The Education of Entrepreneurs: An Instrument to Measure Entrepreneurial Development
Bibliographic record
Abstract
ABSTRACTEntrepreneurship education programs have expanded across post-secondary education in the past thirty years, leading to an increased need in instruments that can evaluate the impact of entrepreneurship education. An instrument in entrepreneurial development with sub-scores in Entrepreneurial Intent, Entrepreneurship Self-Efficacy, Entrepreneurship Outcome Expectations, and Goal Directed Activity was revised over three related studies to investigate the effect entrepreneurship education has on entrepreneurship development. In three separate samples, this instrument differentiated between students, existing entrepreneurs, and alumni individuals who had entrepreneurial coursework versus individuals who did not participate in entrepreneurial education.KeywordsEntrepreneurship, education, instrument development, social cognitive career theoryINTRODUCTIONWith the rise of global economic competition, evolving business markets, and international economic uncertainty, many nations have looked for solutions to stabilize fiscal conditions. One approach has been to focus on entrepreneurship as a means of building sustainable business models upon which new ventures will flourish. With growing trends towards innovation as an economic driver, entrepreneurship has become a commonly referenced term in the popular as well as academic press and has been identified by policy leaders as a crucial element to the global marketplace. Approximately four million new businesses are created annually contributing the majority of new jobs to the US economy (Haltiwanger et al, 2009) as an illustration of the impact entrepreneurship has on economic development. Worldwide, an increased emphasis has been placed on educating the current and future workforce in aspects of entrepreneurship as a means of remaining globally competitive. Business and government officials have called upon post-secondary education to help address the need for entrepreneurs and to develop the knowledge, skills and abilities individuals require to successfully implement new business ventures. This study operationally refines the constructs of entrepreneurship development including the further design of existing instruments to measure these constructs. Moreover, these re-designed instruments are administered in three validity studies to three different samples of: (1) undergraduate students who completed an entrepreneurship course; (2) existing entrepreneurs; and (3) college graduates who had completed an entrepreneurship course up to seven years ago versus graduates who had not completed any entrepreneurship coursework. A review of the existing literature is provided below to frame entrepreneurship education in the present research, which builds upon previous study of entrepreneurial education worldwide (Santos, 2013; Engle et al, 2011) and others.Entrepreneurship educationKatz (2003) provides a historical context for the rise of entrepreneurship education in American higher education, from the earliest courses found in 1876 to focused efforts at Harvard beginning in 1947 and an increase in programs being offered in the 1970s. Today, over 1,600 US institutions of higher learning offer entrepreneurship-related courses with more than 275 endowed faculty positions and close to 50 refereed journals dedicated to the field of entrepreneurship (Katz, 2003). Gibb (1993) studied the growth of entrepreneurship education programs in the United Kingdom, illustrating a growth in the number of programs since the 1980s. The growth in entrepreneurship education programs has not been limited to the United States, as other nations around the globe have also looked to develop programs including Canada (Myrah, 2006), Portugal (Silva, et al, 2012), and the European Union (Turnbull, 2012). Despite the growth in entrepreneurial education programs, little has been done to measure the impact of entrepreneurship education on entrepreneurship development.The ability for an individual to learn entrepreneurship skills has been questioned in the popular and academic literature. …
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".