316-340.

Bennett, J., & Sias, R. (2007). Why company-specific risk changes over time. Financial Analysts Journal, 62, 89-100. Bradley, D., Jordan, B., & Ritter, J. (2003). The quiet period goes out with a bang. Journal of Finance, 58, 1-36. Brennan, M., & Subrahmanyam, A. (1995). Investment analysis and price formation in securities markets. Journal of Financial Economics, 38, 361-381. Brown, G., & Kapadia, N. (2007). Firm-specific risk and equity market development. Journal


of Accounting and Economics, 12, 36-58. Brown, L., & Rozeff, M. (1980). Analysts can forecast accurately! Journal of Portfolio Management, 31-34. Butler, K., & Lang, L. (1991). The forecast accuracy of individual analysts. Journal of Accounting Research, 150-156. Call, A. (2008). Analysts’ cash flow forecasts and the relative informativeness and pricing of the cash component of earnings. (Working paper). University of Georgia. Call, A., Chen, S., & Tong, Y. (2009). Are analysts’ earnings forecasts more accurate when accompanied by cash flow forecasts? Revenue Accounting Study, 14, 358-391. Chen, S., & Matsumoto, D. (2006). Favorable versus unfavorable recommendations: The impact on analyst access to management-provided information. Journal of Accounting Research, 44, 657–689. Chung, K., McInish, T., Wood, R., & Wyhowski, D. (1995). Production of information in bidask spreads: evidence from analysts’ forecasts. Journal of Banking and Finance, 19, 1025-1046. Clement, M. (1999). Analyst forecast accuracy. Journal of Accounting and Economics, 27, 285303. Clement, M., & Tse, S. (2005). Financial analyst characteristics and herding behavior in forecasting. Journal of Finance, 1, 307-341. Cliff, M., & Denis, D. (2004). Do initial public offering firms purchase analyst coverage with underpricing? Journal of Finance, 59, 2871-2901. Coggin, T., & Hunter, J. (1989). Analyst forecasts of EPS and EPS growth. Working Paper, Michigan State University. Collins, D., & Kothari, S. (1994). Lack of timeliness and noise as explanations for the low returnearnings associations. Journal of Accounting and Economics, 18, 289-324.

Dechow, P. (1998). Accounting earnings and cash flows as measures of firm performance: the role of accounting accruals. Journal of Accounting and Economics, 18, 3-42. Defong, M., & Hung, M. (2003). Am empirical analysis of analysts’ cash flow forecasts. Journal of Accounting and Economics, 35, 73-100.


Economy Watch (2017). Capital intensive industries. June, 1-5. Ertimur Y. & Stubben, S. (2005). Analysts’ incentives to issue revenue and cash flow forecasts. (Working paper). Duke University and University of North Carolina at Chapel Hill. Fortin, R., & Roth, G. (2007). Analyst coverage of small cap firms in a period of brokerage firm retrenchment. Journal of Business and Economic Research, 5, 61-68. Glosten, L., & Milgrom, P. (1985). Bid, ask, and transaction prices in a specialist market. Journal of Financial Economics, 14, 71-100. Graham, J., Campbell, H., & Rajgopal, S. (2005). The economic implications of corporate financial reporting. Journal of Accounting and Economics, 40, 3-73. Hong, H., Kubik, J., & Solomon, A. (2000). Security analysts’ career concerns and herding of earnings forecasts. RAND Journal of Economics, 31, 121-144. Irvine, P., & Pontiff, J. (2008). Idiosyncratic return volatility, cash flows, and product market competition. Review of Financial Studies, 1149-1177. Jacob, J., Lys, T., & Neale, M. (1999). Expertise in forecasting performance of security analysts. Journal of Accounting and Economics, 28, 51–82. Lang, M., & Lundholm, R. (1996). Corporate disclosure policy and analysis behavior. The Accounting Review, 71, 467-492. Lev, B. (1989). On the Usefulness of Earnings and Earnings Research. Journal of Accounting Research, 27, 153-192.

Livnat, J., & Zarowin, P. (1990). The incremental information content of cash flow components, Journal of Accounting and Economics, 13, 25-46. McNichols, M., & O’Brien, P. (1997). Self-selection and analyst coverage. Journal of Accounting Research, 35, 167-199. Merton, R. (1997). A simple model of capital market equilibrium. Journal of Finance, 42, 483-510. McInnis, J., & Collins, D. (2008). Do cash flow forecasts deter earnings management? (Working Paper). University of Texas at Austin and University of Iowa. Morck, R., Yung, B., & Yu, W. (2009). The information content of stock markets: Why do emerging markets have synchronous stock price movements? Journal of Financial


Economics, 5, 215-260. Nichols, D. (1989). The Handbook of Investor Relations. Homewood IL: Dow Jones-Irwin. Obrien, P. (1987). Individual forecasting ability. Managerial Finance, 3-9. Obrien, P. (1990). Forecast accuracy of individual analysts in nine industries. Journal of Accounting Research, 286-304. O’Brien, P., & Bhushan, R. (1990). Analyst following and institutional ownership. Journal of Accounting Research, 28, 55-82. Rajan, R., & Servaes, H. (1998). Analyst following of initial public offerings. Journal of Finance, 52, 507-529. Richards, R. (1976). Analysts’ performance and the accuracy of corporate earnings forecasts. The Journal of Business, 350-357. Schipper, K. (1991). Analysts’ forecasts. Accounting Horizons, 4, 105-121. Sinha, P, Brown, L., & Das, S. (1997). A re-examination of financial analysts’ differential earnings forecast accuracy. Contemporary Accounting Research, 30-44. Sloan, R. (1996). Do stock prices fully reflect information in accruals and cash flows about future earnings? The Accounting Review, July, 289–315. Stickel, S. (1992). Reputation and performance among security analysts. The Journal of Finance, 1811-1836. Stunda, R. (1996). An investigation of cash flow proxies in accounting research. Journal of Accounting and Finance, 4, 19-31. Stunda, R. (2015). Does analyst coverage affect bias and information content of management forecasts and are results comparable across industries? Global Journal of Management and Business Research, 15, 4, 1-10. Stunda, R. (2016). Financial analyst accuracy: An examination by industry. Global Journal of Management and Business Research, 16, 2, 1-8. Trueman, B. (1994). Analyst forecasts and herding behavior. Review of Financial Studies, 7, 97124. Wilson, G. (1986). The relative information content of accruals and cash flows: Combined


evidence at the earnings announcement and annual report release date. Journal of Accounting Research, 24, 165-200. Wilson, G. (1987). The incremental information content of the accrual and funds components of earnings after controlling for earnings. The Accounting Review, 62, 293-321.

