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Abstract

Entrepreneurship education has grown considerably, including in secondary schools (SS). However, agreement regarding the goals, objectives, and performance levels of entrepreneurship education (EE) in SS has yet to be reached. Thus, there is a need for greater clarity on what knowledge and skills should be taught to learners. The main objective of this study is to establish generally accepted attainment levels in EE for SS at two levels of secondary education (SE) in terms of knowledge, skills, and attitudes (KSA). We utilized the Delphi method and conducted Qualitative Comparative Analysis (QCA) to uncover patterns and connections between different variables, referred to as conditions. Our findings suggest that the current frameworks for EE in SS need to be revised to address the diverse needs of EE teachers and improve effectiveness and consistency. By comparing our findings with existing EE frameworks, we highlighted overlaps and gaps and contributed to the ongoing dialogue surrounding the refinement and evolution of EE practices.

Keywords

entrepreneurship education Delphi study attainment levels secondary education QCA

Introduction

The availability of entrepreneurship education (EE) at different levels of education has increased significantly including secondary schools (SS) (Fayolle et al., 2016; Hadley, 2023; Sánchez, 2013). Nevertheless, agreement on the goals, objectives, and levels of achievement for EE still lacks in SS. This void has resulted in a lack of transparency and consistency in the curriculum, and an inability to assess the effectiveness of EE (Göksen-Olgun et al., 2022). While there are different views regarding the definition and measurement of effectiveness (see, e.g., Reynolds, 2014 for an overview of the literature), we adhere to literature that operationalizes attainment levels by measurable outcomes of input-process-output approaches (see, e.g., Thomas, 2001). Attainment levels are significant determinants of outcome (Thomas & Mortimore, 1996), but, there is a need to increase clarity regarding what knowledge and skills should be taught to learners to maximize their attainment in entrepreneurship courses.

Assessing and measuring the effectiveness of EE is difficult because learning outcomes in knowledge, skills, and acquired attitudes are not uniformly measurable (Hadley, 2023), leading to difficulties in assessing learning gains of EE. This has broader implications as entrepreneurship is crucial in promoting innovation and developing entrepreneurs and start-ups (Lackéus, 2015; Ruskovaara & Pihkala, 2015). Therefore, achieving agreement and clarity regarding EE’s achievement goals, objectives, and attainment levels in secondary education (SE) is crucial. An agreement is indispensable for effective, uniform, and equitable EE for all learners.

We use a Delphi technique to identify acceptable knowledge, skills, and attitudes (KSA) for secondary school learners’ EE. Our approach to setting these levels is unique. Although secondary teachers’ experience and expertise are used to develop SE curricula and set criteria for learning outcomes, at least in the Netherlands, teacher involvement in such processes often remains limited thereby restricting the diversity of perspectives. Since SE teachers differ in their learning approaches, they are well-suited to decide what should be taught in entrepreneurship courses based on their—often considerable—practical experience, understanding of learners’, teaching skills, flexibility, and aptitude to adapt instruction to learners’ needs (Joensuu-Salo et al., 2021). To establish acceptable achievement levels and encourage a broader range of perspectives, we recruited SE teachers with experience in designing and teaching EE in the Netherlands.

We modified the standard Delphi method by recruiting a larger-than-suggested group of experts. This allowed us to include a large number of EE teachers—particularly secondary school teachers—instead of only relying on the input of scholars and opinion leaders (Kakouris & Liargovas, 2021).

The survey was conducted in three phases. First, we asked participants a series of open-ended questions. Second, we asked participants to rank items using a Likert scale. In the third and final phase we reached an agreement regarding the desired levels of KSA for entrepreneurship.

There are three learning pathways for SE in the Netherlands: VMBO (four-year vocational education), HAVO (five-year general SE), and VWO (six-year preparatory scientific education). Here, we focus on ninth to twelfth grade learners, where entrepreneurship is often related to economics and business economics (Göksen-Olgun et al., 2022). To ensure a balanced and diverse perspective at both levels, we invited secondary school teachers from both levels and teachers with expertise in secondary vocational and higher education for this study.

This paper is structured as follows. First, it reviews the current literature and discusses existing frameworks based on entrepreneurship KSA used for deriving educational attainment levels. Then, it explains the research methods used, including the Delphi and Qualitative Comparative Analysis (QCA). The results section describes the derived attainment levels based on the collected data. In the subsequent discussion section, we use EE frameworks to classify and categorize the attributes based on existing entrepreneurship literature. The results section explains the attainment levels obtained from our collected data based on the knowledge, skills, and abilities (KSA). In the following discussion section, we use EE frameworks to classify and categorize the attributes based on the existing literature on entrepreneurship.

Literature Review

Entrepreneurial Knowledge, Skills, and Attitudes (KSA)

The impact of EE and training programs has been studied using different techniques to develop courses and measure their impact. Some studies focus on entrepreneurship skills (Marques & Albuquerque, 2012; Oosterbeek et al., 2010) while others focus on motives and traits (Gürol & Atsan, 2006; Vodă & Florea, 2019) or venture creation (Lackéus, 2015; Moberg, 2014). In this study, we use a broad definition of EE, which focuses on developing entrepreneurial knowledge, skills, and attitudes and, thus, developing entrepreneurial competencies (Moberg, 2014; Sánchez, 2013).

Entrepreneurial competencies include the KSAs, values, and behaviors required for successful task performance (Moberg, 2014; Morris et al., 2013). These competencies are holistic, transferable, widely applicable, and emphasized by scholars and educators (Sánchez, 2013; van Gelderen, 2020). They include critical thinking, initiative, collaboration, risk planning, uncertainty management, financial management, motivating others, and marketing (Eggers, 1995; European Commission, 2013; Fisher et al., 2008; Garavan & O′Cinneide, 1994). The right mix of EE knowledge, skills, and abilities (KSA) is crucial for entrepreneurship training.

Entrepreneurship knowledge is crucial to develop entrepreneurial human capital (Núñez-Canal et al., 2023). It includes understanding the economic context, management, and business creation, writing a business plan, identifying opportunities, having financial and economic knowledge, and knowing about marketing (Lackéus, 2014; Lans et al., 2014). This knowledge is often taught through a didactic model, where the teacher assumes the role of an expert and teaches the fundamental aspects of starting a business, often through instruction (Kakouris & Liargovas, 2021).

Entrepreneurial skills are categorized into cognitive and non-cognitive (Moberg, 2014). Cognitive skills include problem-solving, critical thinking, and financial and economic literacy, while non-cognitive skills include cooperation, learning by doing, and perseverance (Kakouris & Liargovas, 2021). Literature suggests that the best way to teach entrepreneurial skills and an entrepreneurial mindset is through “teaching for entrepreneurship,” which equips learners with necessary cognitive and non-cognitive skills and involves a shift in the teacher’s role to that of a coach (Kakouris & Liargovas, 2021; Lackéus, 2015).

