Executive functions: a fresh perspective for entrepreneurship education
Bibliographic record
Abstract
Purpose This paper introduces executive functions (EFs)–i.e. high-level cognitive processes that are elicited in novel and non-routinised situations–into discussions within entrepreneurship education (EE). By reviewing the existing literature, it highlights how EFs are important for the entrepreneur, their role in the entrepreneurial process and implications for improving EE. Design/methodology/approach We conduct a literature review bridging cognitive psychology, EE and entrepreneurship fields to clarify the role of EFs in the entrepreneurial process. To do so, we define EFs and then propose a model of the entrepreneurial process to frame our review and identify knowledge and gaps in current research. Findings This review shows why EFs are valuable for EE and calls for more focus on them to better prepare students for entrepreneurship and general life challenges. The findings underscore the importance of EFs in understanding key aspects of the entrepreneurial process. Although EFs are studied in the entrepreneurship and EE fields, they are rarely conceptualised from a cognitive psychology perspective, with research often focusing on isolated EF components instead of examining them as a whole. Originality/value This review is the first to highlight the role of EFs in the entrepreneurial process in a structured way. Integrating cognitive psychology insights on EFs can enrich EE for both venture creation and value creation approaches while also supporting the development of more effective programs. This focus on EFs also provides a fresh perspective and a valuable lens for understanding complex phenomena such as cognition, learning and the factors behind success and failure in entrepreneurship.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".