Tables and Figures

Table 1 Sample Summary, Forecast Period 2011-2015 Industry Utilities Industrials Oil/Gas Healthcare Banking/Finance Technology

High Capital Intensity Firms Forecasts 51 204 65 260 38 152

Low Capital Intensity Firms Forecasts

57 32 49

228 128 196


Table 2 Analyst Accuracy by Industry, 2011-2015 Panel A- Above Average Analysts Industry Average Mean Utilities 0.49 Industrials 1.02 Oil/Gas 0.61 Healthcare 1.55 Banking/Finance 2.01 Technology 1.98

t-test 1.87 1.71 1.91 0.66 0.39 0.42

Panel B- Below Average Analysts Industry Average Mean t-test Utilities 1.76 0.57 Industrials 2.21 0.34 Oil/Gas 1.89 0.40 Healthcare 0.71 2.10 Banking/Finance 0.64 2.12 Technology 0.58 1.90 Note. Model: rapfeijt = |Rjt – Fmjt)/Rjt|*100 - |Rjt – Fijt)/Rjt|*100.

Probability 0.05 0.01 0.05 -

Probability 0.10 0.10 0.05


Table 3 b1 Variable Assessment- ERC by Industry and Year 2011-2015

Industry

2011

2012

2013

2014

2015

ERC

p ERC value

p ERC value

p ERC value

p ERC value

p value

Utilities

.059

2.40c

.062

1.87b

.058

2.39c

.066

1.79b

.072

1.85b

Industrials

.031

2.31c

.033

2.41c

.039

2.38c

.034

1.88b

.040

2.33c

Oil/Gas

.069

1.71a

.070

1.82b

.064

1.65a

.066

1.81b

.068

1.66a

Healthcare

.053

1.64a

.062

1.88b

.061

1.67a

.055

1.79b

.071

1.64a

Banking/Finance

.041

1.99b

.044

1.84b

.039

2.21c

.042

1.84b

.049

1.91b

Technology

.092

1.62a

.099

1.57a

.095

1.66a

.091

1.84b

.096

1.63a

Note. Model: . a b c Significant at the .01 level. Significant at the .05 level. Significant at the .10 level.

Table 4 b1 Variable Assessment- Average Analysts’ Forecast of Cash Flows Associated with Security Price Returns, 2011-2015

Industry

2011

2012

2013

2014

2015

RC

p value

RC

p value

RC

p value

RC

p value

RC

p value

Utilities

.032

1.86b

.029

1.91b

.033

1.69a

.039

1.70b

.040

1.64a

Industrials

.047

2.40c

.041

1.86b

.048

1.79b

.041

1.85b

.049

1.62a

Oil/Gas

.048

1.66a

.052

1.61a

.060

1.77b

.055

1.62a

.061

1.64a

Healthcare

.038

0.83

.031

2.39c

.033

0.68

.043

0.92

.037

0.69

Banking/Finance

.019

0.77

.018

0.82

.022

0.90

.016

2.27 c

.022

2.33c

Technology

.027

1.88b

.020

0.49

.026

2.41c

.019

0.79

.025

1.84b

Note. Model: . a b c Significant at the .01 level. Significant at the .05 level. Significant at the .10 level.


“Data is Extremely Useful!” Preservice Teachers’ Growth in Literacy Assessment and Instruction Catherine M. Kelly St. Catherine University

Abstract Using a case study framework, the author studied the confidence and proficiency of preservice teachers (PTs) in the area of literacy assessment and instruction. The mixed methods study was conducted in a U.S. university literacy methods course, taught both on campus and at a partner K-6 elementary school. Through the Case Study Report, the culminating signature assignment of the course, PTs develop and use assessment tools to measure student learning, organize literacy instruction with attention to the diverse strengths, needs, and interests of students, and work collaboratively and productively in an elementary school setting. Analysis of survey and assessment results indicate that preservice teachers feel more prepared for the realities of assessment and instruction in their future teaching, they better understand literacy development in the context of classroom instruction, and they are more confident in their teaching of literacy as a result of the field-based case study assignment, though they need additional support developing expertise in assessment knowledge. Keywords: preservice teachers; literacy; assessment; literacy instruction; mixed methods Introduction Beginning teachers must know and be able to do many things. According to the Council of Chief State School Officers (CCSSO) in their report “Our Responsibility, Our Promise”:


Learner ready teachers have deep knowledge of their content and how to teach it; they understand the differing needs of their students, hold them to high expectations, and personalize learning to ensure each learner is challenged; they care about, motivate, and actively engage students in learning; they collect, interpret, and use student assessment data to monitor progress and adjust instruction; they systematically reflect, continuously improve, and collaboratively problem solve; and they demostrate leadership and shared responsibility for the learning of all students. (2012, pp. iii-iv). With this impressive list of knowledge, skills, and dispositions critical for day one of P12 teaching, preservice teacher education programs are under increased pressure to ensure their programs are designed to address each of the above competencies. Inlcuded in the list is the ability to understand and appropriately use assessment data to guide instruction. Therefore, developing preservice teachers’ assessment knowledge is a critical aspect of preservice teacher education (Mayor, 2005; Popham, 2009). Teachers with assessment knowledge “understand how to construct, administer, and score reliable assessments and communicate valid interpretations about student learning” (DeLuca & Bellara, 2013, p. 356). Teacher education programs are increasingly designed to develop preservice teachers’ understanding of assessments (Popham, 2009) and this knowledge supports beginning teachers’ ability to use student assessment data in order to plan effective instruction. Developing assessment knowledge, in context of classroom practice through a Case Study Report assignment, is the focus of this research. Literature Review In the past decade, there has been an increase in reports, essays, and studies written about what effective literacy teachers should know and be taught in teacher education programs (Blair, Rupley, & Nichols, 2007; CCSSO, 2012; Dillon, O’Brien, Sato, & Kelly, 2010; Fillmore & Snow, 2002; International Reading Association, 2003; Moats, 1999; Risko et al., 2008; Snow, Griffin, & Burns, 2005; Strickland, Snow, Griffin, Burns, & McNamara, 2002). Maloch et al. (2003) found in their review that teacher education does impact beginning teachers, though there is more to learn about what literacy teacher education programs look like and the knowledge


bases of preservice teachers (PTs) influencing instruction (Hoffman et al., 2005; Snow et al., 2005). As called for in the International Reading Association’s position statement (2000), “effective teachers of reading are knowledgeable, strategic, adaptive, responsive, and reflective” (p. 1). In order to build to that end, PTs benefit from supervised relevant field experiences (Lacina & Block, 2011) to develop knowledge and skills in assessment required in particular for teachers of reading (Snow et al., 2005). According to Snow et al. (2005), teachers need to understand the basic principles underlying quality assessment, be familiar with a wide range of assessment tools and practices, know how to use assessment outcomes to inform instructional decisions, and have skills in communicating assessment results. PTs develop knowledge and skills regarding students, teaching, and learning when engaged with teacher educators who can draw connections to theory through “reflective analyses in relation to what was taught or advocated by the methods course” (Clift & Brady, 2005, p. 316). While teacher education embedded in practice is not a new idea (Zeichner, 2012), PTs learn best when provided “explicit teaching and modeling in teaching practices, opportunities to discuss and collaborate with others as new information is learned, and long-term, focused work on new concepts to enable deep learning to occur” (Dillon et al., 2010, p. 650). In addition to effective content and contexts for PT learning, evaluation of the ability of PTs to apply their learning in context is essential. However, while there is widespread agreement that highly effective teachers are the key to improving the education of P-12 students, there is not agreement about how best to evaluate preservice teachers to determine if they are effective (Darling-Hammond, 2010). The assessment of PTs’ teaching situated in performance tasks has become a necessary component of preservice teacher education. The adoption of the Education Teacher Performance Assessment (edTPA™) in 38 U.S. states and the District of Columbia has significant implications for the preparation of teachers. The edTPA, a multiplemeasures, subject-specific assessment, evaluates a teacher candidate’s success in planning, teaching, assessing, and analyzing her/his instruction during student teaching (AACTE, 2016). In order to be prepared for this assessment, teacher educators in the United States must find ways to support PTs as they learn to plan, teach, assess, and reflect effectively for student learning.


