EICAA Data Analysis Report by Christian Jost

Entrepreneurial and Intrapreneurial Competences Assessment Alliance

EICAA Data Analysis Report Deliverable (WP6) Last update: 13/12/2023

This Data Analysis Report is a publication belonging to Work Package 6 ”Pilot Round & Data Analysis” of the project Entrepreneurial and Intrapreneurial Competences Assessment Alliance (EICAA). Document dissemination level: public. Manuscript completed in November 2023. Revised in December 2023. Authors: Bernd Ebersberger (University of Hohenheim) and Louisa Mach (University of Hohenheim). Contributors: Marta Carceller (TecnoCampus), Ester Bernardó-Mansilla (TecnoCampus), Jaume Teodoro (TecnoCampus), Wouter Van Bockhaven (AMS), Tanvi Anand (AMS), Anita Zehrer (MCI), Gundula Glowka (MCI), Desiree Wieser (MCI), Christine Pirhofer (MCI), Taimur Khan (Adsata), Jonas Kühl (Adsata), András Toth (eVista), Julia Zoller (ProMedia), Rafaela Bodner (ProMedia), Nemanja Sever (ProMedia) Florian Bratzke (Univations), Sandra Bier (Univations), Daniel Worch (Univations), Szabolcs Prónay (University of Szeged), Ábel Garamhegyi (University of Szeged).

Contact information: mailto:bernd.ebersberger@uni-hohenheim.de

The EICAA consortiums consists of the following core partners:

ANTWERP MANAGEMENTSCHOOL ADSATA

EVISTA

MANAGEMENT CENTER INNSBRUCK

TECNOCAMPUS PROMEDIA KOMMUNIKATION

UNIVATIONS

UNIVERSITY OF SZEGED

UNIVERSITY OF HOHENHEIM

Licence Terms

This work is licensed under a Creative Commons License Attribution-NonCommercialShareAlike 4.0 international License (CC BY-NC-SA 4.0) Under the licence, you are free to: SHARE – copy and redistribute the materials in any medium or format ADAPT – remix, transform, and build upon the materials The licensor cannot revoke these freedoms as long as you follow the license terms: Attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.

NonCommercial – You may not use the material for commercial purposes.

ShareAlike – If you remix, transform, or build upon the material, you must distribute your contribution under the same license as original.

No additional restrictions – You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.

EICAA Analysis Bernd Ebersberger & Louisa Mach, University of Hohenheim 2023-12-03

Table of contents Preface What is EICAA? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . What is this report about? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . How does this report connect to other outputs of EICAA? . . . . . . . . . . . . . . .

5 5 6 6

This Report 1. Analysis of key descriptive indicators of the competences . . . . . . . . . . . 2. Analysis of the distribution of the competences . . . . . . . . . . . . . . . . 3. Analysis of segments of the sample . . . . . . . . . . . . . . . . . . . . . . . 4. Regression analysis trying to explain the competences . . . . . . . . . . . . .

9 9 9 9 10

All Countries - Student Data Summary of the Competences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Ideas and Opportunities . . . . . . . . . . . . . . . . . . . . Competence Area: Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Into Action . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on Gender . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on Age Groups . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on the Major of the Study Program . . . . . . . . . . . . . Segmentation Based on Work Experience . . . . . . . . . . . . . . . . . . . . . Regression Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Ideas and Opportunities . . . . . . . . . . . . . . . . . . . . Competence Area: Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Into Action . . . . . . . . . . . . . . . . . . . . . . . . . . .

12 12 12 13 15 16 18 18 20 22 26 27 28 31 34

Austria Summary of the Competences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Ideas and Opportunities . . . . . . . . . . . . . . . . . . . . Competence Area: Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Into Action . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on Gender . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on Age Groups . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on the Major of the Study Program . . . . . . . . . . . . . Segmentation Based on Work Experience . . . . . . . . . . . . . . . . . . . . .

38 38 38 39 40 41 43 43 45 47 51

Belgium Summary of the Competences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Ideas and Opportunities . . . . . . . . . . . . . . . . . . . . Competence Area: Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Into Action . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

54 54 54 55 56 57 58

Germany Summary of the Competences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Ideas and Opportunities . . . . . . . . . . . . . . . . . . . . Competence Area: Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Into Action . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on Gender . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on Age Groups . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on the Major of the Study Program . . . . . . . . . . . . . Segmentation Based on Work Experience . . . . . . . . . . . . . . . . . . . . .

60 60 60 61 62 63 64 64 66 67 69

Hungary Summary of the Competences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Ideas and Opportunities . . . . . . . . . . . . . . . . . . . . Competence Area: Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Into Action . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on Gender . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on Age Groups . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on the Major of the Study Program . . . . . . . . . . . . . Segmentation Based on Work Experience . . . . . . . . . . . . . . . . . . . . .

73 73 73 74 75 76 77 77 79 80 82

Spain Summary of the Competences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Ideas and Opportunities . . . . . . . . . . . . . . . . . . . . Competence Area: Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . Competence Area: Into Action . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on Gender . . . . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on Age Groups . . . . . . . . . . . . . . . . . . . . . . . . Segmentation Based on the Major of the Study Program . . . . . . . . . . . . . Segmentation Based on Work Experience . . . . . . . . . . . . . . . . . . . . .

86 86 86 87 88 89 90 90 91 93 95

All Countries - Employee Data 99 Summary of the Competences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Competence Areas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 Competence Area: Ideas and Opportunities . . . . . . . . . . . . . . . . . . . . 100 Competence Area: Resources . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 Competence Area: Into Action . . . . . . . . . . . . . . . . . . . . . . . . . . . 102

Preface

Preface What is EICAA? EICAA stands for Entrepreneurial and Intrapreneurial competences Assessment Alliance. It is a European university-business collaboration that has developed sophisticated instruments to measure, analyse, and develop entrepreneurial competences. The istruments enable a more data-driven orientation of entrepreneurship education. These instruments are integrated and logically connected within the EICAA Digital Platform – the core product of the EICAA project. Namely, the platform hosts: 1. The Competence Monitor (CM) 2. The Competence Development Kit (CDK) Both instruments can be exploited for fostering entrepreneurial competences among university students or employees (corporate or higher education). They can either be used separately or in combined form. However, we recommend a combined use to fully unleash the potential of the platform. This means that you can: • create a self-assessment (a student or an employee survey version), • run the assessment among your target group (students or employees) • get an analysis of the results together with module recommendations that are based on them (both presented inside the data dashboard of the CM) • get automatically directed to the modules of the CDK that have been identified to be most valuable to develop entrepreneurship competence(s) among the group that underwent the self-assessment. The EICAA Digital Platform is free-of-charge. It is fully GDPR compliant and available under: https://platform.eicaa.eu/. To exploit it, educators or trainers only need to set up a user account. Once this is done, users can create and run as many (self-)assessments as they want. Moreover, the platform provides access to a pool of carefully compiled teaching (for students) and training (for employees) materials that educators and trainers can rely on to inspire and enrich the entrepreneurship education activities they engage in. Therefore, we invite any educator and trainer of entrepreneurship education – with or without prior experience in the field - to become part of the EICAA community by making use of the platform.

What is this report about? This report analyses the data that was gathered during the pilot phase of the EICAA Digital Platform in 2023. Overall, 2,594 higher education students and 251 employees from 66 countries took part in the piloting of the EICAA Digital Platform. More in depth information on the EICAA Pilot Round can be found here: https://www.eicaa.eu/results/pilot-round/. The report starts by presenting findings on the basis of the entire pilot round sample which, however, also takes into consideration different segmentation criteria (e.g. age, gender, etc.). This initial part is complemented by an analysis on the basis of each country of the partners in the EICAA consortium. Where possible in terms of the size of the subsample, this second part takes into consideration the same segmentation criteria as the first part.

How does this report connect to other outputs of EICAA? The structure of this report is somewhat pre-determined by the information gathered from the EICAA Competence Monitor. The Competence Monitor integrates a self-assessment survey for entrepreneurship competences that was developed by the EICAA consortium. As a matter of fact, the survey is derived from a) the EICAA Competence Framework and b) the rubric system therein. 1. The EICAA Competence Framework suggests a progression to the European Entrepreneurship Competence Framework (EntreComp). It also follows the wide conceptual understanding of entrepreneurship that is integral to EntreComp and defines entrepreneurship as „when you act upon opportunities and ideas and transform them into value for others. The value that is created can be financial, cultural, or social”. It delineates three interconnected competence areas (Ideas & Opportunities; Resources; Into Action) and an overall of 19 entrepreneurship competences therein (see below). For more information on the EICAA Competence Framework please consult https://www.eicaa.eu/results/competence-framework/. 2. The EICAA rubric system is constructed upon five levels of proficiency: None, Basic, Intermediate, Advanced and Expert. It was operationalised into survey instruments (one for use among university students and one for use among business employees/practitioners). Thus, the rubric system served as a foundation for the design of a self-assessment survey of entrepreneurship competences that constitutes the data gathering part of the EICAA Competence Monitor. The survey was refined in several iterations following a Delphi process and several pre-tests. All details on the rubric as well as on the development and validation of the survey(s) can be retraced by consulting the documentation on the establishment of the EICAA Competence Monitor available here: https://www.eicaa.eu/results/competence-monitor/.

Furthermore, the data analysis of this report was done with the programme R which provides a free software environment for statistical computing and graphics. The syntax used for our analysis can be found here: https://www.eicaa.eu/results/pilot-round/.

This Report

This Report This report analyzes the data gathered in the pilot round in four steps: 1. Analysis of key descriptive indicators of the competences In the first step of the analysis we provide insight into key descriptive indicators of the competences. In particular, we provide information about the size of the sample or subsample. We report the minimum and the maximum. We describe the central tendency of the distribution by giving the mean and the median and accompany those with the 1st quartile and the 3rd quartile and the standard deviation. This provides an analytic description of the distribution based on a set of well-known indicators. 2. Analysis of the distribution of the competences Additionally, we report the full distribution of the responses by assuming metric nature of the measues and drawing a smoothed representation of the distribution. We color the distribution to match the EICAA coloring scheme used in the survey and other publications to highlight the different levels: • None ■, • Basic ■, • Intermediate ■, • Advanced ■, • Expert ■, 3. Analysis of segments of the sample To analyze segments of the data and the competence distribution therein we break down the sample into subsamples based on gender, age group, major of the study program, and work experience.