Attitudes toward entrepreneurship can be categorized as affective, conative, and cognitive (Burnette et al., 2020; Kakouris & Liargovas, 2021). Affective attitudes relate to emotional reactions, conative attitudes pertain to the willingness to engage, and cognitive attitudes refer to beliefs about entrepreneurship. Attitudes are mainly developed through “education through entrepreneurship,” where teachers coach to transfer knowledge and guide learning (Kakouris & Liargovas, 2021; Lackéus, 2015).

Frameworks Based on Entrepreneurship Competencies

Determining the necessary skills for entrepreneurship can be challenging because the specific skills needed differ based on each person’s particular situation and personality. Several frameworks and lists have been developed to outline entrepreneurial competencies to aid in this process (Bacigalupo et al., 2016; Kraiger et al., 1993; Lackéus, 2015; Man et al., 2002; Mitchelmore & Rowley, 2010; Shane & Venkataraman, 2000). However, there is considerable overlap and divergence among them. Basing a course on a clear and comprehensive framework is critical to provide effective EE. Appendix 1 provides a comprehensive overview of the most commonly used frameworks, detailing their specific domains and objectives. The selected frameworks are primarily aimed at higher education learners, helping them develop competencies encompassing KSA across various aspects of EE.

The Entrepreneurial Competence Framework is a well-known classification of individual competencies developed by Mitchelmore and Rowley (2010). It categorizes competencies into entrepreneurial competencies, business and management competencies, Human Resource Management (HRM), and conceptual and relational competencies. Lackéus (2014) also provides a popular classification framework, the Entrepreneurial competences. It includes KSA, highlighting deeper dimensions of knowledge—such as declarative and procedural entrepreneurial knowledge and self-knowledge as an entrepreneur. The skills and attitudes assessed by the framework, business and broader entrepreneurial skills and attitudes are used to highlight proactivity, perseverance, and tolerance for uncertainty and ambiguity as essential components of entrepreneurship.

The Competence Framework for Sustainable Entrepreneurship by Lans et al. (2014) is among the few that explicitly integrates sustainability into entrepreneurship. The framework combines two distinct areas, entrepreneurship and sustainability, using seven key competencies for sustainable development in a business environment outlined by Dentoni et al. (2012). These competencies are systems thinking, diversity and interdisciplinarity, foresighted thinking, normative, embracing diversity and interdisciplinarity, interpersonal, action, and strategic management. Lans et al. (2014) incorporated and operationalized these critical competencies for sustainable development with the five generic entrepreneurship competencies based on the work of Man et al. (2002) and Mitchelmore and Rowley (2010). Lans et al. (2014) identified five competency areas sharing similarities between entrepreneurship and sustainability, namely: (1) the centrality of (more or less complex) problems, (2) the importance of novelty and creativity, (3) the importance of self-involvement, (4) the conjunction of exploration and exploitation, and (5) the importance of commitment to significant others.

Another framework emphasizing ethical and sustainable thinking is the EntreComp framework (Bacigalupo et al., 2016). It is widely used and known for its flexibility and comprehensiveness. It distinguishes three competency areas, with 5 competencies per area and 442 learning outcomes. The first area encompasses opportunities and ideas, including ethical and sustainable thinking, opportunity recognition, and creativity. The second area covers resources, including the importance of self-insight, self-efficacy, and financial and economic understanding. The third area includes taking initiative and describes uncertainty and collaborating. With this detailed categorization, the EntreComp framework provides an in-depth understanding of the various competencies critical to entrepreneurship.

The Classification Framework of Entrepreneurial Competences (CFEC) systematically categorizes entrepreneurial competencies into domain competence, personal competence, and social/relational competence. The framework was developed in 2020 by Tittel & Terzidis based on a comprehensive literature review of entrepreneurial competencies and previous research by Mitchelmore and Rowley (2010). It can be used to evaluate results methodically. The competence domain includes an individual’s KSA that enable them to perform tasks autonomously and professionally, including three subcategories of entrepreneurship characteristics: opportunity recognition, organizational and strategic, and managerial competence. Personal competence refers to an individual’s ability to develop and shape their life responsibly and independently within their specific social, cultural, or occupational context. Social competence refers to an individual’s ability to cooperate with others, understand their interests and social situations, communicate effectively, and maintain positive relationships. Overall, the CFEC framework provides a comprehensive understanding of entrepreneurial competencies.

In the discussion section, these frameworks are utilized to classify and categorize the outcomes of the Delphi study and to identify the entrepreneurial KSA incorporated or absent in the responses. Moreover, we determine the areas where the existing frameworks fall short of the participants’ expectations.

Methods

The Delphi method is a widely used and formalized method to collect ideas and gain expert agreement (Hardie et al., 2023; Morris et al., 2013). It allows for multiple opinions from experts to be collected without the need for face-to-face interactions (Wilson et al., 2003). The Delphi method has been frequently used in educational and EE research (Green, 2014). For example, the method was applied by Morris et al. (2013) to investigate the relevance of entrepreneurial competencies, and by Neck and Corbett (2018) to improve the teaching and learning of for EE. We applied the Delphi method to establish educational attainment levels for EE aimed at learners’ from ninth to twelfth grade in SS. Inspired by the methodological approach of Stewart and Shamdasani (1980), the process involved three rounds to reach iterative agreements.

In the first round, we gathered insights from participants regarding the essential KSAs required for EE. During the second round, participants refined their responses and provided further clarity using Likert scales. In the final round, agreement was aimed for on the levels of achievement for EE by using ranking scales. The University of Maastricht, the Netherlands’s Ethical Review Board approved the entire study under protocol number ERCIC_353_03_05_2022.

Expert Panels and the Data Collection Process

The EE experts were recruited from the professional network, VECON (Association of Teachers of Economic and Social Sciences). They include experienced teachers teaching EE at pre-vocational SE, senior general SE, and pre-university education level. The teachers were primarily approached by e-mail. Over 100 teachers were approached for each round, resulting in 38 participants in the first round of the Delphi, 62 participants in the second round, and 32 participants in the final round. Each round lasted 2–4 weeks, leaving 6–8 weeks between rounds to analyze and present the findings to experts until an agreement on the attainment levels was reached in Round 3. Characteristics of the participants are presented in Appendix 2.