Assessment knowledge, as used in this paper and to guide the project under study, is drawn from Willis, Adie, and Klenowski (2013): Assessment literacy is a dynamic, context dependent social practice that involves teachers articulating and negotiating classroom and cultural knowledges with one another and with learners, in the initiation, development, and practice of assessment to achieve the learning goals of students. (p. 242) PTs must have experiences to support their knowledge of assessments and using data effectively (Ellis & Smith, 2017; Ferguson, 2017; Reeves & Honig, 2015), as assessment knowledge is expected for practicing teachers (DinanThompson & Penney, 2015; Gillet & Elligson, 2017). In order to be prepared for the complexities of classroom practice, PTs need experience with “the multitude of data sources that inform teachers’ data-driven decision making” (DeLuca & Bellara, 2013, p. 359). The course and course assessment described here are an attempt to provide PTs with this kind of experience within their methods course sequence in advance of student teaching to support the development of assessment knowledge. Methodology In the current context for teacher education, I was interested in how PTs’ assessment knowledge in the area of literacy development is impacted by a major course assignment in the field, designed to provide PTs the opportunity to apply course learning in assessment in order to assess, plan, and instruct K-6 students. This mixed methods study was designed to research the confidence and proficiency of preservice teachers (PTs) in the area of literacy assessment and instruction. The study was guided by the following research questions: 1. How do elementary PTs conceptualize their knowledge about literacy assessment? 2. Does elementary PTs’ confidence in literacy assessment and instruction change as a result of the Case Study assignment? 3. Based on the rubric for the Case Study assignment, do PTs meet the expected criteria for knowledge in literacy assessment and instruction? 4. Is the Case Study assignment effective in improving PTs’ ability to conduct and interpret literacy assessments and plan instruction based on the results?


These questions were designed to help me both understand preservice teachers’ development of assessment knowledge within this literacy methods course, as well as evaluate the effectiveness of a course assignment designed to engage preservice teachers in the work of literacy assessments. This study was conducted as a mixed-methods research design using a concurrent triangulation strategy (Burke, Johnson & Onwuegbuzie, 2004; Cresswell, Plano-Clark, Gutman, & Hanson, 2003). The research data included both quantitative and qualitative data, integrated at the point of data collection, with equal priority given to both types of data, and an implicit theoretical perspective (Cresswell et al., 2003). The study includes both affective instrumentation (Henk & McKenna, 2004) as well as rubric evaluation results. In addition to my role as researcher, I served as the instructor of the teacher education literacy methods course at a small, Midwestern, liberal arts university; participants included the 11 female PTs enrolled as elementary education majors in the course. The undergraduate college at the University is a women’s college; therefore, only female students are enrolled in the course. Participants were in their second of three terms of coursework prior to student teaching, enrolled in EDUC 3490: Literacy Methods for Teaching in the Intermediate Grades (see Table 1). Participants included traditional college age juniors and seniors, as well as non-traditional students returning to college for their Bachelor of Arts or Bachelor of Science in Elementary Education. Because of the embedded fieldwork and supervision requirements of the course, the course is capped at 15 students each term, and all students enrolled in the course participated in the study. Literacy Methods for Teaching in the Intermediate Grades (EDUC 3490) is a course that explores theories, methods, and materials used to develop children’s literacy in all subject areas, with an emphasis on reading, writing, and speaking for children in grades 3-6 (approximately 8-12 years old). The course assumes that effective teachers of language arts are knowledgeable, literate, and curious people who develop and maintain a classroom community in which they and their students learn together. Teacher education programs in the state in which the University is located are required to align licensure programs to the state Standards of Effective Practice. While the course is designed to address many state standards for teaching licensure, for the purposes of the experience and assignment under study, PTs are taught and assessed on the following standards:


8710.2000 E. A teacher of children in kindergarten through grade 6 must have knowledge of and ability to use a variety of assessment tools and practices to plan and evaluate effective reading instruction, including: (1) formal and informal tools to assess students’: (d) knowledge of and skills in applying phonics and other word identification strategies, spelling strategies, and fluency; (e) vocabulary knowledge in relation to specific reading needs and texts; (f) comprehension of narrative and expository texts and the use of comprehension strategies, including determining independent, instructional, and frustration reading levels; (2) formal and informal tools to: (a) plan, evaluate, and differentiate instruction to meet the needs of students from various cognitive, linguistic, and cultural backgrounds; and (b) design and implement appropriate classroom interventions for struggling readers and enrichment programs for gifted readers; (4) the ability to communicate results of assessments to specific individuals in accurate and coherent ways that indicate how the results might impact student achievement; (5) the ability to administer selected assessments and analyze and use data to plan instruction through a structured clinical experience linked to university reading course work; and (6) the ability to understand the appropriate uses of each kind of assessment and the concepts of validity and reliability. (Revisor of Statutes, State of Minnesota, 2016) For the EDUC 3490 course, PTs are taught for the first month of the course on campus, and then the remaining three months of the semester are taught on-site at an elementary partner school (the Literacy Lab experience). The partner school setting for the field experience is West Creek Community School (pseudonym), an urban, pre-kindergarten through sixth grade public elementary school serving approximately 550 students. West Creek Community School is a “strategic partner� (NCATE, 2010) for the University, selected in conjunction with its large urban school district in order to develop clinical preparation for preservice teachers that integrates theoretical knowledge with practical application. The student population of West Creek includes 30.1% Asian / Pacific Islander, 27.4% Black, 22.5% Hispanic, 16.8% White, and 3.2% American Indian. Forty-four percent of the students are designated English Learners,


