Stratégies pédagogiques à visée universelle en enseignement supérieur en contexte d’utilisation d’une classe d’apprentissage actif
Bibliographic record
Abstract
Les classes d’apprentissage actif (CLAAC) s’inscrivent dans la volonté de concevoir des espaces qui favorisent la mise en œuvre d’une diversité de stratégies pédagogiques soutenant l’apprentissage actif. Des études ont relevé les bienfaits des CLAAC, mais peu d’entre elles permettent de décrire les stratégies pédagogiques utilisées. Cette étude multicas, menée dans un établissement d’enseignement supérieur québécois, vise à documenter les stratégies pédagogiques employées par les personnes enseignantes expérimentant les CLAAC. Des séances d’observation en classe et des entretiens individuels ont été menés auprès de six personnes enseignantes. Cet article présente donc la diversité de stratégies pédagogiques employées dans ces nouveaux espaces par les six personnes participantes.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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; 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".