The Impacts of a Blended Entrepreneurship Course on Secondary Students' Entrepreneurial Self-Efficacy and Entrepreneurial Intentions

Abstract

This mixed-methods study examined the impacts of a blended entrepreneurial course on secondary students’ entrepreneurial self-efficacy (ESE) and intentions, which were measured with pre- and post-surveys. The artifacts students created (elevator pitches and business canvas models) were collected. Survey results revealed no improvement in ESE, but significant improvements in two dimensions of intentions: professional attraction and entrepreneurial capacity. Artifact results showed that students could identify problems and generate solutions, but they could not project revenues. These findings suggest that blended courses can increase students’ professional attraction of entrepreneurship and entrepreneurial capacity and enable them to identify problems and generate solutions.

Keywords

entrepreneurship education entrepreneurial self-efficacy entrepreneurial intentions secondary education online and blended courses

Introduction

There is a certain consensus that entrepreneurship can boost economic growth (Nightingale & Coad, 2014; Wong et al., 2005), although most startups and small business ventures have only marginal positive impacts on economic development (Nightingale & Coad, 2014; Shane, 2009) and entrepreneurship tends to bring more benefits to developed countries than to developing ones (Almodóvar-González et al., 2020; Doran et al., 2018). However, because of a widespread belief in the economic benefits of entrepreneurship, interest in entrepreneurship education has been on the rise. While some research studies have found that entrepreneurship education has either no effect or a negative effect on students’ intentions (e.g., Oosterbeek et al., 2010; Rodrigues et al., 2012; Von Graevenitz et al., 2010), quite a few studies have reported positive impacts of entrepreneurship education on entrepreneurial knowledge, skills, and intentions (e.g., Baručić & Umihanić, 2016; Bergman et al., 2011; Souitaris et al., 2007). These mixed results can possibly be explained by pedagogical methods, research methodologies, and contexts (Nabi et al., 2017; Shahin et al., 2021; Von Graevenitz et al., 2010). In general, meta-analyses (e.g., Martin et al., 2013; Nabi et al., 2017) and most empirical studies demonstrate an overall positive impact of entrepreneurship education on individuals.

Elementary and secondary school are critical years for students to become exposed to and develop positive attitudes towards entrepreneurship (Hassi, 2016; Peterman & Kennedy, 2003). However, there is a dearth of research on secondary entrepreneurship education (Elert et al., 2015; Ho et al., 2018; Sánchez, 2013). And, similar to what Nabi et al. (2017) found after reviewing 159 articles on higher-education entrepreneurship education (most of which used subjective measures including perceived changes in attitude, knowledge, feasibility, and intentions), the majority of the studies that focused on entrepreneurship education in the secondary context used students’ self-report questionnaires (e.g., Ho et al., 2018; Peterman & Kennedy, 2003; Rodriguez & Lieber, 2020; Sánchez, 2013; Shahin et al., 2021). Mixed-methods studies that employ both quantitative and qualitative data may yield a fuller picture of the impacts of entrepreneurship education on secondary students.

Online learning was not commonly adopted in entrepreneurship education before the COVID-19 pandemic (Lin & Sekiguchi, 2020), but the pandemic forced many education communities to shift to blended or online learning, creating a need for the “resources and insights to help inform [entrepreneurship] educators as they shift to online learning” (Liguori & Winkler, 2020, p. 349). Although there are research studies on MOOCs and entrepreneurship education (e.g., Beltrán Hernández de Galindo et al., 2019; Calvo et al., 2019; Welsh & Dragusin, 2013), few studies have focused on blended and online learning that is facilitated by school teachers.