13.2% receive Special Education services, and 85.7% receive Free / Reduced Lunch. In 2014, 29.4% of the students at West Creek scored at a proficient level on the statewide reading assessments, far below the statewide average of 58.8% and the district average of 38% proficient. According to the state’s Multiple Measures Rating, given to all schools in the state and measures school performance in the areas of proficiency, growth, achievement gap reduction, and graduation rates, West Creek was identified as a Focus School, part of the 10% lowest performing schools that receive Title I funding, as well as the 10% making the largest contribution to the state achievement gap. For EDUC 3490, the course meets once per week for four hours each session. For each course session, the instructor meets with the PTs for roughly one and a half hours and then PTs transition into elementary classrooms to observe literacy instruction and work with a case study student in the fieldwork classroom. The case study student is assigned by the classroom teacher with guidelines from the instructor. The guidelines recommend the classroom teacher identify a K-6 student who does not represent one of the most struggling or most advanced readers in the class, but represents roughly average grade-level reading skills. The course is structured to provide PTs experience with assessments utilizing a gradual release of responsibility model – providing explicit teaching and modeling, guided practice, and then support in independent application (Kindle & Schmidt, 2013). As instructor of the class, I supervise the PTs throughout their Literacy Lab experience at the partner school and meet individually with PTs as needed to support their learning about literacy instruction and assessment. Preservice teachers learn to conduct and analyze literacy assessments and plan instruction based on the data they collect by organizing literacy instruction with attention to the diverse strengths, needs, and interests of students, and work collaboratively and productively in an elementary school setting, with students, faculty, and administrators throughout the Literacy Lab experience. In order to develop PTs’ knowledge and skills in conducting, analyzing, and using data to inform instruction in literacy, the course, and in particular the Case Study assignment, is designed to help answer the following questions: (a) Why do we assess literacy? (b) What do we assess when we assess literacy? and (c) How (and where and when) do we assess literacy? (Afflerbach, 2007). This case study assignment serves as the signature assignment for the class, designed “for use prior to and during field experiences to provide formative opportunities to


engage in practice teaching that reflects the outcomes measured by the edTPA, as well as other valued knowledge and skills” (Stillman, Ragusa, & Whittaker, 2015, p. 184). In their work with a case study student, PTs conduct and analyze four literacy assessments: an interest inventory and interview, a Words Their Way (Bear, Invernizzi, Templeton, & Johnston, 2011) word study assessment, an informal reading inventory assessment, and writing samples to assess. PTs learn about the theory behind each of these assessments, and are given scaffolded experiences in the administration and analysis of each of these assessments. PTs then learn to use their analysis of the data from the various assessments to plan instruction accordingly. After experiencing these assessments in the context of the university classroom, PTs then conduct and analyze the assessments in their fieldwork classroom with their case study student. PTs write reflections on each assessment and initial interpretations of data after each assessment, getting feedback from me on their process and analysis as they complete each assessment. Finally, PTs compile the assessment data to write a report with an instructional plan given all the assessment data collected, known as the Case Study Report. This assignment builds on assessment instruction from PTs’ first term of methods coursework, embedded in INDI 2440: Choosing and Using Books for Children (see Table 1). In this primary literacy methods and children’s literature course I also taught this cohort of PTs where they learn about oral language and complete an oral language assessment with a student in their field placement. The purpose of the Case Study Report, then, is to help preservice teachers develop an understanding of literacy assessments within a contextual model, understanding the complexity of literacy development, individual students, and instructional methods for literacy (McKenna & Stahl, 2003). Preservice teachers experience literacy assessment in a context supporting the idea that assessment is not “something that is being done to students [but rather] something that is being done with and for the students” (Klenowski, 2009, p. 89). At the University where this study took place, PTs are required to complete the edTPA in order to apply for a state teaching license, though at this time a specific score is not required in order to obtain a license. The University teacher education program has embedded aspects of the edTPA across courses and field experiences throughout the program in order to prepare the PTs for this performance assessment as well as to “assess and cultivate candidates’ readiness for teaching practice” (Stillman et al., 2015, p. 173). The Case Study Report is evaluated using a


rubric (Appendix A) developed to align with assessment characteristics of the edTPA. This allows the teacher eduaction program to analyze how students are progressing on goals related to the edTPA in the middle of their methods course sequence. Three primary data sources were utilized for this study: (a) pre-assessment survey of PTs’ confidence in and expectations of learning about assessment through the Case Study Report (Appendix B), (b) post-assessment surveys (Appendix B), and (c) case study assignment rubric ratings (Appendix A). The rubric used for evaluating the Case Study Report was designed using language from edTPA rubrics, in order to align with expectations for teacher candidates in their student teaching experiences. PTs receive feedback intended to provide them with areas of strength and in which to grow as they move into their final term of methods coursework before student teaching. Categories of evaluation include the introduction and context for learning, assessment results and analysis, instructional recommendations, additional information, reflection, and conventions. Because this research was conducted by the instructor of the course, there were ethical questions to consider. While I introduced the study and answered any questions about the research, in order to minimize undue influence and maintain voluntariness, a colleague unrelated to the study collected the consent forms, which were not shared with me until after final grades had been submitted. Since the assignment and surveys are included in the normal course of the class, those students who chose not to participate did not lose any educational opportunities and grades were not impacted because of participation. Surveys were collected anonymously, and case study rubric scores are reported in the aggregate to protect participant identities. Data were analyzed concurrently utilizing both quantitative and qualitative strategies. Open-ended responses on the surveys were analyzed qualitatively. Qualitative analysis strategies included thematic analysis, reading and rereading of the open-ended responses on the pre- and post-surveys, and a development of patterns (Miles, Huberman, & Saldaùa, 2014). Initial open coding with the responses was done line-by-line and then question-by-question allowing for detailed and generative coding (Strauss & Corbin, 1990). Analysis then moved between open and axial coding in order to make new categories (Miles et al., 2014). The categories included: focus on correctness in assessment administration, connections to coursework, value of assessments, assessment purposes, meeting student needs, and areas for growth. In addition,


descriptive statistics were generated for the rubric scores and Likert-scale responses on pre- and post-surveys, and data displays (Miles et al., 2014) were created to both represent and analyze the data. Results Preservice Teachers in EDUC 3490 showed changes in confidence and were able to demonstrate growing proficiency in literacy assessment implementation and analysis. In addition, students’ responses to questions and reflections about what they hoped to learn (preassessment) and what they did learn (post-assessment) about literacy assessments grew in complexity from pre- to post-survey. Confidence in Literacy Assessments The results of the Likert-scale analysis indicate that PTs’ confidence grew in conducting, analyzing, and using data from literacy assessments as a result of the Case Study Report assignment. When comparing results between the three areas of assessments administration (conducting, interpreting, and using assessment data), PTs indicated highest levels of confidence in conducting assessments in the post-assessment survey with a mean of 3.45 on a 4.0 scale (see Figure 1). Because PTs had multiple experiences conducting assessments both in class and with case study students, as well as an explicit protocol for administration of assessments, PTs felt most confident in this area. PTs showed some growth in their confidence in their ability to interpret the results of the assessments of their case study student, with a mean post-test survey score of 3.0 on a 4.0 scale (see Figure 2). However, confidence in using assessment data to plan instruction was the area PTs felt least confidence in, according to the post-assessment survey, with a mean post-test survey score of 2.9 on a 4.0 scale (see Figure 3). Though they had practiced analysis and implementation of instruction based on assessment results during class, their confidence may have been lessened because the results were from an actual student they worked with in a classroom, providing additional consequence to their decisions.


