Discipline-Specific Compared to Generic Training of Teachers in Higher Education
Bibliographic record
Abstract
A recurrent theme arising in the higher education sector is the suitability and effectiveness of generic versus discipline-specific training of university teachers, who are often recruited based on their disciplinary specialties to become teachers in higher education. We compared two groups of participants who had undergone training using a generic post-graduate certificate in higher education (PGCertGeneric) versus a discipline-specific course in veterinary education (PGCertVetEd). The study was conducted using a survey that allowed comparison of participants who completed PGCertGeneric (n=21) with PGCertVetEd (n=22). Results indicated that participants from both PGCertGeneric and PGCertVetEd considered teaching to be satisfying and important to their careers, valued the teaching observation component of the course, and identified similar training needs. However, the participants of the PGCertVetEd felt that the course made them better teachers, valued the relevance of the components taught, understood course design better, were encouraged to do further courses/reading in teaching and learning, changed their teaching as a result of the course, and were less stressed about teaching as compared to the PGCertGeneric participants (p<.05). It is likely that the PGCertVetEd, which was designed and developed by veterinarians with a wider understanding of the veterinary sector, helped the participants perceive the training course as suited to their needs.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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 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".