4. Regression analysis trying to explain the competences Finally, a regression analysis strives to explain the levels of competences based on four variables: age (measured by a dummy for the youngest age group), workexperience, master students, and female respondents. We report the regression results in tables and in visualizations where we can visually inspect significance more easily than from the confidence intervals. We report the regression analysis only for the overall sample and not for national subsamples.

All Countries Student Data

All Countries - Student Data This is the analysis for all countries involved in the EICAA project: Austria, Belgium, Germany, Hungary, and Spain.

Competence Areas The entrepreneurship competences of the EICAA framework consist of three different competence areas that each comprise competences which we will investigate in more detail further down in the document. These competence areas are Ideas and Opportunities, Resources, and Into Action.

Table 1: Descriptives of the Competence Areas Variable

Min

x25

Mean

Median

x75

Max

Competence

IaO 2594 0 2.4 2.8 0.64 2.8 3.2 5 Res 2594 0 2.3 2.8 0.66 2.8 3.2 5 IAc 2594 0 2.5 3 0.69 3 3.4 5 Note: IaO = Ideas and Opportunities, Res = Resources, IAc = Into Action

Res

IaO

IAc None

Basic

Intermed.

Advanced

Expert

Competences Comparison for the Countries Here we break down the competences on the countries involved in the EICAA project: Austria, Belgium, Spain, Germany, and Hungary. Upon closer inspection we observe some minor differences of the competence distributions across the countries. Competence Area: Ideas and Opportunities The competence area Ideas and Opportunities comprises of the following competences: Spotting opportunities (spop), Design orientation (deor), Creativity (crea), Vision (visi), Valuing ideas (vaid), Ethical and sustainable thinking (sust).

Competence

IaO

Res

IAc

AT BE ES DE HU N

E N

Figure 1: Competence Areas by Countries Table 2: Descriptives of the Competence Area Ideas and Opportunities Variable

Min

x25

Mean

Median

x75

Max

visi vaid sust spop crea

2594 2594 2594 2594 2594

0 0 0 0 0

2 2 2.5 2.2 2.4

2.8 2.5 3 2.9 2.8

0.82 0.82 0.79 0.72 0.75

2.7 2.3 3 3 2.8

3.3 3 3.5 3.2 3.4

5 5 5 5 5

deor 2594 0 2.3 2.8 0.82 2.7 3.3 5 Note: visi = Vision, vaid = Valuing ideas, sust = Ethical and sustainable thinking, spop = Spotting opportunities, crea = Creativity, deor = Design orientation.

Competence

visi vaid sust spop deor crea None

Basic

Intermed.

Advanced

Expert

Competence Area: Resources The competence area Resources comprises of the following competences: Self-awareness and self-efficacy (self), Motivation and perseverance (moti), Mobilising (financial) resources (mobi), Enterprising literacy (litr), Mobilising others (othr), and Digital competence (dico). Table 3: Descriptives of the Competence Area Resources Variable

Min

x25

Mean

Median

x75

Max

self othr moti mobi litr

2594 2594 2594 2594 2594

0 0 0 0 0

2.5 2.3 2.5 2 2

3 2.9 3.1 2.5 2.6

0.77 0.8 0.82 0.83 0.86

3 3 3 2.4 2.5

3.5 3.5 3.8 3 3.2

5 5 5 5 5

dico 2594 0 2 2.6 0.83 2.5 3.2 5 Note: self = Self-awareness and self-efficacy, othr = Mobilising others, moti = Motivation and perseverance, mobi = Mobilising resources, litr = Enterprising literacy, dico = Digital competences.

Competence

self othr moti mobi litr dico None

Basic

Intermed.

Advanced

Expert

Competence Area: Into Action The competence area Into Action comprises of the following competences: Taking the initiative (init), Planning and management (plan), Process management (proc), Coping with uncertainty, ambiguity, and risk (cope), Design validation and co-creation (dval), Working with others (work), and Learning through experience (lepx). Table 4: Descriptives of the Competence Area Into Action Variable

Min

x25

Mean

Median

x75

Max

work proc plan lepx init

2594 2594 2594 2594 2594

0 0 0 0 0

2.5 2.4 2.4 2.7 2.7

3.1 2.9 2.9 3.3 3.4

0.82 0.77 0.8 0.86 0.86

3.1 3 2.8 3.3 3.3

3.8 3.4 3.4 4 4

5 5 5 5 5

dval 2594 0 2 2.5 0.94 2.3 3 5 cope 2594 0 2 2.6 0.87 2.7 3.3 5 Note: work = Working with others, proc = Process management, plan = Planning and management, lepx = Learning through experience, init = Taking the initiative, dval = Design validation and co-creation, cope = Coping with uncertainty, ambiguity, and risk

Competence

work proc plan lepx init dval cope None

Basic

Intermed.

Advanced

Expert

Segmentation Analysis Segmentation Based on Gender Ė Note The participant’s gender is not always provided in the survey. In the sample that is the basis of the analysis we have a total of 2594 observation. The gender is contained in the data of 1842 observations. In the table below we provide an overview of the distribution of the respondents over their self reported gender identities. Table 5: Summary Statistics Variable

Percent

Gender ... male ... female ... prefer-not-to-say ... nonbinary

1842 1052 751 28 11

57% 41% 2% 1%

For the analysis in this section, we keep the observations where gender takes the following values: male, female, prefer-not-to-say, nonbinary. All other observations are not taken into account. In this section we segment the sample based on gender. This allows us to observe the shifting of the competences across different gender identities. We show the descriptive statistics of the competence areas broken down on gender. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different genders. Please note that the competence levels are abbreviated by their first capital letter.

Table 6: Descriptives of Competence Area by Gender Variable

Min

x25

Mean

Median

x75

Max

gender: male IaO Res IAc gender: female

1052 1052 1052

1.3 1 1

2.4 2.4 2.5

2.8 2.9 3

0.61 0.63 0.65

2.9 2.9 3

3.2 3.3 3.4

5 5 5

751 751 751

0 0 0

2.3 2.3 2.6

2.8 2.8 3

0.62 0.63 0.67

2.8 2.8 3

3.2 3.2 3.4

4.6 4.8 4.9

2.4

2.8

0.68

2.8

3.3

Res IAc gender: nonbinary IaO Res

28 28

1 1

2.2 2.4

2.6 2.8

0.75 0.72

2.6 2.8

3.1 3.3

3.8 4

11 11

1.7 1.6

2.9 2.7

3.2 3

0.86 0.84

3.2 2.9

3.4 3.3

5 5

IAc

2.4

2.8

3.4

0.75

3.5

3.6

IaO Res IAc gender: prefer-not-to-say IaO

Competence

IaO

Res

IAc

nonbinary

prefer−not−to−say

female

male N

E N

Figure 2: Competence Areas by Gender

Segmentation Based on Age Groups Ė Note The participant’s age is not always provided in the survey. In the sample that is the basis of the analysis we have a total of 2594 observation. Age is contained in the data of 1862 observations. In the table below we provide an overview of the distribution of the respondents over the age groups. Table 7: Summary Statistics Variable

Percent

ageGroup ... 18-23-years ... 24-30-years ... 31-40-years ... 41-50-years

1862 1567 265 24 5

84% 14% 1% 0%

... 51-plus-years

For the analysis in this section, we keep the observations where the respondents are in the following age groups: 18-23-years, 24-30-years, 31-40-years, 41-50-years. All other observations are not taken into account. In this section we segment the sample based on age groups. This allows us to observe the shifting of the competences across different generations of respondents. We show the descriptive statistics of the competence areas broken down on age groups. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different age groups. Please note that the competence levels are abbreviated by their first capital letter.

Table 8: Descriptives of Competence Area by Age Group Variable

Min

x25

Mean

Median

x75

Max

ageGroup: 18-23-years IaO Res IAc ageGroup: 24-30-years

1567 1567 1567

1 1 1

2.4 2.4 2.6

2.8 2.8 3

0.6 0.63 0.64

2.8 2.8 3

3.2 3.2 3.4

5 5 5

IaO Res IAc ageGroup: 31-40-years IaO

265 265 265

0 0 0

2.5 2.5 2.6

2.9 2.9 3.1

0.66 0.63 0.71

3 2.9 3.1

3.3 3.3 3.6

4.9 4.8 4.7

1.6

2.5

2.9

0.59

2.9

3.2

3.8

Res IAc ageGroup: 41-50-years IaO Res

24 24

1.1 1.1

2.5 2.7

2.9 3

0.61 0.65

3 3

3.2 3.3

3.9 4.1

5 5

1.6 1.7

2.1 2

2.7 2.7

1.3 1.3

2.2 2.4

2.6 2.6

5 5

IAc

1.8

2.9

1.3

2.6

3.4

Competence

IaO

Res

IAc

41−50−years

31−40−years

24−30−years

18−23−years N

E N

Figure 3: Competence Areas by Age Groups

Segmentation Based on the Major of the Study Program Ė Note The participant’s major field of studies may not always provided in the survey. In the sample that is the basis of the analysis we have a total of 2594 observation. The major field of studies is contained in the data of all observations. In the table below we provide an overview of the distribution of the respondents over the fields of study.

Table 9: Summary Statistics Variable

Percent

majorField ... business-and-administration ... other ... agriculture-forestry-and-fishery ... law

2594 1570 89 13 1

61% 3% 1% 0%

... teacher-training-and-education-science ... life-sciences ... manufacturing-and-processing ... transport-services ... computing

4 9 2 19 273

0% 0% 0% 1% 11%

... engineering-and-engineering-trades ... veterinary ... design ... communications-media-and-public-relations ... biological-sciences-agriculture-and-natural-resources

52 1 41 2 2

2% 0% 2% 0% 0%

... engineering ... religion-and-theology ... mathematics-and-sciences ... performing-arts ... journalism-and-information

1 1 2 1 2

0% 0% 0% 0% 0%

... personal-services ... health ... architecture-and-building ... graphik-and-audio-visual-arts ... environmental-protection

2 206 7 218 2

0% 8% 0% 8% 0%

... fine-arts ... social-services ... social-and-behavioral-science ... physical-sciences

2 1 39 32

0% 0% 2% 1%

For the analysis in this section, we keep the observations where the respondents are in the following fields of study: business-and-administration, other, agriculture-forestry-andfishery, teacher-training-and-education-science, life-sciences, transport-services, computing, engineering-and-engineering-trades, design, health, architecture-and-building, graphik-andaudio-visual-arts, social-and-behavioral-science, physical-sciences. All other observations are not taken into account.