In response to the needs mentioned above, the current mixed-methods study examined the impacts of a blended entrepreneurship course on secondary students’ entrepreneurial self-efficacy (ESE) and intentions. The grounds for attaching importance to secondary students’ ESE and intentions are rooted in social cognitive career theory (SCCT). Drawing on Bandura’s (1986) social cognitive theory, SCCT suggests that individuals make career decisions based on their self-efficacy, outcome expectations, and intentions (goals), and that these three social cognitive mechanisms are interlocking (Lent et al., 1994). Self-efficacy can predict career choices and affect expected outcomes. Outcome expectations affect intentions. Compared with outcome expectations, self-efficacy is “a more influential determinant of behavior” (Lent et al., 1994, p. 84).

Seeking to contribute to secondary entrepreneurship education and blended and online entrepreneurship education, the study addressed the following research questions (see Table 1):

1. How did a blended entrepreneurial course affect secondary students' ESE?

2. Did the blended entrepreneurial course affect secondary students' entrepreneurial intentions?

Table 1.

Research Questions and Analysis Strategy.

Research question	Data collection method	Data analysis strategy
RQ1: How did a blended entrepreneurship education course affect secondary students' entrepreneurial self-efficacy?	• The Entrepreneurial Self-Efficacy Scale (ESE)	• Paired-samples t-test
	• Artifact from Lesson 10: Pitch perfect	• Scored artifacts using a rubric
RQ2: Did the blended entrepreneurship education course affect secondary students' entrepreneurial intentions?	• The Entrepreneurial Intentions Questionnaire (EIQ)	• Paired-samples t-test

Relevant Literature

Importance of Entrepreneurship

Entrepreneurship can turn an idea into action and create value for others (McGee et al., 2009; Tsai et al., 2016). Although not all entrepreneurial activities have positive impacts on economic development (Almodóvar-González et al., 2020; Wong et al., 2005), there is a certain consensus that entrepreneurship can boost economic growth by creating new jobs, improving the quality of innovations, and generating wealth (Nightingale & Coad, 2014; Van Praag & Versloot, 2007). In addition, entrepreneurship is a crucial competency for all, helping to increase creativity and self-confidence, enhance personal development, and improve employability (European Commission, 2014; Neck & Corbett, 2018).

Entrepreneurial Mindset

An entrepreneurial mindset is how an entrepreneur thinks and acts (Fayolle & Gailly, 2015). It is essential for entrepreneurship (Neck & Corbett, 2018). Opportunities, central to entrepreneurship, are interpreted in the mind of entrepreneurs (Gaglio & Katz, 2001; Lynch & Corbett, 2021). In addition, business ventures can only be created by those with an entrepreneurial mindset, “in whose mind all of the possibilities come together, who believes that innovation is possible, and who has the motivation to persist until the job is done” (Shaver & Scott, 1992, p. 39). Entrepreneurial scholars concede that there is not a clear understanding of what an entrepreneurial mindset is (Lynch & Corbett, 2021; Neck & Corbett, 2018). Drawing from cognitive psychology, Lynch and Corbett (2021) maintained that an individual with an entrepreneurial mindset cognitively “shifts between elaboration [of opportunities] and implementation as the entrepreneur learns” (p. 2). Grounded in the literature on entrepreneurial mindset, Pidduck et al. (2021) conceptualized entrepreneurial mindset as a result of the interaction between dispositional beliefs (beliefs in the information available to people) that cause individuals to think like an entrepreneur and opportunity beliefs in the existence of feasible and desirable opportunities. They believed entrepreneurial mindset drives entrepreneurial behaviors. Some researchers suggested that the components of an entrepreneurial mindset include self-efficacy, empathy, creativity, opportunity recognition, risk-taking, determination, and leadership, to name a few (Fayolle & Gailly, 2015; Zupan et al., 2018). Research shows that an entrepreneurial mindset serves as a precursor to entrepreneurial intentions and behaviors (Gerhart & Melton, 2016; Kim & Strimel, 2020; Korte et al., 2018). An entrepreneurial mindset is not only necessary for creating business ventures, but it is also important for achievement in existing businesses and organizations. Additionally, it is beneficial for anyone because it encompasses a set of characteristics, behaviors, and skills that are essential for success (Zhao, 2012).