An independent-samples t-test was conducted to compare the pre-test and post-test conditions. There was a significant difference for confidence in conducting assessments in the pre- (M = 2.5, SD = .52223) and post-test (M = 3.45, SD = .52223) scores; t = 1.0, p = 0.001. There was not a significant different in confidence in interpreting assessment data in the pre- (M = 2.3, SD = .82020) and post-test (M = 3.0, SD = .44721) scores; t = .006, p = .067. In the area of using assessment data, there was a significant difference in pre- (M = 2.08, SD = .87386) and post-test (M = 2.90, SD = .53936 scores); t = .178, p = .029. Learning from Literacy Assessments Pre-assessment survey. Prior to beginning the Case Study Report assignment in EDUC 3490, PTs reflected on what they hoped to learn from the experience on the pre-assessment survey. In the pre-assessment survey, PTs indicated little prior knowledge about assessments in literacy. Responses tended to be brief and general. For example, one PT wrote, “I’m hoping to learn how to correct, create, and perform a literacy assessment.” A majority (9/11) of the PTs were concerned with appropriate selection and administration of literacy assessments. For example, a PT wrote, “I hope to learn how to accurately give a literacy assessment as well as practice with it.” Another PT responded, “I would love to learn more about determining which assessments are the most appropriate to use for the concepts being addressed.” In addition, a PT responded, “I hope to learn when the appropriate time is to use what assessment.” PTs were also concerned with learning about interpreting literacy assessment results (9/11). For example, one PT indicated, “I hope to learn to understand and figure out what a student needs.” Another PT stated that, “First and foremost, I want to learn how to accurately and confidently interpret assessment results with ease.” Finally, PTs were hoping to learn about planning effective individualized instruction using assessment results (10/11). This included ideas such as using results correctly and the ability to use data to help students achieve goals. For example, one PT wrote, “I just really hope to learn from experience. Every child is different so every literacy instruction needs to be individualized.” One PT reflected that, “Because we have talked about how one assessment is not the determinant of all things literacy, I want to learn more about how to thoroughly explore


and determine what to pull from assessments.” Another PT hoped to learn, “how to properly strategize personalized activities to aid their learning.” Additionally, a PT indicated, “I hope to learn how to read the results and what to do after the results. What should we do with the results?” PTs understood before embarking on this series of assessments that the goal was to plan effective instruction based on assessment results, though they did not yet feel confident in doing so. Across the open-ended questions on the survey, correctness was a theme that came up throughout the pre-assessment. “I am nervous about providing correct instruction for students and making sure I provide them with work that will be beneficial and appropriate,” responded one PT. Another wrote she wished to learn, “how to understand results correctly and gain the best knowledge on that student to help them.” Conducting, interpreting, and using assessment data correctly was a primary focus for PTs prior to the Case Study Report. PTs have a sense that these assessments are powerful tools in learning about students, but have not yet learned the most effective way to select, implement, and interpret assessment results. As one PT admitted, “I have a good idea of how to do it from class, however I don't know if I've learned anything until I actually get to try it out on a student.” Post-assessment survey. After completing the Case Study Report, PTs had much more to write about what they learned through the experience than they had been able to write preassessment. Overall, PTs indicated they learned the value of literacy assessments (8/11). PTs wrote, “The literacy assessments that we conducted were very helpful in learning how to guide instruction for a student,” and “I learned how valuable literacy assessments are to individual students’ success in literacy development.” Another PT responded, “Data is extremely useful!!! It helps aid the teacher in figuring out what the student should be working on.” In addition, a PT reflected, “Assessments can greatly guide literacy instruction.” While recognizing the importance, some PTs also indicated they found literacy assessments to be challenging to implement. For example, a PT stated, “I learned that there is a lot of work that goes into assessments, but in the long run, they are essential tools in analyzing reading and writing.” Another PT wrote, “I learned how complicated the interpretation is and how important it is to collect accurate information while giving the assessment.” Before completing the Case Study


series of four assessments, students only had a vague understanding of what it meant to administer assessments and the value of the data collected, and their focus was mostly on completing assessments “correctly.” After completing the assessment series, PTs were much better able to recognize challenges and benefits of conducting a series of literacy assessments. More specifically, PTs also indicated they had learned about the ways assessments can guide instruction (9/11). For example, one PT discussed the importance of multiple assessments to guide instruction in her statement, “My efforts must be both intentional and thoughtful and that I must actively use a variety of assessment tools in order to accurately represent a student’s needs.” Another PT indicated, “Doing quality assessments and using quality results is the best way to plan instruction. They often give an exact place to start.” PTs also indicated they had learned it was important to remain flexible in their interpretations as they collected assessment data. To illustrate, one PT stated, “Making mindful interpretations of assessment results as well as remaining flexible with those interpretations is a key factor in providing opportunity for growth in students.” Another PT made a connection to students’ interests in instruction when she stated she had learned, “assessments can guide instruction towards things that will interest your students and help them learn.” While all PTs indicated they had learned a great deal about using assessment data to provide instruction for students, this was also an area in which the PTs indicated they still had room to grow. For example, one PT wrote, “This is the one area that I would like to become more confident in. I understand how to do the assessment and interpret the data, but worry about my instruction. I feel more confident than before, but would still like to grow in this area.” The themes identified from the pre- and post-assessment surveys support the results from the Likertscale confidence ratings, that while confidence grew in conducting, interpreting, and using assessment results, PTs indicate the need to continue to refine their skills. Evaluation of Case Study Report When evaluated using the Case Study Report Rubric, PTs’ mean score on assessment results and analysis was 2.15 on the 4-point scale. One PT received a score of 1, one received a score of 1.5, five PTs received a score of 2, and three PTs received a score of 3 (one participant


completed the surveys, but did not turn in the Case Study Report). A score of 2 was earned using the following qualifications: Assessment results are somewhat interpreted correctly. Minimal areas of strength and/or concern are identified. Minimal evidence illustrates interpretations. The analysis focuses on areas students did well OR needs support using evidence from the summary or work samples. While PTs had received feedback on each individual assessment prior to submitting the final Case Study Report, the ability to synthesize results across assessments remained challenging for them. PTs were often able to identify strengths and in what areas of literacy students needed additional support based on an individual assessment, but had difficulty using multiple measures to support decisions about instructional needs and strengths. PTs’ mean score on instructional recommendations was 2.2, with two PTs earning 1s, four PTs earning 2s, and four PTs earning 3s. These scores indicate PTs continue to need support in interpreting assessment results, and as such, one of the results of this study is continued refinement of the instructional support of PTs learning about literacy assessments within EDUC 3490 and other literacy coursework. Discussion With ever-increasing pressures at federal, state, and local levels for effective reading teachers, the more we know about what novice PTs learn about effective literacy instruction and assessment, the more effectively institutions of higher education can prepare future teachers of literacy. The purpose of this study was to better understand the knowledge and confidence of PTs’ assessment knowledge in the context of a practice-situated University course. While there are several limitations of this study, notwithstanding the sample of convenience, small number of participants and data set, and the primary aim being to improve components of coursework rather than a systematic, large-scale, longitudinal effort (Dillon et al., 2010), the data is encouraging regarding the use of this assessment in order to address PT assessment knowledge. Additionally, this study can contribute to understanding how teacher educators can provide a context to teach the high-leverage skills necessary for effective P-12 teaching (Ball & Forzani, 2009).