In this section we segment the sample based on fields of study. This allows us to observe the shifting of the competences across different educational foci. We show the descriptive statistics of the competence areas broken down on the fields of study. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different fields of study. Please note that the competence levels are abbreviated by their first capital letter.

Competence

IaO

Res

IAc

physical social graphik architecture health design engineering computing transport life teacher agriculture other business N

E N

Figure 4: Competence Areas by Major Field of Studies

Segmentation Based on Work Experience Ė Note The participant’s work experience may not always provided in the survey. In the sample that is the basis of the analysis we have a total of 2594 observation. The work experience is contained in the data of 1896 observations. In the table below we provide an overview of the distribution of the respondents over the work experience. Table 10: Summary Statistics Variable

Percent

hasWorkExperience ... yes ... no

1896 1333 563

70% 30%

For the analysis in this section, we keep the observations where the respondents are in the following groups of work experience: yes, no. All other observations are not taken into account. In this section we segment the sample based on work experience. This allows us to observe the shifting of the competences across different levels of work experience. We show the descriptive statistics of the competence areas broken down on work experience. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across groups with and without work experience. Please note that the competence levels are abbreviated by their first capital letter.

Table 11: Descriptives of Competence Area by Age Group Variable

Min

x25

Mean

Median

x75

Max

hasWorkExperience: yes IaO Res IAc hasWorkExperience: no

1333 1333 1333

0 0 0

2.4 2.4 2.6

2.9 2.9 3

0.63 0.64 0.67

2.9 2.9 3

3.3 3.3 3.5

5 5 5

IaO Res IAc

563 563 563

1 1 1

2.3 2.3 2.5

2.7 2.7 2.9

0.59 0.62 0.64

2.8 2.7 2.9

3.2 3.1 3.4

5 5 5

Competence

IaO

Res

IAc

yes N

E N

Figure 5: Competence Areas by Work Experience

Regression Analysis In the regression analysis we investigate how different socio-demographic characteristics of the respondents are associated with the level of competences the respondents report. As sociodemographic competences we include in the analysis: • age (as a dummy for the youngest age group), • work experience (as a dummy indicating work experience of the respondents), • the level of education (as a dummy indicating a master program), and

• gender (as a dummy indicating female gender). We report the results of an OLS regresssion in tabular format where we provide the parameter estimates and the 95% confidence interval in brackets. Competence Area: Ideas and Opportunities Table 12: Regression on socio-demographic characteristics

(Intercept) young workexp master female Num.Obs. R2 R2 Adj. F

visi

vaid

sust

2.8 [2.6;2.9] −0.1 [−0.2;0.0] 0.2 [0.1;0.2] 0.0 [−0.1;0.2] 0.0 [−0.1;0.0]

2.5 [2.4;2.6] 0.0 [−0.2;0.1] 0.1 [0.0;0.2] −0.1 [−0.3;0.0] −0.1 [−0.2;0.0]

3.0 [2.9;3.1] −0.1 [−0.2;0.0] 0.1 [0.0;0.1] 0.0 [−0.1;0.2] 0.1 [0.0;0.1]

1733 0.013 0.011 5.703

1733 0.012 0.009 5.146

1733 0.008 0.005 3.310

Table 13: Regression on socio-demographic characteristics

(Intercept) young workexp master female Num.Obs. R2 R2 Adj. F

spop

deor

crea

2.9 [2.8;3.0] −0.1 [−0.2;0.0] 0.2 [0.1;0.3] 0.1 [0.0;0.2] −0.1 [−0.2;0.0]

2.9 [2.8;3.1] −0.2 [−0.3;0.0] 0.1 [0.1;0.2] −0.1 [−0.2;0.1] −0.1 [−0.2;0.0]

2.9 [2.8;3.0] −0.1 [−0.2;0.0] 0.1 [0.0;0.2] −0.1 [−0.2;0.0] 0.0 [−0.1;0.0]

1733 0.031 0.029 14.033

1733 0.016 0.014 6.978

1733 0.005 0.003 2.350

In the competence area Ideas and Opportunities we observe that the age of the respondent only partly affects the competences significantly. Design Orientation and Spotting Opportunities are the only competences that are significantly lower for younger respondents. Work experience, however, affects most competences in the area of Ideas and Opportunities positively and significantly. Only Sustainable and Ethical Thinking are not affected by work experience. Overall, the level the higher education programs such as Bachelors or Masters do not affect the respondents Ideas and Opportunity competences. An interesting picture is revealed by the parameter estimated of the female dummy variable. Female respondents have a higher level of Sustainable and Ethical Thinking competences. Whereas they have a lower level of Design Orientation, Spotting Opportunities, and Valuing Ideas.

crea deor young

spop sust vaid visi crea deor

workexp

spop sust vaid visi crea deor

master

spop sust vaid visi crea deor

female

spop sust vaid visi −0.3

−0.2

−0.1

0.0

0.1

0.2

Coefficient estimates and 95% confidence intervals Figure 6: Regression on socio-demographic characteristics 30

0.3

Competence Area: Resources Table 14: Regression on socio-demographic characteristics

(Intercept) young workexp master female Num.Obs. R2 R2 Adj. F

self

othr

moti

3.0 [2.9;3.1] 0.0 [−0.1;0.1] 0.1 [0.1;0.2] 0.0 [−0.1;0.2] 0.0 [−0.1;0.0]

2.9 [2.7;3.0] 0.0 [−0.1;0.1] 0.1 [0.1;0.2] −0.2 [−0.3;−0.1] 0.0 [0.0;0.1]

3.1 [3.0;3.2] −0.1 [−0.2;0.0] 0.1 [0.1;0.2] 0.1 [0.0;0.3] −0.1 [−0.2;0.0]

1733 0.008 0.006 3.678

1733 0.012 0.009 5.061

1733 0.017 0.015 7.536

Table 15: Regression on socio-demographic characteristics

(Intercept) young workexp master female Num.Obs. R2 R2 Adj. F

mobi

litr

dico

2.6 [2.4;2.7] −0.1 [−0.2;0.0] 0.2 [0.1;0.2] 0.0 [−0.2;0.1] −0.1 [−0.2;0.0]

2.6 [2.5;2.8] 0.0 [−0.2;0.1] 0.1 [0.1;0.2] 0.2 [0.1;0.4] −0.1 [−0.2;0.0]

2.7 [2.6;2.8] −0.1 [−0.2;0.0] 0.1 [0.1;0.2] 0.0 [−0.2;0.1] −0.1 [−0.1;0.0]

1733 0.015 0.012 6.468

1733 0.017 0.015 7.688

1733 0.013 0.011 5.721

dico litr young

mobi moti othr self dico litr

workexp

mobi moti othr self dico litr

master

mobi moti othr self dico litr

female

mobi moti othr self −0.2

0.0

0.2

Coefficient estimates and 95% confidence intervals Figure 7: Regression on socio-demographic characteristics 32

In the competence area Resources, we only see a difference between younger and older respondent in the level of the Digital Competences. All other competences in this area are not associated with age. Work experience, however, is positively associated with all of the competences in this area: Digital Competences, Enterprising Literacy, Mobilizing Ressources, Motivation, Mobilizing Others, and Self Efficacy. Master students (as compared to Bachelor students) report a higher level of Enterprising Literacy. Female students report significantly lower levels of Enterprising Literacy, Mobilizing Resources, and Motivating Others.

Competence Area: Into Action Table 16: Regression on socio-demographic characteristics

(Intercept) young workexp master female

work

proc

plan

3.1 [2.9;3.2] −0.1 [−0.2;0.0] 0.1 [0.0;0.2] −0.1 [−0.2;0.1] 0.2 [0.1;0.2]

2.9 [2.8;3.1] 0.0 [−0.2;0.1] 0.1 [0.0;0.2] 0.1 [−0.1;0.2] 0.0 [0.0;0.1]

2.8 [2.7;3.0] 0.0 [−0.2;0.1] 0.1 [0.0;0.2] 0.1 [0.0;0.3] 0.1 [0.0;0.2]

1733 0.015 0.013 6.598

1733 0.007 0.005 3.141

1733 0.013 0.011 5.861

Num.Obs. R2 R2 Adj. F

Table 17: Regression on socio-demographic characteristics

(Intercept) young workexp master female Num.Obs. R2 R2 Adj. F

lepx

init

dval

cope

3.2 [3.1;3.4] 0.0 [−0.2;0.1] 0.1 [0.0;0.2] −0.1 [−0.2;0.1] 0.1 [0.0;0.1]

3.4 [3.2;3.5] −0.1 [−0.3;0.0] 0.1 [0.0;0.2] 0.1 [0.0;0.2] 0.1 [0.0;0.1]

2.7 [2.6;2.9] −0.1 [−0.3;0.0] 0.0 [0.0;0.1] −0.4 [−0.5;−0.2] −0.1 [−0.2;0.0]

2.8 [2.6;2.9] −0.1 [−0.2;0.1] 0.1 [0.0;0.2] 0.0 [−0.2;0.1] −0.1 [−0.2;0.0]

1733 0.007 0.004 2.835

1733 0.014 0.012 6.236

1733 0.017 0.015 7.602

1733 0.008 0.006 3.414

cope dval init young

lepx plan proc work cope dval

workexp

init lepx plan proc work cope dval

master

init lepx plan proc work cope dval

female

init lepx plan proc work −0.4

−0.2

0.0

0.2

Coefficient estimates and 95% confidence intervals Figure 8: Regression on socio-demographic characteristics 35

In the competence area of Into Action,younger respondents report higher levels of competences in Learning through experience, Planning and management, Process management, and Coping with uncertainty, ambiguity and risk. Work experience is associated with higher levels of competences in the Into Action area: Taking the initiative , Planning and management , Process management , Coping with uncertainty, ambiguity, and risk, Working with others , and Learning through experience (lepx). The only exception here is Design validation which is not associated significantly with work experience. Master programs are associated with a more diverse profile of competences. They are associated with lower levels of Design validation and co-creation, and with higher levels of Taking the initiative and Planning and management,. Female respondents show a lower level of Coping with uncertainty, ambiguity, and risk and a lower level of Design validation competences. Yet, they report higher levels of Planning and management and Working with others.

