La planification flexible des démarches d’évaluation, un levier vers une évaluation pour apprendre ?
Bibliographic record
Abstract
L’article discute l’apport de la planification des démarches d’évaluation comme levier pour soutenir les enseignants dans la mise en oeuvre d’une évaluation pour apprendre ( assessment for learning ) en classe. Il propose une réflexion théorique sur les apports d’une planification flexible, caractérisée dans l’article comme une planification approfondie et structurée (hiérarchisée) des démarches d’évaluation mais qui laisse aussi une place importante aux ajustements dans l’interaction (dynamique) et qui implique les apprenants (interactive). La contribution de l’article est de faire le lien entre les travaux scientifiques portant sur la planification de l’enseignement-apprentissage et ceux sur l’évaluation des apprentissages. Les objectifs de l’article consistent à 1) expliciter ce qui caractérise une planification flexible des démarches d’évaluation, et 2) discuter des apports d’une telle planification dans la mise en oeuvre d’une évaluation-soutien d’apprentissage dans les classes.
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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 | 0.041 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".