We structured each round of the Delphi-based survey into a data matrix encompassing three overarching domains: knowledge, skills, and attitudes. Within each domain, we further delineated subcategories, which proved challenging due to considerable overlap among the KSA. Nonetheless, we ensured that participants were asked about each concept separately to underscore the significance of skills and attitudes in EE and knowledge. The knowledge domain comprised six subcategories: business plan, finance, law, marketing, personnel and organization, and practical knowledge. Following the third round, only business plan, finance, marketing, and practical knowledge were considered relevant. The skills domain encompassed cognitive and non-cognitive skills, while the attitudes domain included affective, conative, and cognitive aspects. The Delphi rounds are detailed in Appendix 3.

The Delphi Survey Method: Round 1

In the first round, we asked respondents open-ended questions about KSAs related to entrepreneurial competencies. These competencies are a set of KSAs, values, and behaviors essential for the successful performance of a specific activity or task (Moberg, 2014; Morris et al., 2013) and crucial for training young people in EE. To achieve this, we used an online questionnaire distributed using Qualtrics based on open-ended questions. We only considered fully completed questionnaires (<100% of the questions answered), thus removings any incomplete responses. After cleaning the data, we analyzed the closed-ended responses using SPSS to gain insights into participants’ backgrounds and experiences. The open-ended responses were coded and organized in MAXQDA and then analyzed using QCA, which is a hybrid research method (combining qualitative and quantitative elements) that systematically compares cases and derives solutions to understand complex, real-world situations. QCA can identify patterns and relationships among different combinations of variables, known as conditions. These were the building blocks we used to understand which combinations of categories and subcategories lead to the best provision of entrepreneurship in SE (Cragun et al., 2016; Ragin, 1987).

Several different techniques can be used during QCA. The first technique we used is crisp-set QCA (csQCA) and involves dichotomized conditions and outcomes (Cragun et al., 2016; Ragin, 1987). In Round 1, we used csQCA to score cases on the presence and absence of the total provided essential KSA. We created a list of participant responses categorized into KSA. We then calibrated each answer in Excel with a score of 1 if it matched the generated list and 0 if it did not (Ragin, 2008). After calibration, we used the fsQCA 2.0 program to generate truth tables (available upon request). A truth table is a data matrix of all conditions used in the analysis (Fiss, 2011). By integrating all conditions specified for KSA, the fsQCA program provided an overview, expressed in terms of solutions, of how the different combinations of conditions for each category (KSA) relate to each other. We used the same consistency thresholds in each round, which specify the minimum acceptable level at which a combination of conditions reliably relates to outcomes (Muñoz & Dimov, 2015; Ragin et al., 2006). We set our consistency thresholds at 0.84, 0.95, and 1.0 (where possible), consistent with previous studies (e.g., Muñoz & Dimov, 2015; Ragin, 2000; Schneider & Wagemann, 2010). Based on these consistency thresholds, a Boolean algorithm was applied during csQCA to generate the truth tables. The fsQCA 2.0 program determines three solutions based on the truth tables. These were the complex, the parsimonious, and the intermediate solutions. If a condition is present, it is directly linked to the outcomes included in the complex solution. If multiple conditions lead to one outcome, then this complex outcome can be difficult to understand, so with input from the researchers, the software program generates a parsimonious and intermediate solution (Ragin et al., 2006).

Focusing on the complex and intermediate solutions from a theoretical and practical point of view because, in this case, the solutions are identical. Thus, as explained by Ragin (1987), they strike a balance between sparsity and complexity. Based on the truth tables, we created solution tables for each category (KSA), visualizing the results using circles and crosses, as in previous studies (Fiss, 2009; Ragin, 2008).

The Delphi Survey Method: Round 2

We assessed the relevance of the crucial content in Round 1 by the experts regarding KSA towards secondary EE. We asked the participants to rate items using a 5-point Likert scale. We cleaned the data in SPSS by removing all questionnaires that were less than 100% complete. The survey in this round only used closed questions. We used SPSS to analyze the backgrounds and experiences of the participants. Because we used Likert scales with more than two answer possibilities, we used the second QCA technique, namely fuzzy-set QCA (fsQCA), in the fsQCA 2.0 program (Ragin, 2000). We calibrated the responses in Excel and assigned a value of 0.8 for “very important,” 0.6 for “important,” 0.4 for “neutral,” 0.2 for “unimportant,” and 0.0 for “very unimportant.” We then integrated this data into Ragin’s (2008) fsQCA 2.0 program and generated truth tables. We created solution tables for each category (KSA) based on the truth tables (available on request from the author). We visualized the results using circles and crosses, as in Round 1.

The Delphi Survey Method: Round 3

The final round determined the essential content specifically related to entrepreneurship KSA. Participants ranked the essential content based on perceived importance, ranging from “very important” to “very unimportant.” The responses were calibrated in Excel and then analyzed using QCA with fuzzy sets in the fsQCA 2.0 program (Ragin et al., 2006). The responses to the questions in Round 2 were used. Participants also indicated the desired time allocation for each essential KSA content as a percentage of total EE time. These answers were calibrated in Excel by assigning the corresponding percentage to the decimal value, e.g., 0.8 was expressed as 80%. Truth tables were created for rankings and time allocations using the fsQCA 2.0 program (Ragin, 2008) (available on request). We created solution tables for each category (KSA) based on the truth tables. As in the previous two rounds, we visualized the results using circles and crosses.

Results

We use solution tables (Tables 3 –5) to identify the various aspects of KSA required for entrepreneurship in SE. The tables display the coverage and consistency of each solution. Coverage refers to how well the combinations of conditions explain the observed results. The higher the coverage, the better the explanation. Consistency refers to the extent to which the combinations of conditions consistently lead to the result. The higher the consistency, the stronger the connection.

Analysis of the Knowledge Category

We identified four subcategories of knowledge and selected one two-level solution for each solution. Based on the truth tables, Table 1–4 illustrate the relevant solution for the knowledge category in Rounds 1–3.

Table 1.

Delphi Rounds 1–3 for Knowledge: Business Plan.

Rounds	Round 1		Round 2		Round 3
Educational Level	Lower Level	Higer Level	Lower Level	Higher Level	Lower Level	Lower Level Time	Higher Level	Higher Level Time
Knowledge: Business plan
Idea complex	⊗	●	●	●	⊗	⊗	●	●
Idea innovation	⊗	-	●	-	●	⊗	●	⊗
Purchasing	-	⊗	-	●	●	●	-	⊗
Sale	●	●	●	●	●	●	⊗	⊗
Multiple value creation	⊗	●	●	●	●	⊗	●	-
Consistency	1.0	1.0	1.0	0.9882	0.9943	0.9137	0.9773	0.977839
Raw Coverage	0.61538	0,111	0.7547	0.6482	0.7087	0.4532	0.76377	0.701789

Note. Black circles indicate the presence of the condition, and circles with “X” indicate their absence. Blank spaces indicate irrelevant condition (Fiss, 2009; Ragin, 2008).