Entrepreneurial Self-Efficacy

Self-efficacy is an individual’s perception of their ability to execute a specific behavior (Bandura, 1986). It is one of the four dimensions of psychological capital/psychological state of development (Avey et al., 2010; Luthans et al., 2004). Research has shown that psychological capital can positively affect individuals’ attitudes, behaviors, and performance (Avey et al., 2010; Newman et al., 2014). Psychological capital can be developed at short-term training sessions (Luthans et al., 2008). Entrepreneurial self-efficacy refers to an individual’s belief that they can become an entrepreneur. It is positively related to entrepreneurial alertness (Tang et al., 2021), and it can strengthen the impact of creativity on product and process innovation (Ahlin et al., 2014). Related to the current study, ESE is found to have a positive influence on entrepreneurial intentions (Zhao et al., 2005).

Entrepreneurial Intentions

Entrepreneurial intentions are self-acknowledged convictions that individuals intend to act entrepreneurially and start business ventures sometime in the future (Liñán et al., 2011). Entrepreneurial intentions are considered an important antecedent of entrepreneurial behaviors (Krueger Jr. et al., 2000; Lee et al., 2011). The theory of planned behavior and the theory of the entrepreneurial event can help explain the importance of entrepreneurial intentions. The theory of planned behavior asserts that an intention captures motivational factors that influence behaviors and indicate how likely an individual is to perform the behaviors (Ajzen, 1991). The more favorable one’s belief, the more likely one will act. According to Shapero and Sokol’s (1982) theory of the entrepreneurial event, entrepreneurial intentions depend on perceived feasibility, desirability, and the propensity to take actions on opportunities. Feasibility refers to the degree to which people consider something achievable, and desirability refers to how much individuals want to do something.

Methods

Research Design

This study employed a concurrent triangulation mixed-methods design. Quantitative data included pre- and post-surveys. Qualitative data (the artifacts participants created) were collected from the capstone lesson, Lesson 10 (see the section below titled “The Blended Entrepreneurial Course for Secondary Students” for a description of the 10 lessons) in the course. Quantitative and qualitative data were collected at the same time. Mixing occurred during the interpretation phase.

Participants and Context

Participants were 76 secondary students in the northeastern region of the United States. Recruited from three schools, these participants were enrolled in an introductory entrepreneurship course that was a required part of a business career track. Most participants were in the 11^th grade at the time of the study. Participants were primarily white (59%) and Latino (18%). There were a few Asian students (7%) and African American students (4%). The remaining students chose not to identify their race.

The Blended Entrepreneurship Education Course for Secondary Students

The entrepreneurship education course, offered over several weeks, included 10 lessons (see Table 2). It took students from framing a business idea to creating a business model and pitch framework. The topics of the 10 lessons included: defining entrepreneurship, exploring the entrepreneurial mindset, uncovering the root causes of problems, building empathy, generating ideas to solve problems, building a minimum viable product to test solutions, building a financial model for the product, exploring the market for the product, and creating an elevator pitch to present business ideas. Each lesson consisted of (a) an introductory video, (b) a learning activity, and (c) supplementary resources. The introductory videos provided participants with background information, a description of the learning activity participants would complete for each lesson, and instruction on key concepts and ideas. The learning activities were designed for participants to apply the knowledge and skills they acquired in the lessons. Supplementary resources provided additional insights for each lesson and included videos and readings.

Table 2.

Summary of Individual Lessons.

