La formation à l’enseignement des professeurs d’université : un aperçu
Bibliographic record
Abstract
Dans nos universités, la perspective de l’embauche d’un nombre important de professeurs débutants offre l’occasion idéale de revoir les structures existantes de formation et de soutien à ces novices peu préparés aux exigences de leur métaprofession . Or, depuis trois décennies, des formations ont été mises en place et leur analyse montre qu’aux années où régnait le modèle additif ont succédé les années du modèle transformatif , conçu dans une perspective de formation continue et collaborative, élargi à la dimension professionnelle. Une exploration non exhaustive du site internet de 48 universités et de leurs centres de formation permet d’offrir un aperçu de la formation des professeurs d’université de plusieurs pays.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.016 | 0.018 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".