Evaluating Entrepreneurship Education

Governmental departments in many countries are convinced that it is possible to motivate students at tertiary institutions of education to become entrepreneurs and to start their own businesses. The importance of entrepreneurship education and training was emphasized at the World Economic Forum recently (World Economic Forum 2009, p. 7–8): “(…) while education is one of the most important foundations for economic development, entrepreneurship is a major driver of innovation and economic growth. Entrepreneurship education plays an essential role in shaping attitudes, skills and culture–from the primary level up. (…) We believe entrepreneurial skills, attitudes and behaviors can be learned, and that exposure to entrepreneurship education throughout an individual”s lifelong learning path, starting from youth and continuing through adulthood into higher education–as well as reaching out to those economically or socially excluded–is imperative.”

This research project aims at assessing the effects of entrepreneurship education on students” ability to discover whether an entrepreneurial career suits them. In the previous chapter I argued that this assessment has to be done directly after students have finished the course. But neither instructors nor researchers conducting this assessment may expect that those students who are encouraged to start an own business do so right at this time. Thus one has to first think of a suitable theoretical framework that allows predicting entrepreneurial activity when there is a time lag expected between the end of the course and the start of the business.

Overall, this book aims at discussing and determining the effects of entrepreneurship education on entrepreneurial attitudes and intentions, both from a theoretical, but also from an empirical perspective. Having laid out the theoretical foundations in the previous chapter, I now describe my research design and the generation of a dataset based upon which I can empirically measure the size and nature of the effects of entrepreneurship education in the following chapters. I argued that my theoretical framework has some advantages compared to those of previously conducted studies (see subsection 1.2.4). In this chapter I discuss the practical application of this framework. On the other hand, I discuss several caveats emanating from the data that have to be kept in mind when interpreting the findings of the following chapters. I also present the data collection processes in detail to prove the validity of my data and to make a reproduction of this design possible for a further validation of my findings.

Researchers in the field of entrepreneurship aim at developing a better understanding of individual deliberations regarding the attraction of an entrepreneurial career. The Theory of Planned Behavior has become a widely used theoretical framework to predict entrepreneurial activity and explore the reasons for entering such a career. However, Kolvereid (1996a) and subsequently Souitaris et al. (2007) call for more research to confirm whether their results about the attitudes-intentions link can be generalizable to other contexts. Therefore, to replicate and confirm early results about the linking of entrepreneurial attitudes with intentions I test the Theory of Planned Behavior based on my data in this chapter.

The studies by Peterman and Kennedy (2003), Souitaris et al. (2007), and Oosterbeek et al. (2010) make important contributions to the literature on the effects of entrepreneurship education. These exploit data from a treatment and control group to determine the true causal effects of entrepreneurship education on overall entrepreneurial attitudes and intentions. However, given the methodological deficiencies of these studies discussed in subsection 1.2.4, I replicate and advance these research designs in this chapter. Two research questions are addressed: What is the size and nature of the course-induced effects on mean entrepreneurial attitudes and intentions? And do these effects appeal to some subsamples of students, defined by demographic variables, prior experiences, or personality dimensions, more than to others?

In their recent study, employing a new approach to evaluate entrepreneurship education based on Bayesian Updating, Graevenitz et al. (2010) show that attending an entrepreneurship course helps students to find out about their entrepreneurial aptitude and supports them to better self-select into entrepreneurs and non-entrepreneurs. Although the overall intention to start a business decline during the course, students have stronger opinions about which career path, entrepreneur or not, suits them better. Depending on what they learn, students may adjust their opinions about their entrepreneurial aptitude upwards or downwards. This view of entrepreneurship education significantly differs from the notion in the literature. All of the studies presented in subsection 1.2.3 hypothesize a positive effect of entrepreneurship education on entrepreneurial attitudes and intentions. This misses the sorting – i.e. learning – benefits highlighted in von Graevenitz et al. (2010) and in this chapter.

Although important both for educational production (e.g. Sacerdote 2001) and the formation of entrepreneurial activity (e.g. Nanda and Sørensen 2010), the effects of social interactions on the development of entrepreneurial skills in entrepreneurship education have been completely ignored so far. At the same time there is a large potential for leveraging social interaction effects to increase the formation of entrepreneurial skills among the students: team-based business planning is a prevalent component of entrepreneurship education (Krueger et al. 2000). And due to restricted education budgets, an efficient measure, for example the reshuffling of teams to maximize beneficial social interaction effects for skill formation, is welcome to instructors and course planners. A quantification of externalities deriving from social interactions would be valuable to several stakeholder groups involved in entrepreneurship education, that are concerned about efficient educational production given heterogeneous student quality (Foster 2006).

Entrepreneurship is an important driver of the economy and plays an important role for social welfare in general (e.g. Fritsch and Müller 2008). By contrast, failure as an entrepreneur can be costly both for society and for the individual. On the one hand, for example in the context of funding of entrepreneurial ventures, it has been argued that subsidizing finance for new entrepreneurs may be socially wasteful (De Meza and Soutey 1996; De Meza 2002; Shane 2009). Having the “wrong” person driving an entrepreneurial venture could lead to missed opportunities and therefore to missed benefits in terms of job and value creation. On the other hand, a failed entrepreneurial “experiment” might be devastating to the entrepreneur in terms of psychological and financial (losses and opportunity costs) impacts (Zhao et al. 2010).