Lesson	Description
Lesson1: Defining Entrepreneurship	Students defined entrepreneurship and researched an entrepreneur
Lesson 2: Engaging the Entrepreneurial Mindset	Students explored entrepreneurial mindsets and how they could develop the mindsets
Lesson 3: Insight into Action	Students used the 5 WHY method to uncover the root causes of problems
Lesson 4: Human-Centered Design	Students interviewed potential customers to build empathy
Lesson 5: Innovation Ideation	Students ideated to discover innovative ideas to solve complex problems
Lesson 6: Minimum Viable Product	Students tested ideas and received feedback from classmates and community members to gain feasibility of a concept
Lesson 7: Money Matters	Students explored entrepreneurial finance and built financial models
Lesson 8: Selling proposition	Students completed a competition analysis
Lesson 9: Can’t Sell to Everyone	Students explored TAM-SAM-SOM and sales funnels
Lesson 10: Pitch perfect	Students completed a business model canvas, developed an elevator pitch, and crafted a pitch framework

Data Collection

Overview of procedure

The course was designed to be an online course. However, at the time of the study, participants were allowed to be in class in person but in a limited capacity, so some participants attended the class physically and those who had to quarantine participated online. The three teachers teaching the introductory entrepreneurship course received training on how to use the course, including using the introductory videos, guiding participants to work on the activities, and using supplementary resources. All three teachers taught the course in the same way. They had the classes view the learning videos using an interactive whiteboard or large television. Students who participated online watched the videos on their own devices. Participants worked on the learning activities individually due to social distancing. Participants submitted artifacts (e.g., a description of the problem they wanted to solve, an empathy map showing the needs of potential customers, etc.) to Google Classroom.

Participants took a pre-survey before the course and a post-survey upon completion of the course. The pre- and post-surveys included the same items, measuring participants’ ESE and entrepreneurial intentions. The artifacts participants created in the course capstone, Lesson 10, were also collected. Upon completing this lesson, participants created a pitch framework and business model canvas for potential stakeholders – those who could invest in their idea and business model. Participants described the problem they were trying to solve, the solution, the target market, their product’s uniqueness/competitiveness, and projected revenue for their business model.

Measures

Participants' ESE was assessed using ESE instrument (McGee et al., 2009) (see Table 3 for the instrument sub-scales and sample items). The responses were on a 5-point Likert scale with options ranging from 1 (very difficult) to 5 (very easy). The ESE scale included five dimensions: searching, planning, marshaling, implementing-people, and implementing-financial. The “implementing-people” and “implementing-financial” subscales were not used as they focused on employee supervision and large organizational financial demands that do not apply to secondary students. The ESE subscales of searching, planning, and marshaling were used. The questions in the searching subscale asked participants whether they were able to come up with a new idea, identify the real need for a product, and design a product that would meet the needs of real customers. The planning subscale queried whether participants were able to determine a competitive price, estimate the amount of startup funds they would need, and create marketing campaigns for a new product. The marshaling questions asked participants whether they were able to communicate with others and get others to believe in their business idea. The Cronbach’s alpha reliability for the pre- and post-surveys in the current study were 0.90 and 0.94, respectively.

Table 3.

The Instruments Used in this Study and Subscales of and a Sample Item for Each Instrument.

Dependent variable	Instrument	Sub-scale	Sample item
Entrepreneurial self-efficacy	Entrepreneurial self-efficacy (ESE)	• Searching	Your ability to design a product or service that will meet the needs of a real customer
		• Planning
		• Marshaling
Entrepreneurial intentions	Entrepreneurial Intention Questionnaire (EIQ)	• Professional Attraction	I feel being an entrepreneur has more advantages than disadvantages
		• Entrepreneurial Capacity
		• Entrepreneurial Intention

Participants' entrepreneurial intentions were measured with the Entrepreneurial Intention Questionnaire (EIQ) (Liñán et al., 2011) (see Table 3 for the instrument sub-scales and sample items). The EIQ comprises eight subscales incorporating items that utilize 5-point Likert responses with response options ranging from 1 (strongly disagree) to 5 (strongly agree). The subscales included education and experience, entrepreneurial knowledge, professional attraction, social valuation, entrepreneurial capacity, entrepreneurial intention, entrepreneurial objectives, and entrepreneurship education. The three subscales used to measure secondary student’s entrepreneurial intentions in the current study were professional attraction, entrepreneurial capacity, and entrepreneurial intentions. The other subscales were not used because they did not apply to secondary students or to the current study. The Cronbach’s alphas for the pre- and post-surveys were both 0.92.