Table 2.

Delphi Rounds 1–3 for Knowledge: Financial & Economic Literacy.

Rounds	Round 1		Round 2		Round 3
Educational level	Lower Level	Higer Level	Lower Level	Higher Level	Lower Level	Lower Level Time	Higher Level	Higher Level Time
Knowledge: Financial & economic literacy
Business forms	⊗	⊗	●	⊗	-	●	-	⊗
Accounting	●	●	⊗	●	⊗	-	⊗	⊗
Consistency	1.0	1.0	0.9148	0.9768	0.60	0.8150	0.625	0.202665
Raw Coverage	0.11111	0.111	0.9717	0.6762	0.9973	0.9657	0.94755	1.0

Note. Black circles indicate the presence of the condition, and circles with “X” indicate their absence. Blank spaces indicate irrelevant condition (Fiss, 2009; Ragin, 2008).

Table 3.

Delphi Rounds 1–3 for Knowledge: Marketing.

Rounds	Round 1		Round 2		Round 3
Educational Level	Lower Level	Higer Level	Lower Level	Higher Level	Lower Level	Lower Level Time	Higher Level	Higher Level Time
Knowledge: Marketing
Market research	⊗	●	●	●	●	-	●	⊗
Marketing models	●	●	⊗	●	●	●	●	⊗
Marketing policy	⊗	●	⊗	-	●	●	●	⊗
Marketing plan	●	●	●	●	●	●	-	●
Consistency	1.0	1.0	0.9547	0.9918	1.0	0.9907	1.0	0.855073
Raw Coverage	0.25	0.090	0.8832	0.8864	0.6699	0.7946	0.79189	0.889447

Note. Black circles indicate the presence of the condition, and circles with “X” indicate their absence. Large circles indicate core conditions; small circles indicate additional prerequisites. Blank spaces indicate irrelevant condition (Fiss, 2009; Ragin, 2008).

Table 4.

Delphi Rounds 1–3 for Knowledge: Practical Knowledge.

Rounds	Round 1		Round 2		Round 3
Educational Level	Lower Level	Higer Level	Lower Level	Higher Level	Lower Level	Lower Level Time	Higher Level	Higher Level Time
Knowledge: Practical knowledge
Chamber of Commerce	●	●	●	●	⊗	⊗	●	⊗
Knowledge of insurance	⊗	●	●	●	-	⊗	●	●
Inform tax authorities	●	●	●	●	●	⊗	●	⊗
Consistency	1.0	1.0	0.9208	0.9976	0.7969	0.0911	1.0	0.815385
Raw Coverage	0.16666	0.2	0.9690	0.8545	0.8494	1.0	0.68725	0.779406

In Round 1, the lower level includes sales as the only condition for knowledge in business plans. In contrast, in Round 2, the conditions included are complexity, innovation, procurement, sales, and multiple value creation. In Round 3, the conditions include innovation, procurement, sales, and multiple value creation. At the higher level, Round 1 includes complexity, sales, and multiple value creation; Round 2 includes complexity, procurement, sales, and multiple value creation, while in Round 3, the conditions for knowledge in business plans are complexity, innovation, and multiple value creation.

Both levels acknowledge the importance of creating value and promoting innovation. However, when we look at the time allocation question in round 3, we see that participants want to spend less time on these activities. This observation is intriguing because it suggests a potential disconnect between perception and action in prioritizing these crucial aspects of EE. At the lower level, knowledge about a business plan consists of innovation, procurement, sales, and multiple value creation. In contrast, at the higher level, it includes complexity, innovation, and multiple value creation. This difference can be attributed to different levels of education among learners. We can infer that learners with higher levels of education, are also more challenged at the knowledge level in EE.

The second category of knowledge is economic and financial literacy. In Round 1, the lower level only includes accounting as a knowledge condition. However, in Round 2, the economic and financial literacy condition is expanded to include different business forms. In Round 3, there is no specific economic and financial literacy condition. However, the time allocation question suggests that financial and economic literacy knowledge for different business forms is still important.

At the higher level, Round 1 includes only the financial and economic literacy for different business forms; Round 2 includes only accounting, while in Round 3, there is no specific condition for knowledge in economic and financial literacy, also not when we look at the time allocation question.

Notably, both the lower and higher education institutions acknowledge the significance of financial and economic literacy. However, they do not have any specific economic and financial literacy conditions, maybe because this aspect is already incorporated into the existing curricula of business and economics programs in SE.

The third category of knowledge is marketing. In Round 1, knowledge of marketing models and a marketing plan are conditions at the lower level. In Round 2, market research and a marketing plan were conditions, whereas in Round 3, all conditions were present. Looking at the time commitment question in round 3, we see no changes in the conditions except for market research.

All conditions were present at the higher level in Round 1. In Round 2, market research, knowledge of marketing models, and a marketing plan were conditions. In contrast, in Round 3, market research and knowledge of marketing policies and models were present. However, when looking at the time allocation question in round 3, we see that participants want to spend less time on these activities and more time on a marketing plan; maybe the time for forming a marketing plan is specified because a marketing plan is one of the attainment levels for the business economics course at the higher level.

The last category concerns practical knowledge about entrepreneurship. In Round 1, we found that registering with the Chamber of Commerce and informing tax authorities were present at the lower-level. In Round 2, entrepreneurship insurance was also considered a condition. In Round 3, informing tax authorities was the only identified condition. However, when we analyzed the responses to the time allocation question in Round 3, we found no specific condition for knowledge in practical entrepreneurship for the lower-level participants. This finding is interesting because the lower level focuses more on practical experience than the higher level. The low consistency grade, which is associated with the time commitment of Round 3, may explain this result.

For the higher-level participants, registration with the Chamber of Commerce, knowledge of entrepreneurship insurance, and informing tax authorities were conditions in all rounds. However, when we looked at the time allocation question in Round 3, we found that only knowledge of insurance was considered a condition for practical entrepreneurship knowledge, probably because it is one of the attainment levels for the business economics course at the higher level.

Analysis of the Skills category

Tables 5 and 6 present the relevant solution for the category of skills, based on the truth tables, for Rounds 1–3. We identified two subcategories of skills and selected one solution at two different levels for each subcategory.

Table 5.

Delphi Rounds 1–3 for Skills: Cognitive.

