Measuring Student Transformation in Entrepreneurship Education Programs
Bibliographic record
Abstract
This article describes how to measure student transformation primarily within a university entrepreneurship degree program. Student transformation is defined as changes in knowledge (“Head”), skills (“Hand”), and attitudinal (“Heart”) learning outcomes. Following the institutional impact model, student transformation is the primary goal of education and all other program goals and aspects of quality desired by stakeholders are either input factors (professors, courses, facilities, support, etc.) or output performance (number of startups, average starting salary, % employment, etc.). This goal‐setting framework allows competing stakeholder quality expectations to be incorporated into a continuous process improvement (CPI) model when establishing program goals. How to measure these goals to implement TQM methods is shown. Measuring student transformation as the central focus of a program promotes harmony among competing stakeholders and also provides a metric on which other program decisions (e.g., class size, assignments, and pedagogical technique) may be based. Different stakeholders hold surprisingly different views on defining program quality. The proposed framework provides a useful way to bring these competing views into a CPI cycle to implement TQM requirements of accreditation. The specific entrepreneurial learning outcome goals described in the tables in this article may also be used directly by educators in nonaccredited programs and single courses/workshops or for other audiences.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| 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".