Data Analysis

Survey analysis

Entrepreneurial self-efficacy was measured in three dimensions: searching, marshaling, and planning. Entrepreneurial intentions were also measured in three dimensions: professional attraction, entrepreneurial capacity, and entrepreneurial intentions. The scores of the three dimensions of self-efficacy and three dimensions of entrepreneurial intentions were computed. A paired-samples t-test was used to compare the scores of these dimensions before and after the course.

Artifact analysis

The artifacts were scored using a rubric created based on the Kern Engineering Entrepreneurship Network (KEEN) framework (see Appendix A for the rubric). The KEEN framework was created by the Kern Family Foundation to increase the quantity and quality of engineering talent in the United States. The rubric criteria included problem identification, solving problems, identifying customers or target market, identifying strategies, competitiveness, or uniqueness, projecting revenue, and explanation. There were five possible scores on each criterion: 4 (exceeding the criterion), 3 (meeting the criterion), 2 (approaching the criterion), 1 (beginning), and 0 (when the work a participant submitted was left blank).

Thirty-nine artifacts were randomly selected and scored in total, which equated to 51% of total participants’ artifacts. To ensure the validity and reliability of the qualitative analysis, the first and second authors were involved in scoring the qualitative artifacts. I (the first author) created a rubric based on the KEEN framework. The second author and I used the rubric to score three artifacts initially. We then met to revise the rubric and discuss scoring. Next, we used the revised rubric to score five artifacts independently. Then, we met to finalize the rubric, after which we independently scored 10 additional artifacts. The inter-rater reliability was 0.90. We discussed our differences and reached a consensus, after which I scored the remaining artifacts.

Results

Survey Results

Paired-samples t-tests showed that participants’ professional attraction toward entrepreneurship significantly increased from the pre-survey (M = 3.58, SD = 0.70) to the post-survey (M = 3.76, SD = 0.67) (t = −2.60, p = 0.01, d = 0.59) (see Table 4). The effect size was d = 0.59, suggesting a medium effect (Cohen, 1977). Entrepreneurial capacity significantly increased from the pre-survey (M = 3.10, SD = 0.69) to the post-survey (M = 3.35, SD = 0.70) (t = −3.24, p = 0.00, d = 0.65). The effect size was d = 0.65, indicating a medium effect. The third dimension of entrepreneurial intentions and ESE did not improve significantly.

Table 4.

Pre- and Post-test Means, Standard Deviations, and t-Test Results.

Dependent Variable	Dimension	Pre-survey n = 76		Post-survey n = 76		t	p	Cohen’s d
Dependent Variable	Dimension	Mean	SD	Mean	SD	t	p	Cohen’s d
Entrepreneurial Intention	Professional Attraction	3.58	0.70	3.76	0.67	−2.62	0.01	0.59
	Entrepreneurial Capacity	3.10	0.69	3.35	0.70	−3.24	0.00	0.65
	Entrepreneurial Intentions	2.94	1.15	3.05	1.06	−0.94	0.35	0.97
Entrepreneurial Self-Efficacy	Searching	3.34	0.73	3.41	0.86	−0.66	0.51	0.93
	Planning	3.32	0.71	3.47	0.80	−1.74	0.09	0.77
	Marshaling	3.41	0.80	3.37	0.87	0.41	0.68	0.75

Note. All scores ranged from 1 to 5. Significant results are in bold.

Artifact Results

Two categories, problem identification and solving problems, averaged over 3 (see Table 5). Specifically, the mean of problem identification was 3.54 (out of 4) with a median of 4.0, and that of solving problems was 3.18 with a median of 3.0. The mean of projecting revenue was 1.44 with a median of 1.0.