Rounds	Round 1		Round 2		Round 3
Educational Level	Lower Level	Higer Level	Lower Level	Higher Level	Lower Level	Lower Level Time	Higher Level	Higher Level Time
Skills: Cognitive
Validate ideas	⊗	⊗	-	-	⊗	⊗	●	⊗
Problem solving	⊗	●	●	●	●	●	●	●
Critical thinking	-	●	●	●	●	●	●	●
Research skills	⊗	⊗	●	●	-	⊗	⊗	⊗
Financial and economic literacy	●	⊗	●	●	●	●	●	⊗
Information skills	●	⊗	●	●	●	●	●	●
Planning and managing	⊗	⊗	●	●	●	⊗	●	●
Consistency	1.0	0.38	0.9875	0.990845	0.997826	0.996226	0.980843	0.937799
Raw Coverage	0.0888	0.1183	0.8663	0.840502	0.548387	0.377143	0.365193	0.712727

Note. Black circles indicate the presence of the condition, and circles with “X” indicate their absence. Blank spaces indicate irrelevant condition (Fiss, 2009; Ragin, 2008).

Table 6.

Delphi Rounds 1–3 for Skills: Non-Cognitive.

Rounds	Round 1		Round 2		Round 3
Educational Level	Lower Level	Higer Level	Lower Level	Higher Level	Lower Level	Lower Level Time	Higher Level	Higher Level Time
Skills: Non-cognitive
Opportunities	⊗	●	●	●	●	●	●	●
Driven	-	-	●	●	⊗	⊗	●	⊗
Persevere	-	-	-	-	⊗	⊗	●	●
Communication	●	⊗	●	●	●	⊗	⊗	⊗
Resources	-	⊗	●	●	●	⊗	⊗	⊗
Self-awareness and self-reliance	⊗	●	●	●	⊗	●	-	●
Inspire, engage and enthuse others	-	⊗	-	-	⊗	⊗	⊗	●
Learning by doing	●	⊗	●	-	●	●	⊗	⊗
Collaborate	⊗	⊗	●	●	●	⊗	⊗	⊗
Taking initiative	-	●	●	●	●	●	●	●
Dealing with uncertainty and risk	⊗	●	-	-	⊗	⊗	⊗	⊗
Consistency	0.36	0.38	0.9926	0.988961	0.961207	0.956693	0.942857	0.981735
Raw Coverage	0.1894	0.1013	0.8569	0.863378	0.322719	0.363776	0.424893	0.746528

Note. Black circles indicate the presence of the condition, and circles with “X” indicate their absence. Blank spaces indicate irrelevant condition (Fiss, 2009; Ragin, 2008).

At the lower educational level, during Round 1, cognitive skills included financial, economic, and information skills. In Round 2, all cognitive skills were included except for validating ideas. In Round 3, all cognitive skills except validating ideas and research skills were mentioned. When analyzing the responses to the time allocation question in Round 3, we found that only planning and managing were not considered.

At the higher educational level, during Round 1, cognitive skills such as problem-solving and critical thinking were mentioned. In Round 2, all cognitive skills were present except for validating ideas. However, in Round 3, all cognitive conditions were mentioned except for research skills. Upon analyzing the responses to the time allocation question in Round 3, we discovered that problem-solving, critical thinking, information skills, planning, and managing were present. Notably, validating ideas and financial-economic skills were absent. The latter may be related to the fact that it is already one of the learning outcomes for the upper-level business economics subject.

The second subcategory of skills includes non-cognitive skills. In the first round, non-cognitive skills were identified as communication and learning through practical experience. In the second round, non-cognitive skills include skills focused on opportunities, driving, communication, resources, self-awareness, self-reliance, learning by doing, collaboration, and taking the initiative. In the third round, non-cognitive skills at the lower level include skills focused on opportunities, communication, resources, learning-by-doing, collaboration, and taking the initiative. When analyzing the responses to the time allocation question in Round 3, we found that opportunities, self-awareness, self-reliance, learning by doing, and taking the initiative were considered.

At the higher level, seeing opportunities, self-awareness, self-reliance, taking the initiative, and dealing with uncertainty and risk were included. In the second round, non-cognitive skills such as opportunities, driven communication, resources, self-awareness, self-reliance, collaboration, and taking the initiative are considered. In the third round, non-cognitive skills such as opportunities, drive, perseverance, and initiative are considered at the higher level. When analyzing the responses to the time allocation question in the third round, we found that opportunities, perseverance, self-awareness and self-reliance, inspiring, engaging, and enthusing others, and taking the initiative were included.

Analysis of the Attitudes Category

Table 7–9 present the relevant solution for the attitude category, based on the truth tables developed in each round of the Delphi-based study. We identified three subcategories of attitudes and developed a two-level solution for each subcategory.

Table 7.

Delphi Rounds 1–3 for Attitude: Affective.

Rounds	Round 1		Round 2		Round 3
Educational Level	Lower Level	Higer Level	Lower Level	Higher Level	Lower Level	Lower Level Time	Higher Level	Higher Level Time
Attitude: affective
Opportunities	⊗	⊗	●	●	-	●	-	●
Social	⊗	⊗	-	●	●	●	●	●
Creative	●	⊗	●	●	●	●	●	●
Flexible	-	-	●	-	●	●	-	●
Communicative	-	-	●	●	●	●	●	●
Well-intentioned	⊗	●	●	●	⊗	●	⊗	●
Courageous	-	-	-	●	⊗	-	⊗	⊗
Consistency	0.1186	0.248	0.8693	0.8429	0.588548	0.685786	0.6415	0.702128
Raw Coverage	1.0	0.33	0.9904	0.9986	0.98441	1.0	0.9185	0.994975

Note. Black circles indicate the presence of the condition, and circles with “X” indicate their absence. Blank spaces indicate irrelevant condition (Fiss, 2009; Ragin, 2008).

Table 8.

Delphi Rounds 1–3 for Attitude: Conative.

Rounds	Round 1		Round 2		Round 3
Educational Level	Lower Level	Higer Level	Lower Level	Higher Level	Lower Level	Lower Level Time	Higher Level	Higher Level Time
Attitude: conative
Go for it	⊗	●	-	●	●	●	⊗	⊗
Persistent	●	●	●	●	-	●	●	●
Proactive	●	⊗	●	●	●	●	●	●
Disciplines	-	-	●	●	⊗	●	●	●
Dealing with failings	⊗	●	●	●	⊗	●	⊗	⊗
Take risks	⊗	⊗	-	⊗	⊗	●	⊗	⊗
Keep appointments	-	-	●	●	●	●	●	-
Consistency	0.377	0.121	0.9439	1.0	0.575339	0.679349	0.5408	0.53207
Raw Coverage	0.5	0.63	0.9530	0.4878	0.923077	1.0	0.9611	0.953003

Note. Black circles indicate the presence of the condition, and circles with “X” indicate their absence. Blank spaces indicate irrelevant condition (Fiss, 2009; Ragin, 2008).