Austria

Austria [This analysis is based on the reported nationality of the respondent regardless of the location of the HEI the respondent is currently attending] This is the analysis for all countries involved in the EICAA project: Austria, Belgium, Germany, Hungary, and Spain.

Summary of the Competences In the following we summarize and visualize the competences grouped by competence areas Ideas and Opportunities, Resources, and Into Action. We first report the standard summary statistics (minimum, 25% quantile as x25 -, mean, median, standard deviation, 75% quantile as x75 -, maximum). Then we provide a plot that illustrates the distribution of the competences. The color coding helps to identify the levels None ■, Basic ■, Intermediate ■, Advanced ■, Expert ■, Note that the numerical values of the computations and the visualization base on the raw values of the survey. The values are not normalized or standardized as in the dashboard of the EICAA competence monitor. Competence Areas The entrepreneurship competences of the EICAA framework consist of three different competence areas that each comprise competences which we will investigate in more detail further down in the document. These competence areas are Ideas and Opportunities, Resources, and Into Action. Summary Statistics Table 18: Descriptives of the Competence Areas Variable

Min

x25

Mean

Median

x75

Max

IaO 99 0 2.5 2.9 0.71 2.9 3.4 4.4 Res 99 0 2.5 2.9 0.68 2.9 3.4 4.3 IAc 99 0 2.6 3 0.71 3 3.5 4.5 Note: IaO = Ideas and Opportunities, Res = Resources, IAc = Into Action

Competence

Distributions

Res

IaO

IAc None

Basic

Intermed.

Advanced

Expert

Competence Area: Ideas and Opportunities The competence area Ideas and Opportunities comprises of the following competences: Spotting opportunities (spop), Design orientation (deor), Creativity (crea), Vision (visi), Valuing ideas (vaid), Ethical and sustainable thinking (sust). Table 19: Descriptives of the Competence Area Ideas and Opportunities Variable

Min

x25

Mean

Median

x75

Max

visi vaid sust spop crea

99 99 99 99 99

0 0 0 0 0

2.3 2 2.8 2.6 2.4

2.9 2.5 3.1 3.1 3

0.8 0.87 0.78 0.77 0.84

3 2.3 3 3 3

3.3 3 3.8 3.6 3.6

4.7 4.3 4.8 5 5

deor 99 0 2.3 3 0.87 3 3.7 4.7 Note: visi = Vision, vaid = Valuing ideas, sust = Ethical and sustainable thinking, spop = Spotting opportunities, crea = Creativity, deor = Design orientation.

Competence

visi vaid sust spop deor crea None

Basic

Intermed.

Advanced

Expert

Competence Area: Resources The competence area Resources comprises of the following competences: Self-awareness and self-efficacy (self), Motivation and perseverance (moti), Mobilising (financial) resources (mobi), Enterprising literacy (litr), Mobilising others (othr), and Digital competence (dico). Table 20: Descriptives of the Competence Area Resources Variable

Min

x25

Mean

Median

x75

Max

self othr moti mobi litr

99 99 99 99 99

0 0 0 0 0

2.5 2.6 2.8 2 2.4

3.1 3.1 3.2 2.6 2.8

0.82 0.78 0.84 0.82 0.8

3 3.2 3.2 2.6 3

3.5 3.6 4 3.1 3.2

5 4.7 5 5 4.2

dico 99 0 2.2 2.9 0.9 2.8 3.5 5 Note: self = Self-awareness and self-efficacy, othr = Mobilising others, moti = Motivation and perseverance, mobi = Mobilising resources, litr = Enterprising literacy, dico = Digital competences.

Competence

self othr moti mobi litr dico None

Basic

Intermed.

Advanced

Expert

Competence Area: Into Action The competence area Into Action comprises of the following competences: Taking the initiative (init), Planning and management (plan), Process management (proc), Coping with uncertainty, ambiguity, and risk (cope), Design validation and co-creation (dval), Working with others (work), and Learning through experience (lepx). Table 21: Descriptives of the Competence Area Into Action Variable

Min

x25

Mean

Median

x75

Max

work proc plan lepx init

99 99 99 99 99

0 0 0 0 0

2.6 2.4 2.4 3 3

3.2 2.9 3 3.4 3.5

0.83 0.78 0.87 0.85 0.88

3.1 2.8 3 3.3 3.3

3.8 3.4 3.6 4 4

4.8 4.8 5 5 5

dval 99 0 2 2.5 0.96 2.3 3 5 cope 99 0 2 2.7 0.86 2.7 3.3 4.3 Note: work = Working with others, proc = Process management, plan = Planning and management, lepx = Learning through experience, init = Taking the initiative, dval = Design validation and co-creation, cope = Coping with uncertainty, ambiguity, and risk

Competence

work proc plan lepx init dval cope None

Basic

Intermed.

Advanced

Expert

Segmentation Analysis Segmentation Based on Gender The participant’s gender is not always provided in the survey. In the sample that is the basis of the analysis we have a total of 99 observation. The gender is contained in the data of all observations. In the table below we provide an overview of the distribution of the respondents over their self reported gender identities. Table 22: Summary Statistics Variable

Percent

Gender ... male ... female ... prefer-not-to-say ... nonbinary

99 50 48 1 0

51% 48% 1% 0%

For the analysis in this section, we keep the observations where gender takes the following values: male, female. All other observations are not taken into account. In this section we segment the sample based on gender. This allows us to observe the shifting of the competences across different gender identities. We show the descriptive statistics of the competence areas broken down on gender. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different genders. Please note that the competence levels are abbreviated by their first capital letter.

Table 23: Descriptives of Competence Area by Gender Variable

Min

x25

Mean

Median

x75

Max

gender: male IaO Res IAc gender: female

50 50 50

1.5 1.5 1.6

2.4 2.6 2.6

2.8 2.9 3

0.61 0.56 0.63

2.9 2.9 2.9

3.2 3.3 3.5

4.2 4.3 4.5

IaO Res IAc

48 48 48

0 0 0

2.6 2.4 2.6

3 3 3

0.81 0.8 0.78

3 3 3.1

3.6 3.4 3.6

4.4 4.2 4.5

Competence

IaO

Res

IAc

female

male N

E N

Figure 9: Competence Areas by Gender

Segmentation Based on Age Groups The participant’s age is not always provided in the survey. In the sample that is the basis of the analysis we have a total of 99 observation. Age is contained in the data of all observations. In the table below we provide an overview of the distribution of the respondents over the age groups. Table 24: Summary Statistics Variable

Percent

ageGroup ... 18-23-years ... 24-30-years ... 31-40-years ... 41-50-years

99 72 25 2 0

73% 25% 2% 0%

... 51-plus-years

For the analysis in this section, we keep the observations where the respondents are in the following age groups: 18-23-years, 24-30-years. All other observations are not taken into account. In this section we segment the sample based on age groups. This allows us to observe the shifting of the competences across different generations of respondents. We show the descriptive statistics of the competence areas broken down on age groups. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different age groups. Please note that the competence levels are abbreviated by their first capital letter. Table 25: Descriptives of Competence Area by Age Group Variable

Min

x25

Mean

Median

x75

Max

ageGroup: 18-23-years IaO Res IAc ageGroup: 24-30-years

72 72 72

1.5 1.5 1.6

2.4 2.4 2.6

2.9 2.9 3

0.62 0.61 0.63

2.8 2.9 3

3.2 3.4 3.5

4.4 4.3 4.5

IaO Res IAc

25 25 25

0 0 0

2.7 2.6 2.7

3.1 3 3.1

0.94 0.89 0.9

3.2 3 3

3.6 3.9 3.6

4.4 4.1 4.4

Competence

IaO

Res

IAc

24−30−years

18−23−years N

E N

Figure 10: Competence Areas by Age Groups

Segmentation Based on the Major of the Study Program The participant’s major field of studies may not always provided in the survey. In the sample that is the basis of the analysis we have a total of 99 observation. The major field of studies is contained in the data of all observations. In the table below we provide an overview of the distribution of the respondents over the fields of study.

Table 26: Summary Statistics Variable

Percent

majorField ... business-and-administration ... other ... agriculture-forestry-and-fishery ... law

99 60 15 2 0

61% 15% 2% 0%

... teacher-training-and-education-science ... life-sciences ... manufacturing-and-processing ... transport-services ... computing

0 0 0 0 20

0% 0% 0% 0% 20%

... engineering-and-engineering-trades ... veterinary ... design ... communications-media-and-public-relations ... biological-sciences-agriculture-and-natural-resources

0 0 0 0 0

0% 0% 0% 0% 0%

... engineering ... religion-and-theology ... mathematics-and-sciences ... performing-arts ... journalism-and-information

0 1 1 0 0

0% 1% 1% 0% 0%

... personal-services ... health ... architecture-and-building ... graphik-and-audio-visual-arts ... environmental-protection

0 0 0 0 0

0% 0% 0% 0% 0%

... fine-arts ... social-services ... social-and-behavioral-science ... physical-sciences

0 0 0 0

0% 0% 0% 0%

For the analysis in this section, we keep the observations where the respondents are in the following fields of study: business-and-administration, other, computing. All other observations are not taken into account. In this section we segment the sample based on age groups. This allows us to observe the shifting of the competences across different study fields of the respondents.

We show the descriptive statistics of the competence areas broken down on the fields of study. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different fields of study. Please note that the competence levels are abbreviated by their first capital letter.