The assignment under research helps PTs develop their knowledge to “construct, administer, and score reliable assessments and communicate valid interpretations about student learning” (DeLuca & Bellara, 2013, p. 356). Teaching is a, profession of practice, and prospective teachers must be prepared to become expert practitioners who know how to use the knowledge of their profession to advance student learning…In order to achieve this we must place practice at the center of teaching preparation. (NCATE, 2010, p. 2) The course and assignment were designed to place practice at the center of the development of PTs in order to deepen their knowledge of literacy development and assessment in the context of a classroom. Findings indicate that PTs’ confidence in conducting, analyzing, and reporting assessment data in literacy increased during the course, and their ability to discuss what they learned about assessments in literacy developed beyond “correct” administration of assessments. Despite growth in confidence in administering, analyzing, and using assessment data, the ability to synthesize across data sources remains a challenge and indicates a need to continue to focus on this skill throughout the preparation of PTs. I intend to revise the course to include more opportunities for PTs to see modeling and engage in guided practice of this critical skill. Preservice teachers in the context of this course were able to add complexity to their understanding of assessments in the development of their assessment knowledge. While ideally, PTs would have earned higher scores on the Case Study Report rubric, the results indicate that at the mid-point of their teacher preparation program, they are moving towards proficiency. And while PTs indicated they realized assessments were challenging to administer and analyze, they also showed increased confidence in their abilities to do so. Prior to this course, PTs have had minimal exposure to administration and analysis of assessment data. Being their first time with a more extensive experience with assessment data, while working with an actual student in their fieldwork class rather than generic data sets, PTs are beginning to make sense of one of the most critical and complex of their responsibilities as future teachers. The more the PTs learn about assessment data, they also become exposed to what they still do not know. It is impossible to determine with the data sources included in this study whether skills increased because of the intervention of the course, Literacy Lab experience, and Case Study Report without a baseline


data source; however, the increased complexity in understanding and increased confidence in assessment knowledge is promising. While more work is needed to conclude the best context for learning appropriate assessment implementation and analysis, the use of rubric language from the edTPA, designed to evaluate students during student teaching, needs additional scaffolding to be used as a developmentally appropriate evaluation tool for these PTs in early field- and coursework experiences. Expectations of PTs at this point in their preparation should be revised from the expectations of teacher candidates during student teaching, so the use of the rubric may not be best suited at this point for a summative signature assignment. Using this as a formative assessment tool, rather than one used to determine a grade, may be a more effective learning experience for PTs. More research is needed to determine effective scaffolding of the edTPA assessment for evaluation during teacher education programs. The unique facilitation of the course on-site at an elementary school incorporating assessments conducted at the school provides PTs a real-world application of the literacy instruction and assessment theories presented in class. PTs indicated they learned a great deal from the opportunity, yet as described, there remain areas necessary for additional development. Therefore, while the Case Study Report appears to be a viable method for facilitating PT learning in literacy assessment, future instruction in EDUC 3490 will include additional modeling and opportunities to practice using assessment data to plan instruction, in order to provide PTs with instruction how they learn best – through explicit teaching and modeling and long-term engagement with new concepts (Dillon et al., 2010). Author Biography Dr. Catherine Kelly, an assistant professor at St. Catherine University, teaches undergraduate and graduate courses in literacy methods and children's literature, content area literacy, research methods, and assessment in addition to supervising practicum and student teaching experiences. Her research interests focus on effective preparation of and induction for elementary teachers.


References AACTE (2016). About edTPA. Retrieved from http://edtpa.aacte.org/ Afflerbach, P. (2007). Understanding and using reading assessment K-12. Newark, DE: International Reading Association. Ball, D., & Forzani, F. (2009). The work of teaching and the challenge for teacher education. Journal of Teacher Education, 60(5), 497-510. Bear, D. R., Invernizzi, M. A., Templeton, S., & Johnston, F. A. (2011). Words their way: Word study for phonics, vocabulary, and spelling instruction (5th ed.). Upper Saddle River, NJ: Pearson. Blair, T. R., Rupley, W. H., & Nichols, W. D. (2007). The effective teacher of reading: Considering the “what” and “how” of instruction. The Reading Teacher, 60(5), 432-438. Burke Johnson, R. & Onweugbuzie, A. J. (2004). Mixed methods research: A research paradigm whose time has come. Educational Researcher, 33(7), 14-26. Council of Chief State School Officers (CCSSO) (2012). Our responsibility, our promise: Transforming educator preparation and entry into the profession. Washington, DC: Author. Clift, R. T., & Brady, P. (2005). Research on methods courses and field experiences. In M. Cochran-Smith and K. Zeichner (Eds.), Studying teacher education: The report of the AERA panel on research and teacher education (pp. 309-424). Mahwah, NJ: Lawrence Erlbaum Associates. Cresswell, J. W., Plano Clark, V. L., Gutmann, M. L., & Hanson, W. E. (2003). Advanced mixed methods research designs. In A. Tashakkori, & C. Teddlie (Eds.) Handbook of Mixed Methods in Social and Behavioral Research (pp. 209-240). Thousand Oaks, CA: Sage. Darling-Hammond, L. (2010). Evaluating teacher effectiveness: How teacher performance assessments can measure and improve teaching. Center for American Progress. DeLuca, C. & Bellara, A. (2013). The current state of assessment education: Aligning policy, standards, and teacher education curriculum. Journal of Teacher Education, 64(4), 356372. Dillon, D. R., O’Brien, D. G., Sato, M., & Kelly, C. M. (2010). Professional development and


teacher education for reading. In M. L. Kamil, P. D. Pearson, E. B. Moje, & P. Afflerbach (Eds.). Handbook of reading research (Vol. IV, pp. 629-660). New York, NY: Routledge. DinanThompson, M. & Penney, D. (2015). Assessment literacy in primary physical education. European Physical Education Review, 21(4), 485-503. Ellis, S. & Smith, V. (2017). Assessment, teacher education, and the emergence of professional expertise. Literacy, 51(2), 84-93. Fillmore, L. W., & Snow, C. E. (2002). What teachers need to know about language. In C. T. Adger, C. E. Snow, & D. Christian (Eds.), What teachers need to know about language (pp. 7-54). McHenry, IL: Delta Systems. Ferguson, K. (2017). Using a simulation to teach reading assessment to preservice teachers. The Reading Teacher, 70(5), 561-569. Gillett, E. & Ellingson, S. P. (2017). How will I know what my students need? Preparing preservice teachers to use running records to make instructional decisions. The Reading Teacher, 71(2), 135-143. Henk, W. A., & McKenna, M. C. (2004). Developing affective instrumentation for use in literacy research. In N. K. Duke & M. H. Mallette (Eds.), Literacy Research Methodologies (pp. 197-226). New York, NY: The Guilford Press. Hoffman, J., Roller, C., Maloch, B., Sailors, M., Duffy, G., & Beretvas, S. N. (2005). Teachers’ preparation to teach reading and their experiences in the first three years of teaching. The Elementary School Journal, 21, 343-356. International Reading Association (2000). Effective reading teachers (Position statement). Newark, DE: Author. Retrieved from http://www.reading.org/General/AboutIRA/PositionStatements/ExcellentTeachersPositio n.aspx International Reading Association (2003). Standards for reading professionals – revised 2003. Newark, DE: International Reading Association. Kindle, K. J., & Schmidt, C. M. (2013). Developing preservice teachers: A self-study of instructor scaffolding. Reading Improvement, 50(3), 83-100. Klenowski, V. (2009). Australian Indigenous students: Addressing equity issues in assessment.