Table 9.

Delphi Rounds 1–3 for Attitude: Cognitive.

Rounds	Round 1		Round 2		Round 3
Educational Level	Lower Level	Higer Level	Lower Level	Higher Level	Lower Level	Lower Level Time	Higher Level	Higher Level Time
Attitude: cognitive
Realism	●	●	-	●	●	●	●	●
Leadership vision	-	-	●	●	●	●	●	●
Consistency	0.1111	0.454	0.9825	0.9931	0.630952	0.780555	0.6071	0.789855
Raw Coverage	0.2	0.5	0.8208	0.6051	1.0	1.0	1.0	1.0

Note. Black circles indicate the presence of the condition, and circles with “X” indicate their absence. Blank spaces indicate irrelevant condition (Fiss, 2009; Ragin, 2008).

The first subcategory of attitudes includes affective attitudes. In the first round of analysis, the affective attitude condition at the lower level is creativity. In the second round, the affective attitudes are expanded to include opportunity, creativity, flexibility, communication, and benevolence as present conditions. In the third round, the affective attitudes include social attitudes, creativity, flexibility, and communicative attitudes as present conditions. When examining the responses to the time allocation question in the third round at the lower level, we found that almost all affective attitude conditions were present except courageous.

At the higher level, the affective attitude conditions in round one were social, creative, and communicative. In round two, the affective attitudes were opportunity, creativity, communication, social attitudes, benevolence, and courage. In the third round, the affective attitudes were social, creative, and communicative. When analyzing the responses to the time allocation question in the third round at the higher level, we found that almost all affective attitude conditions were present except courageous.

The second subcategory of attitudes includes conative attitudes. In the first round, the conative attitudes related to persistence and proactivity are considered at the lower level. In the second round, the conative attitudes at the lower level include persistence, proactivity, discipline, handling failures, and keeping appointments. In the third round, the conative attitudes at the lower level are related to persistence, proactivity, and keeping appointments. When analyzing the responses to the time allocation question in the third round at the lower level, we found that all conative attitude conditions were present.

At the higher level, the conative attitudes are related to taking all available opportunities (go for it), persistence, and handling failures in the first round. In the second round, the conative attitudes at the higher level include available opportunities, persistence, proactivity, discipline, handling failures, and keeping appointments. In the third round, the conative attitudes at the higher level focus on persistence, proactivity, discipline, and keeping appointments. When analyzing the responses to the time allocation question in the third round at the higher level, we found that only persistence, proactiveness, and discipline conative attitude conditions were present.

The third and final subcategory of attitudes includes cognitive attitudes. In the first round of analysis, we identified “realism” as the cognitive attitude condition at the lower level. In the second round, leadership vision was identified as the cognitive attitude condition, while in the third round, both realism and leadership vision were mentioned. When we analyzed the responses to the time allocation question in the third round at the lower level, we observed that all cognitive attitude conditions were present. Similarly, at the higher level, we found that the cognitive attitude condition in round 1 was also realism, while in rounds 2 and three, all cognitive attitude conditions were included. Furthermore, we found that all cognitive attitude conditions were present again when analyzing the responses to the time allocation question in the third round at the higher level.

Discussion

In this section, we compare our findings with the established literature on knowledge, skills, and attitudes relative to existing frameworks in EE.

Knowledge in Existing EE Frameworks

The findings show that the knowledge component within the EE domain includes business plans, financial-economic insights, marketing strategies, and practical knowledge. However, there are differences in knowledge acquisition between different levels of education. At lower levels of education, EE focuses mainly on buying and selling goods and services, which is a narrow definition of entrepreneurship. On the other hand, at higher levels of education, the emphasis is on solving complex problems in EE, which aligns with the broader definition of EE and contributes to “learning by creating value” (Lackéus, 2015). The difference in focus between the two levels of education may be due to how entrepreneurship is taught at each level. Lower levels of education prepare learners’ for secondary vocational education, while higher levels provide entry to higher vocational education or university. This difference affects what should be taught, how it should be taught, and what pedagogy learners are accustomed to in other subjects. Further research is needed to explore the differences in teaching methodology between the two levels of education, as this study only focused on the “what” question.

Both levels recognize the importance of value creation in EE. However, surprisingly, the time allocated to this aspect in EE provision is minimal. This observation is significant as value creation is considered a crucial aspect of entrepreneurship in recent literature on EE (Lin et al., 2023; Mawson et al., 2023). Despite the importance of values in EE, previous research indicates that most teachers overlook values when designing, implementing, and evaluating entrepreneurship programs (Göksen-Olgun et al., 2022; Kyrö, 2015).

Furthermore, the findings show that marketing, financial, economic, and practical knowledge are also important aspects of entrepreneurship educational offerings for both levels, with marketing being the main focus of time allocation. This finding may be related to the fact that entrepreneurship in the Dutch education system is often taught in combination with economics or business economics, with financial and economic knowledge aspects in particular already covered in the final attainment levels of those subjects.

Comparing our findings with existing frameworks, we find significant similarities, especially with the higher-level and existing frameworks in EE. For example, knowledge about business plans, complex problems, marketing, innovation, and multiple value creation can be found in existing frameworks as well. However, these frameworks are missing practical knowledge, purchasing, and sales. This solution can be attributed to the level of knowledge in SE, especially at the lower level, and the relatively young age of the target group, which is still a long distance from the labor market (Huber et al., 2014). However, other factors may also be at play, underscoring the need for additional research to uncover the underlying causes. The most striking differences and similarities of entrepreneurship knowledge combined with the existing frameworks are summarized in Table 10.

Table 10.

Knowledge in Existing EE Frameworks.