Competence

IaO

Res

IAc

computing

other

business N

E N

Figure 11: Competence Areas by Major Field of Studies

Segmentation Based on Work Experience The participant’s work experience may not always provided in the survey. In the sample that is the basis of the analysis we have a total of 99 observation. The work experience is contained in the data of all observations. In the table below we provide an overview of the distribution of the respondents over the age groups. Table 27: Summary Statistics Variable

Percent

hasWorkExperience ... yes ... no

99 84 15

85% 15%

For the analysis in this section, we keep the observations where the respondents are in the following groups of work experience: yes, no. All other observations are not taken into account. In this section we segment the sample based on work experience. This allows us to observe the shifting of the competences across different levels of work experience of respondents. We show the descriptive statistics of the competence areas broken down on work experience. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across groups with and without work experience. Please note that the competence levels are abbreviated by their first capital letter. Table 28: Descriptives of Competence Area by Age Group Variable

Min

x25

Mean

Median

x75

Max

hasWorkExperience: yes IaO Res IAc hasWorkExperience: no

84 84 84

0 0 0

2.5 2.5 2.7

3 3 3.1

0.73 0.7 0.72

2.9 2.9 3

3.5 3.4 3.5

4.4 4.3 4.5

IaO Res IAc

15 15 15

1.5 1.5 1.6

2.3 2.5 2.5

2.7 2.7 2.8

0.54 0.57 0.61

2.8 2.7 3

3 3.1 3.2

3.5 3.7 3.8

Competence

IaO

Res

IAc

yes N

E N

Figure 12: Competence Areas by Work Experience

Belgium

Belgium This is the analysis for all countries involved in the EICAA project: Austria, Belgium, Germany, Hungary, and Spain.

Min

x25

Mean

Median

x75

Max

IaO 20 1.7 2.6 2.9 0.62 2.8 3.3 4 Res 20 1.9 2.5 3 0.55 3.1 3.3 3.8 IAc 20 2 2.9 3.2 0.6 3.3 3.6 4 Note: IaO = Ideas and Opportunities, Res = Resources, IAc = Into Action

Competence

Distributions

Res

IaO

IAc None

Basic

Intermed.

Advanced

Expert

Competence Area: Ideas and Opportunities The competence area Ideas and Opportunities comprises of the following competences: Spotting opportunities (spop), Design orientation (deor), Creativity (crea), Vision (visi), Valuing ideas (vaid), Ethical and sustainable thinking (sust). Table 30: Descriptives of the Competence Area Ideas and Opportunities Variable

Min

x25

Mean

Median

x75

Max

visi vaid sust spop crea

20 20 20 20 20

1.7 1.7 1.8 1.8 1.8

2.3 2 2.5 2.9 2.3

3 2.5 3 3.2 2.9

0.84 0.59 0.79 0.77 0.77

3 2.5 2.8 3.1 2.8

3.3 3 3.5 4 3.4

4.7 3.7 4.8 4.5 4.8

deor 20 1 2.3 2.9 0.77 3 3.3 4.3 Note: visi = Vision, vaid = Valuing ideas, sust = Ethical and sustainable thinking, spop = Spotting opportunities, crea = Creativity, deor = Design orientation.

Competence

visi vaid sust spop deor crea None

Basic

Intermed.

Advanced

Expert

Competence Area: Resources The competence area Resources comprises of the following competences: Self-awareness and self-efficacy (self), Motivation and perseverance (moti), Mobilising (financial) resources (mobi), Enterprising literacy (litr), Mobilising others (othr), and Digital competence (dico). Table 31: Descriptives of the Competence Area Resources Variable

Min

x25

Mean

Median

x75

Max

self othr moti mobi litr

20 20 20 20 20

2 1.8 1.5 1 1.5

2.7 2.5 2.8 1.9 2.4

3.1 3 3.4 2.4 3.4

0.6 0.69 0.83 0.73 0.94

3.2 3.2 3.4 2.4 3.5

3.6 3.4 3.8 2.8 4

4 4.3 4.8 4 5

dico 20 1.2 2 2.7 0.79 2.8 3 4.8 Note: self = Self-awareness and self-efficacy, othr = Mobilising others, moti = Motivation and perseverance, mobi = Mobilising resources, litr = Enterprising literacy, dico = Digital competences.

Competence

self othr moti mobi litr dico None

Basic

Intermed.

Advanced

Expert

Competence Area: Into Action The competence area Into Action comprises of the following competences: Taking the initiative (init), Planning and management (plan), Process management (proc), Coping with uncertainty, ambiguity, and risk (cope), Design validation and co-creation (dval), Working with others (work), and Learning through experience (lepx). Table 32: Descriptives of the Competence Area Into Action Variable

Min

x25

Mean

Median

x75

Max

work proc plan lepx init

20 20 20 20 20

1.5 1.8 2 1.7 2.7

2.9 3 3 3 3.3

3.4 3.2 3.2 3.4 3.9

0.83 0.57 0.56 0.71 0.65

3.5 3.2 3.3 3.5 4

3.9 3.4 3.4 4 4.4

4.9 4.2 4 4.3 4.7

dval 20 1 1.8 2.5 1 2.3 3 4 cope 20 1.7 2.6 3 0.78 3 3.7 4.3 Note: work = Working with others, proc = Process management, plan = Planning and management, lepx = Learning through experience, init = Taking the initiative, dval = Design validation and co-creation, cope = Coping with uncertainty, ambiguity, and risk

Competence

work proc plan lepx init dval cope None

Basic

Intermed.

Advanced

Expert

Segmentation Analysis The segmentation analysis cannot be performed in a meaningful way based on the number of observations.

Germany

Germany This is the analysis for all countries involved in the EICAA project: Austria, Belgium, Germany, Hungary, and Spain.

Min

x25

Mean

Median

x75

Max

IaO 325 1 2.3 2.7 0.63 2.7 3.1 5 Res 325 1 2.3 2.7 0.64 2.7 3.1 5 IAc 325 1 2.5 2.9 0.68 2.9 3.3 5 Note: IaO = Ideas and Opportunities, Res = Resources, IAc = Into Action

Competence

Distributions

Res

IaO

IAc None

Basic

Intermed.

Advanced

Expert

Competence Area: Ideas and Opportunities The competence area Ideas and Opportunities comprises of the following competences: Spotting opportunities (spop), Design orientation (deor), Creativity (crea), Vision (visi), Valuing ideas (vaid), Ethical and sustainable thinking (sust). Table 34: Descriptives of the Competence Area Ideas and Opportunities Variable

Min

x25

Mean

Median

x75

Max

visi vaid sust spop crea

325 325 325 325 325

1 0.67 1 1.2 1

2.3 1.7 2.5 2.5 2.2

2.8 2.2 3 2.9 2.7

0.81 0.79 0.75 0.72 0.72

3 2 3 3 2.6

3.3 2.7 3.5 3.2 3.2

5 5 5 5 5

deor 325 1 2.3 2.7 0.81 2.7 3.3 5 Note: visi = Vision, vaid = Valuing ideas, sust = Ethical and sustainable thinking, spop = Spotting opportunities, crea = Creativity, deor = Design orientation.

Competence

visi vaid sust spop deor crea None

Basic

Intermed.

Advanced

Expert

Competence Area: Resources The competence area Resources comprises of the following competences: Self-awareness and self-efficacy (self), Motivation and perseverance (moti), Mobilising (financial) resources (mobi), Enterprising literacy (litr), Mobilising others (othr), and Digital competence (dico). Table 35: Descriptives of the Competence Area Resources Variable

Min

x25

Mean

Median

x75

Max

self othr moti mobi litr

325 325 325 325 325

1 1 1 1 1

2.5 2.2 2.5 1.8 2

2.9 2.7 3.1 2.4 2.7

0.76 0.79 0.79 0.82 0.82

3 2.8 3.2 2.4 2.8

3.5 3.2 3.8 3 3.2

5 5 5 5 5

dico 325 1 2 2.5 0.79 2.5 3 5 Note: self = Self-awareness and self-efficacy, othr = Mobilising others, moti = Motivation and perseverance, mobi = Mobilising resources, litr = Enterprising literacy, dico = Digital competences.

Competence

self othr moti mobi litr dico None

Basic

Intermed.

Advanced

Expert

Competence Area: Into Action The competence area Into Action comprises of the following competences: Taking the initiative (init), Planning and management (plan), Process management (proc), Coping with uncertainty, ambiguity, and risk (cope), Design validation and co-creation (dval), Working with others (work), and Learning through experience (lepx). Table 36: Descriptives of the Competence Area Into Action Variable

Min

x25

Mean

Median

x75

Max

work proc plan lepx init

325 325 325 325 325

1 1 1 1 1

2.4 2.4 2.4 2.7 3

3 2.9 2.9 3.2 3.4

0.84 0.77 0.79 0.82 0.85

3 2.8 2.8 3 3.3

3.5 3.4 3.4 3.7 4

5 5 5 5 5

dval 325 0.67 1.7 2.3 0.93 2 3 5 cope 325 1 2 2.6 0.85 2.7 3 5 Note: work = Working with others, proc = Process management, plan = Planning and management, lepx = Learning through experience, init = Taking the initiative, dval = Design validation and co-creation, cope = Coping with uncertainty, ambiguity, and risk

Competence

work proc plan lepx init dval cope None

Basic

Intermed.

Advanced

Expert

Segmentation Analysis Segmentation Based on Gender The participant’s gender is not always provided in the survey. In the sample that is the basis of the analysis we have a total of 325 observation. The gender is contained in the data of 313 observations. In the table below we provide an overview of the distribution of the respondents over their self reported gender identities. Table 37: Summary Statistics Variable

Percent

Gender ... male ... female ... prefer-not-to-say ... nonbinary

313 166 141 6 0

53% 45% 2% 0%

For the analysis in this section, we keep the observations where gender takes the following values: male, female, prefer-not-to-say. All other observations are not taken into account. In this section we segment the sample based on gender. This allows us to observe the shifting of the competences across different gender identities.