Teaching Education, 20(2), 77-93. Lacina, J. & Block, C. C. (2011). What matters most in distinguished literacy teacher education programs? Journal of Literacy Research, 43(3), 319-351. Maloch B., Flint A. S., Eldridge D., Harmon J., Loven R., Fine J. C., (2003). Understandings, beliefs, and reported decision making of first-year teachers from different reading teacher preparation programs. The Elementary School Journal, 103, 431–457. Mayor, S. (2005). Preservice teachers’ developing perspectives on assessment and remediation of struggling readers. Reading Improvement, 42(3), 164-178. McKenna, M. C., & Stahl, S. A. (2003). Assessment for reading instruction. New York, NY: The Guilford Press. Miles, M. B., Huberman, A. M., & Saldaña, J. (2014). Qualitative data analysis (3nd ed.). Thousand Oaks, CA: Sage. Moats, L. C. (1999). Teaching reading is rocket science: What expert teachers of reading should know and be able to do. Washington, DC: American Federation of Teachers. National Council for the Accreditation of Teacher Education (NCATE) (2010). Transforming teacher education through clinical practice: A national strategy to prepare effective teachers. Retrieved from http://www.ncate.org/Public/Publications/TransformingTeacherEducation/tabid/737/Defa ult.aspx Popham, W. J. (2009). Assessment literacy for teachers: Faddish or fundamental? Theory into Practice, 48(1), 4-11. Reeves, T. D., & Honig, S. L. (2015). A classroom data literacy intervention for pre-service teachers. Teaching and Teacher Education, 50, 90-101. Revisor of Statutes, State of Minnesota (n.d.). Standards of effective practice for teachers. Retrieved from https://www.revisor.mn.gov/rules/?id=8710.2000 Risko, V. J., Roller, C. M., Cummins, C., Bean, R. M., Block, C. C., Anders, P. L., & Flood, J. (2008). A critical analysis of research on reading teacher education. Reading Research Quarterly, 43(3), 252-288. Snow, C. E., Griffin, P., & Burns, M. S. (Eds.) (2005). Knowledge to support the teaching of reading: Preparing teachers for a changing world. San Francisco, CA: Jossey-Bass.


Stillman, J., Ragusa, G., & Whittaker, A. (2015). Teacher performance assessment: Ready for professional practice. In E. R. Hollins (Ed.) Rethinking field experiences in preservice teacher preparation: Meeting new challenges for accountability (pp. 171-201). New York, NY: Routledge. Strauss, A., & Corbin, J. (1990). Basics of qualitative research: Grounded theory procedures and techniques. Newbury Park, CA: Sage. Strickland, D. S., Snow, C. E., Griffin, P., Burns, M. S., & McNamara, P. (2002). Preparing our teachers: Opportunities for better reading instruction. Washington, DC: National Academy Press. Willis, J., Adie, L., & Klenowski, V. (2013). Conceptualizing teachers’ assessment literacies in an era of curriculum and assessment reform. Australian Educational Researcher, 40(2), 241-256. Zeichner, K. (2012). The turn once again to practice-based teacher education. Journal of Teacher Education, 63(5), 376-382.


Tables and Figures Table 1: Methods Preparation Coursework at the University Term 1

Term 2

Term 3

EDUC 2070

EDUC 3490

EDUC 3010 (Math

(Teachers as

(Intermediate

Methods)

Leaders)

Literacy

Term 4 Student Teaching

Methods) EDUC 2090

EDUC 3550

EDUC 3030

Student Teacher

(General Methods)

(Content-Area

(Science Methods)

Seminar

Literacy: Elementary) INDI 2440

EDUC 3080 (Art

EDUC 3050

(Choosing and

Methods)

(Social Studies

Using Books for

Methods)

Children) EDUC 3110

EDUC 3290

(Music Methods)

(Kindergarten Methods)

EDUC 3130 (P.E.

EDUC 3540

Methods)

(Relationship Techniques)


Figure 1: Confidence in conducting assessments

Figure 2: Confidence in interpreting assessments

Figure 3: Confidence in using assessment results


Appendix A Case Study Rubric

1

2

3

4

Introduction

Introduction is

Introduction includes

Introduction includes

Introduction includes

and context

incomplete.

pseudonym, grade

pseudonym, grade

pseudonym, grade

for learning

Reading level is

level, and how

level, and how

level, and how

inaccurate.

student was selected.

student was selected.

student was selected.

Assessment sessions

Assessment sessions

Assessment sessions

are not well

are somewhat

are described fully.

described. Estimated

described. Estimated

Estimated reading

reading level is

reading level is

level is accurate.

inaccurate.

accurate.

Standards of Effective Practice Standard: Standard 5 - Learning Environment: Sub-standard: M. Standard: Standard 8 - Assessment Sub-standard: E. Assessment

Assessment results

Assessment results

Assessment results

Assessment results

results and

are not accurately

are somewhat

are mostly interpreted

are interpreted

analysis

interpreted. No

interpreted correctly.

correctly. A few areas

correctly. Several

specific areas of

Minimal areas of

of strength are/or

areas of strength and

(based on

strength and

strength are/or

concern are

concern are

edTPA rubric

concern are

concern are

identified. Evidence

identified. Significant

#11)

identified. The

identified. Minimal

is included to

evidence is included

analysis is

evidence illustrates

illustrate

to illustrate

superficial or not

interpretations. The

interpretations. The

interpretations.

supported by

analysis focuses on

analysis focuses on

Analysis uses specific

either student

what students did

what students did

examples from work

work samples or

well OR needs

well AND needs

samples to

the summary of

support using

support, and is

demonstrate patterns

student learning.

evidence from the

supported with

of student learning

The evaluation

summary or work

evidence from the

consistent with the

criteria are not

samples.

summary and work

summary.

aligned with the learning objectives

samples.

