Faire fonctionner ce qui fonctionne : le transfert des connaissances éducationnelles par le <i>What Works Clearinghouse</i> étatsunien
Bibliographic record
Abstract
L’Institut national d’excellence en éducation (INEE) transmet les résultats de la recherche en vue d’orienter les pratiques éducatives au Québec. Il est impératif de tirer des leçons d’initiatives similaires. Ainsi, cet article examine le travail du What Works Clearinghouse étatsunien, qui répertorie les pratiques éducatives efficaces en évaluant les études selon leur rigueur. Notre analyse des écrits empiriques révèle que l’utilisation de ces pratiques est limitée puisque les membres du corps enseignant interprètent mal les niveaux de preuve et préfèrent s’inspirer de leurs collègues. Nous proposons conséquemment de promouvoir les pratiques optimales par des vidéos de praticien·ne·s et d’exclure les niveaux de preuves.
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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 | 0.015 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.023 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 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".