Table 5.

Mean and Standard Deviations of Artifact Scores by Rubric Category.

Category	Mean	Median	Standard Deviation	Standard Error Mean
Problem Identification	3.54	4.0	0.72	0.12
Solving Problems	3.18	3.0	0.76	0.12
Identifying Customer/Target Market	2.77	3.0	1.04	0.17
Identifying Strategies/Competition	2.44	2.0	1.02	0.16
Projecting Revenue	1.41	1.0	1.45	0.23
Explanation	2.41	3.0	1.19	0.19

Note. The highest score of each category was 4.

The total scores for each participant were placed into quartiles to look at their distribution (see Table 6). Most scores were in the first and second quartiles. Specifically, 28.20% were in the first quartile (between 19 and 24 points), and 51.28% were in the second quartile (between 13 and 18 points), indicating that most of the participants’ overall scores were above 60% of the total score.

Table 6.

Participants’ Total Score Quartiles.

Quartile	Students Scoring in Quartile	Percentage of Total, %
1^st Quartile Score of 19–24	11	28.20
2^nd Quartile Score of 13–18	20	51.28
3^rd Quartile Score of 7–12	7	17.95
4^th Quartile Score of 0–6	1	2.56

Discussion

This mixed-methods study examined the impacts of a blended entrepreneurship course on secondary students' ESE and entrepreneurial intentions. Survey results showed significant improvements in two dimensions of entrepreneurial intentions: professional attraction and entrepreneurial capacity. The improvement of the third subscale of entrepreneurial intentions (entrepreneurial intentions) was not significant. The three dimensions of ESE (searching, planning, marshaling) did not improve significantly. The analysis of students' artifacts showed that students did identify problems and generate solutions to these problems. However, many students' artifacts did not demonstrate a clear understanding of the projected revenue for the business based on a target market.

The survey results showed that the professional attraction dimension of secondary students' entrepreneurial intentions (i.e., recognizing an opportunity that could be a business idea, generating solutions to other people’s problems, etc.) increased upon completion of the course. Findings from the artifacts corroborated the survey findings, providing evidence of students' ability to identify problems and develop solutions. Both opportunity recognition and problem solving are essential to entrepreneurship. Specifically, the first crucial step into entrepreneurship is identifying an opportunity for a new business, product, or service (Nicolaou et al., 2009; Shane & Venkataraman, 2000). Shane and Venkataraman (2000) define entrepreneurship as a search for potential opportunities to create products or services and how one exploits those opportunities. Entrepreneurs focus on developing unique solutions that generate value for others (Hsieh et al., 2007; Sarasvathy et al., 2014). Given the central role of opportunity recognition and problem-solving in entrepreneurship and students’ improvement in these two aspects, the blended course equipped students with valuable entrepreneurial skills.

Findings from the artifact analysis suggested that students did not do well in projecting revenues. Students scored a mean of 1.41 out of 4.0 for this criterion. The survey corroborated this result, showing that ESE’s planning dimension (e.g., determining a competitive price for a new product and estimating the amount of startup funds needed) did not improve significantly.

There are several possible reasons why students scores were low in projecting revenues. The course’s lesson on projecting revenue was more complicated than other lessons and involved financial terminology and algebraic calculations that may have been unfamiliar to students. It also required students to use an Excel spreadsheet to create financial models for their business ideas. The spreadsheet included the projected cost of goods sold, net startup, and operating expenses, and was designed to help students calculate projected revenues and costs for an entire year. The financial terms, spreadsheet, and application of mathematics skills to computing projected revenues may have been overly challenging for high school students. Financial literacy is difficult for secondary students to grasp. The OEDC Program for International Student Assessment Excellence and Equity in Education (2016) found that only 10% of 15-year-olds achieved financial literacy proficiency.