Knowledge	Description	L	H	1	2	3	4	5
Business plan	Business plan: Familiar with the knowledge necessary to compose a business plan.	✓	✓	✓	✓	✓	✓	✓
	Complexity: Understands that entrepreneurial issues range from relatively simple to complex problems and that determining the type of problem is helpful in finding an appropriate approach.	-	✓	✓	✓	✓	✓	✓
	Innovative: Familiar with the innovation life cycle approach and its relevance to economic innovation and technological development.	✓	✓	✓	✓	✓	✓	✓
	Purchasing: Understands the procurement process and its implications for generating economic value.	✓	-	-	-	-	-	-
	Sale: Understands the sales process and its implications for generating economic value.	✓	-	-	-	-	✓	-
	Multiple value creation: Familiar with the approach of multiple value creation and its relevance for sustainable value creation in economic, social, and ecological domains.	✓	✓	-	✓	✓	-	✓
Financial	Financial literacy: Knows financial concepts and understands the key values and underlying principles.	✓	✓	-	✓	✓	✓	✓
	Business forms: Has insight into various business structures and the related financial variations.	✓	-	-	✓	✓	✓	-
	Basic Accounting: Familiar with the basic principles and fundamental techniques of accounting.	-	-	-	✓	✓	✓	-
Marketing	Market research: Has insight into conducting market research and understands the key values and underlying principles.	✓	✓	✓	-	-	-	✓
	Marketing models: Possesses knowledge of marketing models and understands the key values and underlying principles.	✓	✓	✓	✓	-	-	-
	Marketing policy: Has knowledge of marketing activities and decision-making processes in marketing policy.	✓	✓	✓	✓	-	-	-
	Marketing plan: Possesses knowledge about designing a marketing plan and understands the associated principles.	✓	-	-	-	-	✓	-
	Practical Entrepreneurial Knowledge: Possesses practical knowledge related to entrepreneurship.	✓	✓	-	-	-	-	-
Practical	Chamber of Commerce: Has knowledge of registering a company with the Chamber of Commerce.	-	✓	-	-	-	-	-
	Insurance: Possesses knowledge about important insurances for entrepreneurs.	-	✓	-	-	-	-	-
	Tax authorities: Has knowledge of arranging tax matters with the tax authorities.	✓	✓	-	-	✓	-	-

Note. The columns L and H signify the Lower level (L) and the Higher level (H). The columns 1–5 relate to: (1) The entrepreneur competence framework (Mitchelmore & Rowley, 2010), (2) Entrepreneurial competencies (Lackéus, 2015), (3) EntreComp (Bacigalupo et al., 2016), (4) Classification Framework of Entrepreneurial Competences (CFEC) (Tittel & Terzidis, 2020), (5) Competence framework for sustainable entrepreneurship (Lans et al., 2014).

Skills in Existing EE Frameworks

According to our findings, the cognitive skills component in EE includes problem-solving, critical thinking, financial and economic literacy, information skills, and planning and managing. It is worth noting that the validation of ideas is only present as a condition in the higher SE level. On the other hand, the validation of ideas is not included in the time allocation of EE at the higher level. These finding is in contrast with the existing frameworks, which mainly consider the validation of ideas as essential (Bacigalupo et al., 2016; Lans et al., 2014; Mitchelmore & Rowley, 2010; Tittel & Terzidis, 2020).

The results of the non-cognitive skills assessment in Entrepreneurial Education indicate that both educational levels emphasize opportunities, self-awareness, self-reliance, and taking initiative. However, for the higher level, the non-cognitive skills of being driven, persevering, inspiring, engaging, and enthusing others are given more importance. Communication, resources, learning by doing, and collaboration are also emphasized for the lower level. One interesting finding is a difference in the skills emphasized between the two levels. It could be because the lower-level curriculum focuses more on hands-on activities, resulting in a more straightforward approach to entrepreneurship concepts. On the other hand, the high-level curriculum focuses on more complex problems and multiple value creation, emphasizing perseverance and motivation. Further research could help us better understand these differences.

When comparing our findings with existing frameworks, we find many similarities between our results. Cognitive skills such as problem-solving, critical thinking, and financial literacy are also found in current frameworks. Additionally, non-cognitive skills like communication, collaboration, and perseverance are similar. However, dealing with uncertainty and risk is not addressed in either level of education despite being important in EE (Hameed & Irfan, 2019). This group comprises SE learners who are relatively young and have not yet entered the labor market. These learners have little or no experience with entrepreneurship and, thus, have not yet dealt with its uncertainties and risks. The most notable differences and similarities in skills related to entrepreneurship are listed in Table 11.

Table 11.

Skills in Existing EE Frameworks.

Skill	Description	L	H	1	2	3	4	5
Cognitive	Validate ideas: Can assess the feasibility and value creation of ideas.	-	✓	✓	-	✓	✓	✓
	Problem solving: Can develop ideas that solve problems that are relevant to the environment.	✓	✓	-	-	✓	✓	✓
	Critical thinking: Can analyze, evaluate and interpret information in a thoughtful and systematic way.	✓	✓	✓	-	✓	-	✓
	Research skills: Can develop and apply effective research techniques (gathering, analyzing and interpreting information).	✓	✓	-	-	✓	-	✓
	Financial and economic literacy: Can apply financial and economic concepts in different contexts.	✓	✓	✓	-	✓	✓
	Information skills (searching, selecting, assessing): Mastering information skills, including effectively searching, selecting and assessing information.	✓	✓	-	-	✓	✓	✓
	Planning and managing: Can use organizational and leadership skills to plan and manage effectively.	✓	✓	✓	✓	✓	✓	✓
Non-cognitive	Opportunities: Can recognize and seize opportunities to create value for others.	✓	✓	✓	✓	✓	✓	✓
	Driven: Can demonstrate extra commitment to, stay focused and motivated to achieve entrepreneurship goals.	-	✓	✓	✓	✓	-	-
	Persevere: Can show determination and resilience, overcome obstacles and persevere through challenges to achieve desired results.	-	✓	✓	✓	✓	-	✓
	Communication: Can communicate clearly, purposefully and understandably with others.	✓	-	✓	✓	✓	✓	✓
	Resources: Can use available resources efficiently to achieve stated goals.	✓	-	✓	-	✓	✓	✓
	Self-awareness and self-reliance: Can create self-awareness (understanding personal strengths and weaknesses) and promote self-reliance.	✓	✓	-	✓	✓	-	✓
	Inspire, engage and enthuse others: Can persuade, engage and inspire others in value-creating activities.	-	✓	✓	-	✓	-	✓
	Learning-by-doing: Can engage in value creation initiatives and reflect on both successes and failures (self and others).	✓	-	-	-	✓	-	✓
	Collaborate: Can work effectively with others (peers/coach/companies).	✓	-	-	-	✓	✓	✓
	Taking initiative: Can take initiative to add or create value.	✓	✓	-	-	✓	-	✓
	Dealing with uncertainty and risk: Can weigh risks and make decisions despite uncertainty and risk.	-	-	-	✓	✓	✓	✓

Attitude: Affection in Existing EE Frameworks

There are no significant differences in affective attitudes between lower and higher levels of education. In particular, affective attitudes include social, creative, flexible (lower level), and communicative approaches and are equally important for both levels of education. Both groups agree that seeing opportunities, flexibility (higher level), and well-intentionedness are important and indicate a willingness to invest time in these. These affective attitudes, except for well-intentioned, are also well represented in existing frameworks.