We show the descriptive statistics of the competence areas broken down on gender. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different genders. Please note that the competence levels are abbreviated by their first capital letter. Table 38: Descriptives of Competence Area by Gender Variable

Min

x25

Mean

Median

x75

Max

gender: male IaO Res IAc gender: female

166 166 166

1.3 1.3 1

2.4 2.3 2.4

2.7 2.7 2.8

0.64 0.66 0.68

2.7 2.6 2.8

3.1 3.1 3.2

5 5 5

IaO Res IAc gender: prefer-not-to-say IaO

141 141 141

1.2 1.2 1.3

2.3 2.4 2.5

2.7 2.8 3

0.63 0.62 0.68

2.7 2.8 3

3.1 3.2 3.4

4.2 4.6 4.9

2.4

0.82

2.5

2.8

3.4

Res IAc

6 6

1 1

2.3 2.1

2.4 2.5

0.87 0.98

2.5 2.5

2.7 2.7

3.7 4

Competence

IaO

Res

IAc

prefer−not−to−say

female

male N

E N

Figure 13: Competence Areas by Gender

Segmentation Based on Age Groups The participant’s age is not always provided in the survey. In the sample that is the basis of the analysis we have a total of 325 observation. Age is contained in the data of 317 observations. In the table below we provide an overview of the distribution of the respondents over the age groups. Table 39: Summary Statistics Variable

Percent

ageGroup ... 18-23-years ... 24-30-years ... 31-40-years ... 41-50-years

317 204 105 6 1

64% 33% 2% 0%

... 51-plus-years

For the analysis in this section, we keep the observations where the respondents are in the following age groups: 18-23-years, 24-30-years, 31-40-years. All other observations are not taken into account. In this section we segment the sample based on age groups. This allows us to observe the shifting of the competences across different generations of respondents. We show the descriptive statistics of the competence areas broken down on age groups. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different age groups. Please note that the competence levels are abbreviated by their first capital letter.

Table 40: Descriptives of Competence Area by Age Group Variable

Min

x25

Mean

Median

x75

Max

ageGroup: 18-23-years IaO Res IAc ageGroup: 24-30-years

204 204 204

1 1 1

2.3 2.3 2.4

2.7 2.7 2.8

0.63 0.66 0.68

2.7 2.7 2.8

3.1 3.1 3.2

4.8 5 5

IaO Res IAc ageGroup: 31-40-years IaO

105 105 105

1.3 1.3 1

2.3 2.5 2.5

2.7 2.8 2.9

0.6 0.58 0.67

2.8 2.8 3

3.1 3.1 3.3

4.2 4.3 4.2

2.4

0.74

3.1

3.5

3.8

Res IAc

6 6

2 2

2.7 2.8

3.1 3.1

0.69 0.76

3.1 3

3.6 3.6

3.9 4.1

Competence

IaO

Res

IAc

31−40−years

24−30−years

18−23−years N

E N

Figure 14: Competence Areas by Age Groups

is contained in the data of all observations. In the table below we provide an overview of the distribution of the respondents over the fields of study. Table 41: Summary Statistics Variable

Percent

majorField ... business-and-administration ... other ... agriculture-forestry-and-fishery ... law

325 239 14 5 1

74% 4% 2% 0%

... teacher-training-and-education-science ... life-sciences ... manufacturing-and-processing ... transport-services ... computing

3 0 0 0 10

1% 0% 0% 0% 3%

... engineering-and-engineering-trades ... veterinary ... design ... communications-media-and-public-relations ... biological-sciences-agriculture-and-natural-resources

19 0 20 0 0

6% 0% 6% 0% 0%

... engineering ... religion-and-theology ... mathematics-and-sciences ... performing-arts ... journalism-and-information

0 0 0 0 2

0% 0% 0% 0% 1%

... personal-services ... health ... architecture-and-building ... graphik-and-audio-visual-arts ... environmental-protection

2 1 7 0 2

1% 0% 2% 0% 1%

... fine-arts ... social-services ... social-and-behavioral-science ... physical-sciences

0 0 0 0

0% 0% 0% 0%

For the analysis in this section, we keep the observations where the respondents are in the following fields of study: business-and-administration, other, agriculture-forestry-and-fishery,

computing, engineering-and-engineering-trades, design, architecture-and-building. All other observations are not taken into account. In this section we segment the sample based on fields of study. This allows us to observe the shifting of the competences across different fields of study. We show the descriptive statistics of the competence areas broken down on the fields of study. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different fields of study. Please note that the competence levels are abbreviated by their first capital letter. IaO

Res

IAc

Competence

architecture design engineering computing agriculture other business N

E N

Figure 15: Competence Areas by Major Field of Studies

Segmentation Based on Work Experience The participant’s work experience may not always provided in the survey. In the sample that is the basis of the analysis we have a total of 325 observation. The work experience is contained in the data of 317 observations. In the table below we provide an overview of the distribution of the respondents over the work experience.

Table 42: Summary Statistics Variable

Percent

hasWorkExperience ... yes ... no

317 249 68

79% 21%

For the analysis in this section, we keep the observations where the respondents are in the following groups of workexperience: yes, no. All other observations are not taken into account. In this section we segment the sample based on work experience. This allows us to observe the shifting of the competences across different levels of work experience of the respondents. We show the descriptive statistics of the competence areas broken down on work experience. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across groups with and without work experience. Please note that the competence levels are abbreviated by their first capital letter. Table 43: Descriptives of Competence Area by Age Group Variable

Min

x25

Mean

Median

x75

Max

hasWorkExperience: yes IaO Res IAc hasWorkExperience: no

249 249 249

1.3 1.3 1

2.3 2.4 2.5

2.7 2.8 2.9

0.65 0.65 0.69

2.7 2.8 2.9

3.1 3.2 3.3

5 5 5

IaO Res IAc

68 68 68

1 1 1

2.4 2.2 2.5

2.7 2.6 2.8

0.58 0.64 0.68

2.7 2.6 2.8

3 3.1 3.2

4.1 4.6 4.9

Competence

IaO

Res

IAc

yes N

E N

Figure 16: Competence Areas by Work Experience

Hungary

Hungary This is the analysis for all countries involved in the EICAA project: Austria, Belgium, Germany, Hungary, and Spain.

Min

x25

Mean

Median

x75

Max

IaO 724 0.54 2.2 2.7 0.68 2.7 3.2 5 Res 724 0 2.2 2.7 0.7 2.7 3.2 5 IAc 724 0 2.3 2.9 0.74 2.8 3.4 5 Note: IaO = Ideas and Opportunities, Res = Resources, IAc = Into Action

Competence

Distributions

Res

IaO

IAc None

Basic

Intermed.

Advanced

Expert

Competence Area: Ideas and Opportunities The competence area Ideas and Opportunities comprises of the following competences: Spotting opportunities (spop), Design orientation (deor), Creativity (crea), Vision (visi), Valuing ideas (vaid), Ethical and sustainable thinking (sust). Table 45: Descriptives of the Competence Area Ideas and Opportunities Variable

Min

x25

Mean

Median

x75

Max

visi vaid sust spop crea

724 724 724 724 724

0 0 0 0.5 0

2 1.7 2.5 2.2 2.2

2.7 2.4 3.2 2.7 2.7

0.89 0.85 0.86 0.75 0.79

2.7 2.3 3.2 2.8 2.6

3.3 3 3.8 3.2 3.2

5 5 5 5 5

deor 724 0 2 2.5 0.9 2.3 3 5 Note: visi = Vision, vaid = Valuing ideas, sust = Ethical and sustainable thinking, spop = Spotting opportunities, crea = Creativity, deor = Design orientation.

Competence

visi vaid sust spop deor crea None

Basic

Intermed.

Advanced

Expert

Competence Area: Resources The competence area Resources comprises of the following competences: Self-awareness and self-efficacy (self), Motivation and perseverance (moti), Mobilising (financial) resources (mobi), Enterprising literacy (litr), Mobilising others (othr), and Digital competence (dico). Table 46: Descriptives of the Competence Area Resources Variable

Min

x25

Mean

Median

x75

Max

self othr moti mobi litr

724 724 724 724 724

0 0 0 0 0

2.5 2.2 2.5 1.8 2

3 2.8 3.1 2.4 2.6

0.82 0.85 0.89 0.88 0.88

3 2.8 3 2.4 2.5

3.5 3.5 3.8 3 3.2

5 5 5 5 5

dico 724 0 1.8 2.5 0.9 2.5 3 5 Note: self = Self-awareness and self-efficacy, othr = Mobilising others, moti = Motivation and perseverance, mobi = Mobilising resources, litr = Enterprising literacy, dico = Digital competences.

Competence

self othr moti mobi litr dico None

Basic

Intermed.

Advanced

Expert

Competence Area: Into Action The competence area Into Action comprises of the following competences: Taking the initiative (init), Planning and management (plan), Process management (proc), Coping with uncertainty, ambiguity, and risk (cope), Design validation and co-creation (dval), Working with others (work), and Learning through experience (lepx). Table 47: Descriptives of the Competence Area Into Action Variable

Min

x25

Mean

Median

x75

Max

work proc plan lepx init

724 724 724 724 724

0 0 0 0 0

2.4 2.2 2.2 2.7 2.7

3.1 2.8 2.8 3.2 3.4

0.9 0.83 0.89 0.9 0.92

3 2.8 2.8 3.3 3.5

3.8 3.4 3.4 4 4

5 5 5 5 5

dval 724 0 1.3 2.3 0.97 2.3 3 5 cope 724 0 1.7 2.5 0.9 2.3 3 5 Note: work = Working with others, proc = Process management, plan = Planning and management, lepx = Learning through experience, init = Taking the initiative, dval = Design validation and co-creation, cope = Coping with uncertainty, ambiguity, and risk

Competence

work proc plan lepx init dval cope None

Basic

Intermed.

Advanced

Expert

Segmentation Analysis Segmentation Based on Gender The participant’s gender is not always provided in the survey. In the sample that is the basis of the analysis we have a total of 724 observation. The gender is contained in the data of 41 observations. In the table below we provide an overview of the distribution of the respondents over their self reported gender identities. Table 48: Summary Statistics Variable

Percent

Gender ... male ... female ... prefer-not-to-say ... nonbinary

41 23 17 1 0

56% 41% 2% 0%

For the analysis in this section, we keep the observations where gender takes the following values: male, female. All other observations are not taken into account.