Further, the lesson asked students to conduct a break-even analysis and calculate when the amount of product or service sold equaled the amount spent to create the product or service. Students may have had difficulty solving these algebraic problems because many secondary students lack the algebraic visualization skills to perceive the relationships between expressions in words and algebraic formulas and equations (Muchoko et al., 2019; Wahyuni et al., 2020). This is especially true when the calculations are in unfamiliar contexts, such as financial literacy.

For these reasons, the learning activity may have created an excessive cognitive load. Cognitive load refers to the amount of information held in our working or short-term memory, which has a limited capacity (Paas et al., 2010). The information becomes stored in long-term memory when we have built schemas to help categorize and make sense of new information (Sweller, 1994). The less familiar with a topic we are, the more we depend on our working memory to complete tasks. Since entrepreneurship and financial terminology were new for students, they had not built schemas to help them work with the new information. Adding the additional level of advanced mathematics could have overtaxed them.

The projecting revenue lesson can be improved with additional procedural and conceptual scaffolding to avoid overloading students’ short-term memory. Including more relevant, everyday examples like saving allowance money to purchase a game or tickets may activate students’ prior knowledge to connect financial terms to what they already know. Since worked examples can lighten cognitive load (Bannert, 2002), additional procedural scaffolding should be incorporated to walk students through worked examples using the included spreadsheet. After that, the video lesson could provide guided practice to demonstrate how students should input data into the spreadsheet for a fictional business. This way, students would become familiar with the tool (spreadsheet) and develop confidence in using it with their business ideas.

Students’ ESE did not improve, which is not consistent with Sánchez’s (2013) study that shows that secondary students’ entrepreneurial mindset (self-efficacy, risk-taking, and proactiveness) and intentions improved after they completed an elective course on financial and marketing basics, created business plans, and listened to practitioners’ talks. These inconsistent findings can possibly be explained by how self-efficacy was measured in these two studies. In Sánchez’s (2013) study, ESE was measured by items focusing on the ability to develop new product and recognize opportunities, create an innovative environment, build and maintain relationships with investors, etc. In the current study, self-efficacy was measured using items that asked students whether they were able to estimate startup funds, determine a competitive price for a new product, identify real customer needs and design products that fulfill those needs, and get other people to believe in their business ideas.

The searching dimension of ESE did not improve significantly, which can be attributed to the fact that students did not have an opportunity to interact with real customers. Most items in the searching subscale asked students whether they could identify real customer needs and design a product or service to meet those needs. The course required students to interact with potential customers to gain feedback on their product idea and design. However, due to the COVID-19 pandemic, students could not interact with real customers and relied on secondary research.

The marshalling dimension of ESE did not improve. This is explained by how students engaged with the learning activities. The marshalling subscale included questions about students’ confidence in their ability to get others to believe in their business ideas, make contact and communicate with others to exchange ideas, and explain concepts verbally and in writing. Due to the COVID-19 pandemic, students had to maintain social distance and could not work with each other in a meaningful way. They completed learning activities individually. They could not discuss with other students the problems they identified or the business ideas they generated. Nor could they practice their pitches or receive robust peer feedback. Therefore, they did not gain much experience explaining entrepreneurial concepts or communicating business ideas to others, leaving them uncertain of their abilities.

Limitations

Several limitations were present in this study. First, due to the COVID-19 pandemic, it was impossible to interview teachers and students because of issues with consent forms. Interview data could have provided additional insights into students’ experience with and attitudes towards the course. Second, due to the COVID-19 pandemic, students had to work on the project individually, and they were not able to present to local entrepreneurs. They did not have the opportunities to communicate with others to exchange ideas and get other people to believe in their ideas. Lastly, the course was run at the end of the school year in an expedited fashion. It would have been more advantageous to complete one lesson per week. This would have allowed more time for students to explore their ideas, ask questions, and talk to potential customers.

