Apprendre à organiser et à gérer la classe, communauté d’apprentissage assistée par l’ordinateur multimédia en réseau
Bibliographic record
Abstract
Cet article présente les fondements théoriques de la gestion de classe d'orientation socioconstructiviste et les jalons d'application de la notion clé de classe, communauté d'apprentissage. La pertinence sociale et pédagogique de cette orientation pour la formation des enseignantes et des enseignants est analysée. Des illustrations d'un tel fonctionnement de classe sont tirées de la pratique d'universitaires et d'enseignantes et d'enseignants associés. Leur pratique est soutenue par l'ordinateur multimédia en réseau et des exemples en provenance du programme PROTIC qui met à la dis- position de chaque élève un ordinateur portable sont inclus. Le potentiel des ressources et des outils en ligne (Internet et intranet) est examiné en rapport avec le développement de la classe, communauté d'apprentissage. Des implications pour le développement professionnel des pédagogues sont mises de l'avant.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 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".