In this section we segment the sample based on gender. This allows us to observe the shifting of the competences across different gender identities. We show the descriptive statistics of the competence areas broken down on gender. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different genders. Please note that the competence levels are abbreviated by their first capital letter. Table 49: Descriptives of Competence Area by Gender Variable

Min

x25

Mean

Median

x75

Max

gender: male IaO Res IAc gender: female

23 23 23

1.9 2 1.9

2.4 2.8 3.1

2.9 3.2 3.3

0.62 0.6 0.65

3.2 3.2 3.5

3.4 3.6 3.7

4.1 4.5 4.2

IaO Res IAc

17 17 17

2 1.8 2.1

2.7 2.4 2.9

3 2.9 3.3

0.61 0.63 0.66

2.9 2.8 3.2

3.4 3.5 3.7

4 3.9 4.3

Competence

IaO

Res

IAc

female

male N

E N

Figure 17: Competence Areas by Gender

Segmentation Based on Age Groups The participant’s age is not always provided in the survey. In the sample that is the basis of the analysis we have a total of 724 observation. Age is contained in the data of 42 observations. In the table below we provide an overview of the distribution of the respondents over the age groups. Table 50: Summary Statistics Variable

Percent

ageGroup ... 18-23-years ... 24-30-years ... 31-40-years ... 41-50-years

42 39 3 0 0

93% 7% 0% 0%

... 51-plus-years

For the analysis in this section, we keep the observations where the respondents are in the following age groups: 18-23-years. All other observations are not taken into account. In this section we segment the sample based on age groups. This allows us to observe the shifting of the competences across different generations of respondents. We show the descriptive statistics of the competence areas broken down on age groups. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different age groups. Please note that the competence levels are abbreviated by their first capital letter. Table 51: Descriptives of Competence Area by Age Group Variable

Min

x25

Mean

Median

x75

Max

ageGroup: 18-23-years IaO Res IAc

39 39 39

1.9 1.8 1.9

2.5 2.6 3

2.9 3 3.3

0.61 0.62 0.64

2.9 3.1 3.3

3.4 3.6 3.7

4.1 4.5 4.3

Res

IAc

Competence

IaO

18−23−years N

E N

Figure 18: Competence Areas by Age Groups Segmentation Based on the Major of the Study Program The participant’s major field of studies may not always provided in the survey. In the sample that is the basis of the analysis we have a total of 724 observation. The major field of studies is contained in the data of all observations. In the table below we provide an overview of the distribution of the respondents over the fields of study.

Table 52: Summary Statistics Variable

Percent

majorField ... business-and-administration ... other ... agriculture-forestry-and-fishery ... law

724 723 0 0 0

100% 0% 0% 0%

... teacher-training-and-education-science ... life-sciences ... manufacturing-and-processing ... transport-services ... computing

0 0 0 0 1

0% 0% 0% 0% 0%

... engineering-and-engineering-trades ... veterinary ... design ... communications-media-and-public-relations ... biological-sciences-agriculture-and-natural-resources

0 0 0 0 0

0% 0% 0% 0% 0%

... engineering ... religion-and-theology ... mathematics-and-sciences ... performing-arts ... journalism-and-information

0 0 0 0 0

0% 0% 0% 0% 0%

... personal-services ... health ... architecture-and-building ... graphik-and-audio-visual-arts ... environmental-protection

0 0 0 0 0

0% 0% 0% 0% 0%

... fine-arts ... social-services ... social-and-behavioral-science ... physical-sciences

0 0 0 0

0% 0% 0% 0%

For the analysis in this section, we keep the observations where the respondents are in the following fields of study: business-and-administration. All other observations are not taken into account. In this section we segment the sample based on fields of study. This allows us to observe the shifting of the competences across different educational foci of respondents.

IAc

Competence

IaO

business N

E N

Figure 19: Competence Areas by Major Field of Studies

Segmentation Based on Work Experience The participant’s work experience may not always provided in the survey. In the sample that is the basis of the analysis we have a total of 724 observation. The work experience is contained in the data of 42 observations. In the table below we provide an overview of the distribution of the respondents over the work experience. Table 53: Summary Statistics Variable

Percent

hasWorkExperience ... yes ... no

42 29 13

69% 31%

For the analysis in this section, we keep the observations where the respondents are in the following groups of workexperience: yes, no. All other observations are not taken into account. In this section we segment the sample based on work experience. This allows us to observe the shifting of the competences across different levels of work experience of respondents. We show the descriptive statistics of the competence areas broken down on work experience. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across groups with and without work experience. Please note that the competence levels are abbreviated by their first capital letter. Table 54: Descriptives of Competence Area by Age Group Variable

Min

x25

Mean

Median

x75

Max

hasWorkExperience: yes IaO Res IAc hasWorkExperience: no

29 29 29

2 2 2

2.7 2.7 3

3.1 3.1 3.4

0.57 0.61 0.56

3.2 3.2 3.5

3.4 3.6 3.7

4.1 4.5 4.3

IaO Res IAc

13 13 13

1.9 1.8 1.9

2.1 2.4 2.5

2.7 2.9 3.1

0.6 0.56 0.72

2.5 2.8 3.2

3.2 3.2 3.6

3.6 3.7 4.2

Competence

IaO

Res

IAc

yes N

E N

Figure 20: Competence Areas by Work Experience

Spain

Spain This is the analysis for all countries involved in the EICAA project: Austria, Belgium, Germany, Hungary, and Spain.

Min

x25

Mean

Median

x75

Max

IaO 1220 1.3 2.4 2.8 0.6 2.9 3.2 5 Res 1220 1 2.4 2.8 0.62 2.8 3.2 5 IAc 1220 1.2 2.6 3 0.64 3 3.4 5 Note: IaO = Ideas and Opportunities, Res = Resources, IAc = Into Action

Competence

Distributions

Res

IaO

IAc None

Basic

Intermed.

Advanced

Expert

Competence Area: Ideas and Opportunities The competence area Ideas and Opportunities comprises of the following competences: Spotting opportunities (spop), Design orientation (deor), Creativity (crea), Vision (visi), Valuing ideas (vaid), Ethical and sustainable thinking (sust). Table 56: Descriptives of the Competence Area Ideas and Opportunities Variable

Min

x25

Mean

Median

x75

Max

visi vaid sust spop crea

1220 1220 1220 1220 1220

1 1 1 1 1.2

2.3 2 2.5 2.5 2.4

2.7 2.6 3 2.9 2.9

0.78 0.79 0.76 0.68 0.71

2.7 2.7 3 3 3

3.3 3 3.5 3.5 3.4

5 5 5 5 5

deor 1220 1 2.3 2.9 0.75 3 3.3 5 Note: visi = Vision, vaid = Valuing ideas, sust = Ethical and sustainable thinking, spop = Spotting opportunities, crea = Creativity, deor = Design orientation.

Competence

visi vaid sust spop deor crea None

Basic

Intermed.

Advanced

Expert

Competence Area: Resources The competence area Resources comprises of the following competences: Self-awareness and self-efficacy (self), Motivation and perseverance (moti), Mobilising (financial) resources (mobi), Enterprising literacy (litr), Mobilising others (othr), and Digital competence (dico). Table 57: Descriptives of the Competence Area Resources Variable

Min

x25

Mean

Median

x75

Max

self othr moti mobi litr

1220 1220 1220 1220 1220

1 1 1 1 1

2.5 2.5 2.5 2 2

3 3 3.1 2.6 2.6

0.75 0.76 0.77 0.78 0.85

3 3 3 2.6 2.5

3.5 3.5 3.5 3 3.2

5 5 5 5 5

dico 1220 1 2 2.7 0.78 2.8 3.2 5 Note: self = Self-awareness and self-efficacy, othr = Mobilising others, moti = Motivation and perseverance, mobi = Mobilising resources, litr = Enterprising literacy, dico = Digital competences.

Competence

self othr moti mobi litr dico None

Basic

Intermed.

Advanced

Expert

Competence Area: Into Action The competence area Into Action comprises of the following competences: Taking the initiative (init), Planning and management (plan), Process management (proc), Coping with uncertainty, ambiguity, and risk (cope), Design validation and co-creation (dval), Working with others (work), and Learning through experience (lepx). Table 58: Descriptives of the Competence Area Into Action Variable

Min

x25

Mean

Median

x75

Max

work proc plan lepx init

1220 1220 1220 1220 1220

1 1 1 1 1

2.6 2.4 2.4 2.7 2.7

3.1 3 2.9 3.3 3.3

0.76 0.72 0.74 0.85 0.82

3.1 3 2.8 3.3 3.3

3.6 3.4 3.4 4 4

5 5 5 5 5

dval 1220 1 2 2.7 0.87 2.7 3.3 5 cope 1220 1 2 2.7 0.84 2.7 3.3 5 Note: work = Working with others, proc = Process management, plan = Planning and management, lepx = Learning through experience, init = Taking the initiative, dval = Design validation and co-creation, cope = Coping with uncertainty, ambiguity, and risk

Competence

work proc plan lepx init dval cope None

Basic

Intermed.

Advanced

Expert

Segmentation Analysis Segmentation Based on Gender The participant’s gender is not always provided in the survey. In the sample that is the basis of the analysis we have a total of 1220 observation. The gender is contained in the data of 1216 observations. In the table below we provide an overview of the distribution of the respondents over their self reported gender identities. Table 59: Summary Statistics Variable

Percent

Gender ... male ... female ... prefer-not-to-say ... nonbinary

1216 731 456 20 9

60% 38% 2% 1%

For the analysis in this section, we keep the observations where gender takes the following values: male, female, prefer-not-to-say, nonbinary. All other observations are not taken into account.

In this section we segment the sample based on gender. This allows us to observe the shifting of the competences across different gender identities. We show the descriptive statistics of the competence areas broken down on gender. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different genders. Please note that the competence levels are abbreviated by their first capital letter. Table 60: Descriptives of Competence Area by Gender Variable

Min

x25

Mean

Median

x75

Max

gender: male IaO Res IAc gender: female

731 731 731

1.3 1 1.2

2.4 2.4 2.6

2.9 2.9 3

0.61 0.63 0.64

2.9 2.9 3

3.2 3.3 3.4

5 5 5

IaO Res IAc gender: prefer-not-to-say IaO

456 456 456

1.5 1.2 1.4

2.3 2.3 2.6

2.8 2.7 3

0.57 0.61 0.64

2.8 2.7 3

3.2 3.2 3.4

4.6 4.8 4.8

1.7

2.4

2.8

0.63

2.9

3.3

Res IAc gender: nonbinary IaO Res

20 20

1.4 1.9

1.9 2.5

2.6 2.9

0.72 0.61

2.7 2.9

3.1 3.3

3.8 3.8

9 9

1.7 1.6

2.8 2.6

2.9 2.8

0.66 0.57

3.1 2.9

3.4 3.2

3.8 3.4

IAc

2.4

2.7

3.1

0.49

3.4

3.5

3.6

Segmentation Based on Age Groups The participant’s age is not always provided in the survey. In the sample that is the basis of the analysis we have a total of 1220 observation. Age is contained in the data of 1187 observations. In the table below we provide an overview of the distribution of the respondents over the age groups.