The study results on the conative attitude component of the Entrepreneurial Education domain demonstrate that proactivity and keeping appointments are important for both educational levels. However, persistence is more emphasized for higher levels, while the lower levels focus on the desire to take action (go for it). We find no significant difference in the components of time allocation. All these findings are consistent with the existing frameworks. However, our study reveals that risk-taking and dealing with failure are also not emphasized in attitudes in these frameworks, although they are essential for successful entrepreneurship (Hameed & Irfan, 2019). Therefore, it is crucial to include risk-taking and dealing with failure in pedagogies for EE. Depending on the chosen pedagogy, these skills can be taught and developed at the secondary level.

In the cognitive attitude component of the EE domain, both realism and leadership vision are crucial at both levels in our results and the existing frameworks. Realism is important when learners work in contexts vastly different from their own, for example, when affluent learners work in areas with economic challenges (Neal, 2017). Pedagogy in EE plays a significant role in this regard. While this study primarily focuses on the “what” question in EE, the “how” question, which pertains to the pedagogy in EE, cannot be separated from it. Table 12 presents the most prominent differences and similarities in entrepreneurial attitudes.

Table 12.

Attitudes in Existing EE Frameworks.

Attitude	Description	L	H	1	2	3	4	5
Affective	Opportunities: Willing to accept and discuss entrepreneurship issues, problems and opportunities.	✓	✓	✓	-	✓	✓	✓
	Social: Demonstrates kindness, understanding and the ability to get along well with others.	✓	✓	✓	✓	✓	✓	✓
	Creative: Demonstrates an open and innovative attitude, focusing on the ability to generate original ideas, think flexibly and think outside the box.	✓	✓	-	✓	✓	✓	✓
	Flexible: Demonstrates willingness to adapt to different circumstances and deal effectively with unexpected situations.	✓	✓	-	-	✓	-	✓
	Communicative: Aware that conveying information in a clear and respectful manner is effective.	✓	✓	✓	✓	✓	✓	✓
	Well-intentioned: Shows kindness, willingness to help others and an overall positive attitude.	-	-	-	-	✓	-	-
	Courageous: Shows willingness and determination to face difficulties, dangers or challenges with self-confidence.	-	-	-	-	✓	-	✓
Conative	Go for it: Demonstrates a mental willingness and determination to fully engage in the pursuit of goals, overcome challenges and achieve success.	✓	-	-	✓	✓	-	✓
	Persistent: Demonstrates a willingness and determination to go fully for a goal, overcome obstacles and achieve success.	-	✓	-	-	✓	✓	✓
	Proactive: Demonstrates a proactive attitude by taking initiative, planning ahead and actively working on challenges.	✓	✓	-	✓	✓	-	✓
	Disciplined: Displays an organized attitude, working systematically and consistently to achieve goals.	-	✓	✓	-	✓	✓	-
	Dealing with failings: When faced with entrepreneurship challenges, tends to experiment and is not afraid that something will fail.	-	-	-	-	✓	-	-
	Take risks: Open to taking risks that can provide valuable learning opportunities.	-	-	-	-	✓	✓	✓
	Keep appointments: Shows commitment and respect for others' time by being consistent, punctual and reliable in appointments.	✓	✓	-	-	✓	✓	-
Cognitive	Realism: Has a realistic view of circumstances and the feasibility of goals.	✓	✓	✓	-	✓	-	✓
Cognitive	Leadership vision: Demonstrates an open and learning attitude toward developing leadership skills.	✓	✓	✓	-	✓	✓	-

Conclusion

Agreement and clarity about assessment levels in EE at SS are lacking (Fayolle et al., 2016; Göksen-Olgun et al., 2022; Hadley, 2023; Sánchez, 2013). By directly involving teachers in the Delphi process, we aimed to empower teachers to develop curricula (Kakouris & Liargovas, 2021) and bridge the gap between theoretical frameworks and practical implementation in the classroom, thus providing a more robust foundation for EE in SS (Joensuu-Salo et al., 2021). However, some limitations of our approach should be mentioned. In this study, we operationalized effectiveness by attainment levels and excluded other frames of effectiveness such as content and pedagogical best practices. In addition, we conducted three rounds with varying numbers of participants due to our open-ended approach. In the first round, we asked open-ended questions and found that teachers sometimes struggled to independently arrive at key attainment levels. For future research, it is advised that teachers need to get used to it and receive more guidance on open-ended questions. In the second round, we used a 5-point Likert scale. However, we found that participants considered many suggested items from Round 1 crucial, which resulted in too many variables for the QCA program and significant differences between the sub-conditions in the different rounds. To provide more guidance and choices to teachers, we chose ranking over Likert scales in Round 3. Additionally, we added a component on the time commitment to make teachers more aware of their teaching time versus what they want to include as attainment levels for EE. Another limitation pertains to the participants who are involved. Our respondents are teachers who had experience in teaching EE. We observed that secondary school teachers rely more on their practical experience obtained from teaching EE than on an academic perspective. It is worth noting that although economics teachers are expected to incorporate EE into their curriculum after completing their teacher training program, it was only in recent years that there has been more emphasis on entrepreneurship within teacher training programs.

Our study advances the literature in several ways. First, by comparing our findings with existing EE frameworks, we have highlighted overlaps and gaps (Mitchelmore & Rowley, 2010; Lackéus, 2015; Bacigalupo et al., 2016; Tittel & Terzidis, 2020; Lans et al., 2014) and contribute to the debate surrounding the refinement and evolution of EE practices (Hameed & Irfan, 2019; Neal, 2017). Our comparative analysis provides insights into areas where current frameworks may fall short in adequately addressing the diverse needs of secondary school learners.

Second, our findings can serve as the first step toward enhancing the effectiveness and consistency of EE in SS. By establishing clear attainment levels focused on KSAs based on teachers’ practical experiences and insights, we provide a tangible framework for curriculum development and assessing learning outcomes and pedagogy in this field. Moving forward, future studies should continue to refine and expand upon these attainment levels, focusing not only on the “what” but also on the “how” of EE delivery.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research,authorship,and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research,authorship,and/or publication of this article: This study was supported by Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Grant No. 023.015.011).

Ethical Approval

The University of Maastricht,the Netherlands’s ethical review board,approved this study (reference number: ERCIC_353_03_05_2022). The board determined that the study procedure adhered to all ethical requirements.

ORCID iDs

Sultan Göksen-Olgun

Richard Martina

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