Score/ Level


1

2

3

4

and/or analysis. Standards of Effective Practice Standard: Standard 8 - Assessment: Sub-standard: A, Sub-standard: E, Sub-standard: F, Substandard: G. Sub-standard: H. Sub-standard: M. Instructional

Activities do not

Activities align

Activities align with

Activities provide a

Recommenda

align with

peripherally to

objectives and

logical path to

tions

objectives and

objectives and

assessment. A few

meeting objectives

assessment. Many

assessment. Some

activities may be

based on assessment

(based on

activities are

activities are

extraneous or

results. No activities

edTPA rubric

extraneous and

extraneous or

irrelevant. Activities

are extraneous or

#3)

irrelevant. No

irrelevant. Activities

are appropriate for

irrelevant. Activities

attempt is made to

are not effectively

the students' needs

are appropriate for

individualize

individualized for the

and strengths. Several

the students' needs

activities for needs

needs and/or

specific strategies are

and strengths.

or strengths of

strengths of case

included. PT justifies

Specific, high-quality

case study student.

study student.

why learning tasks

strategies are

No specific

Minimal strategies

(or their adaptations)

described. PT

strategies are

are included. PT

are appropriate using

justifies why learning

included. PT’s

justifies learning

examples of students’

tasks (or their

justification of

tasks with limited

prior academic

adaptations) are

learning tasks is

attention to students’

learning OR

appropriate using

either missing OR

prior academic

examples of

examples of students’

represents a deficit

learning OR

personal/cultural/

prior academic

view of students

personal/cultural/com

community assets. PT

learning and/or

and their

munity assets. PT

makes superficial

examples of personal/

backgrounds. PT

does not make

connections to

cultural/community

does not make

connections to

research and/or

assets. PT makes

connections to

research and/or

theory.

connection to

research and/or

theory or connections

research and/or

theory or

are unrelated.

theory.

connections are unrelated. Standards of Effective Practice Standard: Standard 7 - Planning Instruction: Sub-standard: B, Sub-standard: C, Sub-standard:

Score/ Level


1

2

3

4

E, Sub-standard: G. Additional

Additional

Minimal discussion

Some discussion of

A thoughtful

Information

information is not

of additional

additional

discussion of

addressed.

information is

information sought

additional

included.

and how to secure

information that

that information is

would be helpful and

included.

how to secure that information is included.

Reflection

The analysis is

The analysis provides

The analysis provides

The analysis is

weak, providing

minimal evidence of

some evidence of

thoughtfully written

no evidence of

being a reflective

being a reflective

and provides

reflection on the

practitioner. It

practitioner. It

evidence of the

experience. It does

includes minimal

includes a few ideas

teacher being a

not include

ideas about the

about the

reflective practitioner.

thoughtful ideas

administration,

administration,

It includes specific

about the

analysis and synthesis

analysis and synthesis

ideas about the

administration,

of results, and

of results, and

administration,

analysis and

implementing

implementing

analysis and synthesis

synthesis of

instruction.

instruction.

of results, and

results, or

implementing

implementing

instruction.

instruction. Standards of Effective Practice Standard: Standard 9 - Reflection and Professional Development: Sub-standard: E, Substandard: H. Conventions

Spelling and

The report contains

The report contains

Spelling and grammar

grammar are

many spelling and

few spelling and

in report are flawless.

unacceptable.

grammar errors.

grammar errors.

Score/ Level


Appendix B Pre-assessment survey On a scale of 1 to 4, how confident are you in your ability to conduct literacy assessments with intermediate students? 1 – Not at all confident

2 – A little confident

3 – Reasonably

4 – Very high

confident

confidence

On a scale of 1 to 4, how confident are you in your ability to interpret the results of literacy assessments of intermediate students? 1 – Not at all confident

2 – A little confident

3 – Reasonably

4 – Very high

confident

confidence

On a scale of 1 to 4, how confident are you in your ability to use assessment results to plan literacy instruction for intermediate students? 1 – Not at all confident

2 – A little confident

3 – Reasonably

4 – Very high

confident

confidence

What do you hope to learn about conducting literacy assessments through your work with your case study student? What do you hope to learn about interpreting literacy assessment results through your work with your case study student? What do you hope to learn about using assessment data to plan literacy instruction through your work with your case study student?


Post assessment survey On a scale of 1 to 4, how confident are you in your ability to conduct literacy assessments with intermediate students? 1 – Not at all confident

2 – A little confident

3 – Reasonably

4 – Very high

confident

confidence

On a scale of 1 to 4, how confident are you in your ability to interpret the results of literacy assessments of intermediate students? 1 – Not at all confident

2 – A little confident

3 – Reasonably

4 – Very high

confident

confidence

On a scale of 1 to 4, how confident are you in your ability to use assessment results to plan literacy instruction for intermediate students? 1 – Not at all confident

2 – A little confident

3 – Reasonably

4 – Very high

confident

confidence

What did you learn about conducting literacy assessments through your work with your case study student? What did you learn about interpreting literacy assessment results through your work with your case study student? What did you learn about using assessment data to plan literacy instruction through your work with your case study student?


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Journal of Scholastic Inquiry: Special Edition

Volume 8 Page 107

WHY READ OUR JOURNALS? Continuing Education: Each of the CSI's peer-reviewed journals focuses on contemporary issues, scholarly research, discovery, and evidence-based practices that will elevate readers' professional development. Germane Reference: The CSI's journals are a vital resource for students, practitioners, and professionals in the fields of education, business, and behavioral sciences interested in relevant, leading-edge, academic research. Diversity: The CSI’s peer-reviewed journals highlight a variety of study designs, scientific approaches, experimental strategies, methodologies, and analytical processes representing diverse philosophical frameworks and global perspectives Broad Applicability: The CSI's journals provide research in the fields of education, business and behavioral sciences specialties and dozens of related sub-specialties. Academic Advantage: The CSI's academically and scientifically meritorious journal content significantly benefits faculty and students. Scholarship: Subscribing to the CSI's journals provides a forum for and promotes faculty research, writing, and manuscript submission. Choice of Format: Institutions can choose to subscribe to our journals in digital or print format.


Journal of Scholastic Inquiry: Special Edition

Volume 8 Page 108

Teen Mothers Graduating from an Alternative School: A Counter Discourse to Prevailing Negative Perceptions Olivia Panganiban Modesto, Texas A&M University-Kingsville Effective Kindergarten Readiness: What about Collaborative Preschool Interventions? Julie A. Hentges, University of Central Missouri Nancy Montgomery, University of Central Missouri Using Brand Equity and Personality Metrics to Predict the 2016 U.S. Presidential Election Richard J Monahan, American Public University Security Price Impact of Cash Flow Estimates Versus Accounting Accruals Across Industries Ronald Stunda, Valdosta University “Data is Extremely Useful!” Preservice Teachers’ Growth in Literacy Assessment and Instruction Catherine M. Kelly, St. Catherine University

Published by: Center for Scholastic Inquiry, LLC 4857 Hwy 67, Suite #2 Granite Falls, MN 56241 855-855-8764

ISSN: 2330-6564 (online) ISSN: 2330-6556 (print)

Profile for Center for Scholastic Inquiry

Journal of Scholastic Inquiry: Special Edition (Fall 2017)  

Journal of Scholastic Inquiry: Special Edition (Fall 2017)  

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