Competence

IaO

Res

IAc

nonbinary

prefer−not−to−say

female

male N

E N

Figure 21: Competence Areas by Gender Table 61: Summary Statistics Variable

Percent

ageGroup ... 18-23-years ... 24-30-years ... 31-40-years ... 41-50-years

1187 1102 81 4 0

93% 7% 0% 0%

... 51-plus-years

Table 62: Descriptives of Competence Area by Age Group Variable

Min

x25

Mean

Median

x75

Max

ageGroup: 18-23-years IaO Res IAc ageGroup: 24-30-years

1102 1102 1102

1.3 1 1.2

2.4 2.4 2.6

2.8 2.8 3

0.59 0.62 0.63

2.9 2.8 3

3.2 3.2 3.4

5 5 5

IaO Res IAc ageGroup: 31-40-years IaO

81 81 81

1.6 1.4 1.5

2.7 2.6 2.7

3.1 3 3.2

0.58 0.58 0.68

3.1 3 3.2

3.4 3.4 3.7

4.9 4.8 4.6

2.1

2.4

2.7

0.51

2.8

3.1

3.2

Res IAc

4 4

2.1 3

2.4 3

2.7 3.2

0.51 0.16

2.7 3.1

3.1 3.3

3.3 3.3

Competence

IaO

Res

IAc

31−40−years

24−30−years

18−23−years N

E N

Figure 22: Competence Areas by Age Groups

is contained in the data of all observations. In the table below we provide an overview of the distribution of the respondents over the fields of study. Table 63: Summary Statistics Variable

Percent

majorField ... business-and-administration ... other ... agriculture-forestry-and-fishery ... law

1220 389 44 4 0

32% 4% 0% 0%

... teacher-training-and-education-science ... life-sciences ... manufacturing-and-processing ... transport-services ... computing

1 6 0 13 232

0% 0% 0% 1% 19%

... engineering-and-engineering-trades ... veterinary ... design ... communications-media-and-public-relations ... biological-sciences-agriculture-and-natural-resources

24 0 18 0 0

2% 0% 1% 0% 0%

... engineering ... religion-and-theology ... mathematics-and-sciences ... performing-arts ... journalism-and-information

0 0 0 0 0

0% 0% 0% 0% 0%

... personal-services ... health ... architecture-and-building ... graphik-and-audio-visual-arts ... environmental-protection

0 204 0 213 0

0% 17% 0% 17% 0%

... fine-arts ... social-services ... social-and-behavioral-science ... physical-sciences

2 1 37 32

0% 0% 3% 3%

For the analysis in this section, we keep the observations where the respondents are in the following fields of study: business-and-administration, other, agriculture-forestry-and-fishery,

life-sciences, transport-services, computing, engineering-and-engineering-trades, design, health, graphik-and-audio-visual-arts, social-and-behavioral-science, physical-sciences. All other observations are not taken into account. In this section we segment the sample based on fields of study. This allows us to observe the shifting of the competences across different educational foci of respondents. We show the descriptive statistics of the competence areas broken down on fields of study. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across different fields of study. Please note that the competence levels are abbreviated by their first capital letter.

Competence

IaO

Res

IAc

physical social graphik health design engineering computing transport life agriculture other business N

E N

Figure 23: Competence Areas by Major Field of Studies

Segmentation Based on Work Experience The participant’s work experience may not always provided in the survey. In the sample that is the basis of the analysis we have a total of 1220 observation. The work experience is contained in the data of 1216 observations. In the table below we provide an overview of the distribution of the respondents over the work experience.

Table 64: Summary Statistics Variable

Percent

hasWorkExperience ... yes ... no

1216 811 405

67% 33%

For the analysis in this section, we keep the observations where the respondents are in the following groups of workexperience: yes, no. All other observations are not taken into account. In this section we segment the sample based on work experience. This allows us to observe the shifting of the competences across different levels of work experience of the respondents. We show the descriptive statistics of the competence areas broken down on work experience. We abbreviate the competence areas (IaO = Ideas and Opportunities, Res = Resources, and IAc = Into Action). The figure below visualizes the differences of the competence distribution across groups with and without work experience. Please note that the competence levels are abbreviated by their first capital letter. Table 65: Descriptives of Competence Area by Age Group Variable

Min

x25

Mean

Median

x75

Max

hasWorkExperience: yes IaO Res IAc hasWorkExperience: no

811 811 811

1.3 1.2 1.2

2.4 2.4 2.6

2.9 2.9 3

0.6 0.62 0.64

2.9 2.9 3

3.3 3.3 3.4

4.9 4.8 4.8

IaO Res IAc

405 405 405

1.3 1 1.2

2.3 2.3 2.5

2.7 2.7 3

0.59 0.61 0.63

2.8 2.8 3

3.2 3.1 3.4

5 5 5

Competence

IaO

Res

IAc

yes N

E N

Figure 24: Competence Areas by Work Experience

All Countries Employee Data

All Countries - Employee Data Summary of the Competences In the following we summarize and visualize the competences grouped by competence areas Ideas and Opportunities, Resources, and Into Action. We first report the standard summary statistics (minimum, 25% quantile as x25 -, mean, median, standard deviation, 75% quantile as x75 -, maximum). Then we provide a plot that illustrates the distribution of the competences. The color coding helps to identify the levels • None ■, • Basic ■, • Intermediate ■, • Advanced ■, • Expert ■, Note that the numerical values of the computations and the visualization base on the raw values of the survey. The values are not normalized or standardized as in the dashboard of the EICAA competence monitor. Competence Areas The entrepreneurship competences of the EICAA framework consist of three different competence areas that each comprise competences which we will investigate in more detail further down in the document. These competence areas are Ideas and Opportunities, Resources, and Into Action. Summary Statistics Table 66: Descriptives of the Competence Areas Variable

Min

x25

Mean

Median

x75

Max

IaO 251 1.6 2.8 3.3 0.71 3.3 3.8 5 Res 251 1.2 2.9 3.2 0.68 3.2 3.6 5 IAc 251 1.5 3 3.5 0.69 3.5 3.8 5 Note: IaO = Ideas and Opportunities, Res = Resources, IAc = Into Action

Competence

Distributions

Res

IaO

IAc None

Basic

Intermed.

Advanced

Expert

Competence Area: Ideas and Opportunities The competence area Ideas and Opportunities comprises of the following competences: Spotting opportunities (spop), Design orientation (deor), Creativity (crea), Vision (visi), Valuing ideas (vaid), Ethical and sustainable thinking (sust). Table 67: Descriptives of the Competence Area Ideas and Opportunities Variable

Min

x25

Mean

Median

x75

Max

visi vaid sust spop crea

251 251 251 251 251

1.3 1 1.5 1.2 1.2

2.7 2 3 3 2.8

3.4 2.8 3.5 3.4 3.4

0.87 0.92 0.84 0.78 0.81

3.3 3 3.8 3.5 3.4

4 3.3 4 4 3.8

5 5 5 5 5

deor 251 1 3 3.4 0.84 3.3 4 5 Note: visi = Vision, vaid = Valuing ideas, sust = Ethical and sustainable thinking, spop = Spotting opportunities, crea = Creativity, deor = Design orientation.

100

Competence

visi vaid sust spop deor crea None

Basic

Intermed.

Advanced

Expert

Competence Area: Resources The competence area Resources comprises of the following competences: Self-awareness and self-efficacy (self), Motivation and perseverance (moti), Mobilising (financial) resources (mobi), Enterprising literacy (litr), Mobilising others (othr), and Digital competence (dico). Table 68: Descriptives of the Competence Area Resources Variable

Min

x25

Mean

Median

x75

Max

self othr moti mobi litr

251 251 251 251 251

1 1.2 1 1.2 1

3 2.8 3.2 2.2 2.2

3.5 3.3 3.7 2.9 3

0.76 0.79 0.8 0.92 0.98

3.5 3.3 3.8 2.8 3

4 3.8 4.2 3.4 3.8

5 5 5 5 5

dico 251 1 2.5 3 0.8 3 3.8 5 Note: self = Self-awareness and self-efficacy, othr = Mobilising others, moti = Motivation and perseverance, mobi = Mobilising resources, litr = Enterprising literacy, dico = Digital competences.

101

Competence

self othr moti mobi litr dico None

Basic

Intermed.

Advanced

Expert

Competence Area: Into Action The competence area Into Action comprises of the following competences: Taking the initiative (init), Planning and management (plan), Process management (proc), Coping with uncertainty, ambiguity, and risk (cope), Design validation and co-creation (dval), Working with others (work), and Learning through experience (lepx). Table 69: Descriptives of the Competence Area Into Action Variable

Min

x25

Mean

Median

x75

Max

work proc plan lepx init

251 251 251 251 251

1.1 1 1 1 2

3.1 3 3 3 3.3

3.7 3.4 3.5 3.7 3.9

0.79 0.8 0.81 0.81 0.72

3.6 3.4 3.6 4 4

4.2 4 4 4 4.3

5 5 5 5 5

dval 251 1 2 2.9 1 3 3.7 5 cope 251 1 2.3 3.1 0.97 3 3.7 5 Note: work = Working with others, proc = Process management, plan = Planning and management, lepx = Learning through experience, init = Taking the initiative, dval = Design validation and co-creation, cope = Coping with uncertainty, ambiguity, and risk

102

Competence

work proc plan lepx init dval cope None

Basic

Intermed.

103

Advanced

Expert

GET IN TOUCH WITH US

http://www.eicaa.eu

EICAA Project Coordinator Florian Bratzke Univations GmbH mailto:bratzke@univations.de

twitter.com/

facebook.com/

Linkedin.com/company/

EICAAproject

eicaaproject/

The information and views set out in this publication are those of the authors and do not necessarily reflect the official opinion of the European Union. Neither the European Union institutions and bodies nor any person acting on their behalf may be held responsible for the use which may be made of the information contained therein.

Nine partners from five EU countries bundle their resources to bring EICAA to success.