Les systèmes d’émulation utilisés par les enseignants novices pour gérer les comportements d’élèves s’appuient-ils sur la formation initiale ?
Bibliographic record
Abstract
Dans le but d’améliorer la formation des futurs enseignants du primaire, cette contribution examine la pertinence du dispositif de formation en alternance intégrative de la HEP Vaud, en Suisse. Plus spécifiquement, dans le cadre de l’enseignement primaire, elle étudie l’utilisation par des enseignants novices de systèmes d’inspiration béhavioriste afin de gérer les comportements de leurs élèves, principalement l’usage des systèmes d’émulation.Nous constatons que les enseignants de notre échantillon qui y ont recours en ont pris connaissance sur le terrain professionnel, lors de leurs stages et non dans le cadre de la formation en institut. Nous relevons également qu’ils n’ont qu’une compréhension partielle de ces systèmes et qu’ils les appliquent sous forme de trucs et astuces, sans s’appuyer sur des savoirs robustes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.004 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".