Entrepreneurial Motivation in University Business Students: A Latent Profile Analysis based on Self-determination Theory
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The development of entrepreneurship education (EE) has become a top priority for many universities around the world. Accordingly, the objectives of this paper are to identify motivation profiles of university business students, to determine how profile membership predicts students’ entrepreneurial intention and interest to study entrepreneurship, and to identify predictors of membership in these motivation profiles. To achieve these objectives, our method entails the application of self-determination theory (SDT) in a person-centered analysis. Our study is, in fact, the first application of the full range of motivations from SDT to define students’ entrepreneurial motivations; furthermore, we use latent profile analysis to identify groups of students that can be distinguished according to these motivations. We discover four groups of students: 1) uniformly lowly motivated, 2) indifferent, 3) conflicted, and 4) uniformly highly and intrinsically motivated. We find that students in these groups differ with regard to their interest to study entrepreneurship and their intention to be entrepreneurs. We also identify psychological traits and background factors that could explain the group membership. We discuss the implications of these findings on the promotion and delivery of EE, and on how students may be motivated to become entrepreneurs.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it