Pratique réflexive et études de cas : quelques enjeux à l’utilisation de la méthode des cas en formation des maîtres
Bibliographic record
Abstract
Cet article porte sur la méthode des cas, approche qui suscite beaucoup d'intérêt en formation des maîtres. Elle se présente comme un dispositif de formation particulièrement adapté aux objectifs professionnels poursuivis. Ceux-ci consistent, entre autres, à rendre l'enseignant plus réflexif, c'est-à-dire capable de réfléchir sur sa pratique et de l'analyser. Nous identifions divers modes d'exploitation possible des cas en lien avec des objectifs de formation variés. Prenant appui sur notre propre expérience avec cette méthode, nous essayons également de cerner quelques enjeux importants que soulève l'utilisation de la méthode des cas comme outil pédagogique pour développer, chez les étudiants en formation, des habiletés de pratique reflexive.
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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.000 | 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; both teacher heads agree on what is shown here.
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".