Directions for Future Research

Future research can interview students and teachers to gain an in-depth understanding of secondary students’ experiences with the entrepreneurial course and how the course impacts their ESE and intentions. Studying student growth across the course using a pre- and post-artifact analysis may also shed light on how much students learned. Future studies can have students fill out a preliminary canvas before the course’s first lesson and then create their final canvas during the capstone lesson. The third research direction pertains to projecting revenue. Findings from the artifact analysis suggested that students did not do well in projecting revenues. Future studies can explore strategies that can be used to enhance secondary students’ abilities to project revenues. These strategies can include using worked examples and procedural scaffolding that demonstrates how students should input data into a spreadsheet for a fictional business. Another direction is related to the dark side of entrepreneurship. Given that this course was the first entrepreneurship course for almost all participants, the dark side of entrepreneurship is out of the scope of the course. Entrepreneurial activities do not always bring benefits to a society. For example, Walmart’s strategies to keep prices low lead to controversial practices, such as temporary work, low wages, and outsourcing (Jaffee & Bensman, 2016). Students need to be provided with opportunities to critically examine both the positive and negative impacts of entrepreneurship on economic and social developments (Talmage & Gassert, 2020) and learn about “all sides of entrepreneurship” (i.e., uncertainty, risk, and failure) (Bandera et al., 2021, p. 623). Future studies can include these topics in their courses, which may have different impacts on secondary students’ ESE and intentions.

Implications and Conclusions

More research on secondary entrepreneurship education and on blended and online entrepreneurship education is needed. In addition, a wider variety of research methods should be employed. The majority of the existing studies on secondary entrepreneurship education used students’ self-report surveys. This study contributes to secondary entrepreneurship education by using mixed-methods to examine the impacts of a blended entrepreneurship education course on students. It shows that blended entrepreneurship education courses have the potential to increase the professional attraction of entrepreneurship, improve secondary students’ entrepreneurial capacity, and enable secondary students to identify problems and generate solutions. It also shows that building financial models for new business ventures can be challenging for secondary students.

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

ORCID iDs

Toi E Hershmann

Ugur Kale

Example Artifacts

The following sample artifact was created by Participant 18 (participants were assigned to random numbers during artifact analysis).

Scoring Rubric

Criteria	Exceeding	Meeting	Approaching	Beginning
Problem Identification	Clearly frames a problem to be solved and indicates the need for a solution to this problem	Using information given, clearly frames a problem to be solved	Identifies a clear problem to be solved without reason	Does not identify a clear problem to be solved
Solving Problems	Develops a logical plan to solve the problem and articulates a reason for choosing the solution	Develops a logical plan to solve the problem	Develops a plan to solve a problem that is unclear or incomplete	Not much consistency in problem solution, areas are left unfinished
Identify Customers or Target Market	Clearly defines specific target customer types and the problem the business solves for the customer	Clearly defines a specific customer types the problem the business solves for the customer	Clear understanding of a specific customer type but does not identify how the business solves a problem for this customer	No clear understanding of the customer base or target market
Identifying Strategies/Competitiveness/Uniqueness	Clearly identifies multiple advantages for solving the problem over competition	Clearly identifies an advantage for solving the problem over competition	Identifies a single advantage for solving the problem over the competition but isn’t clear	Does not identify advantages for solving the problem
Projecting Revenue	Demonstrates a clear understanding of the different revenue streams for the business based on customer/target market	Demonstrates a clear understanding of revenue streams but is less clear on the connection to the customer/target market	Demonstrates an understanding of at least one revenue stream but does not connect it to the customer/target market	Does not demonstrate a clear understanding of at least one revenue stream
Explanation	Explains Ideas clearly in a logical manner utilizing the business model canvas framework making connections between each section	Explains ideas clearly in a logical manner following the business model canvas framework	Ideas are explained but may be a little unclear, and/or the business model canvas framework is incomplete	Ideas are not explained clearly, and little to no information is added to the business model canvas framework

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