L’innovation frugale en éducation : Un système innovant, responsable et inclusif
Bibliographic record
Abstract
La question de l’innovation en éducation est une question assez ancienne dont la teneur a trouvé une actualité nouvelle avec l’usage accentué du numérique. Dans ce cadre, la présente étude tente de dresser un portrait, pas nécessairement complet, des pratiques pédagogiques innovantes chez les enseignants marocains pour ensuite s’atteler à celles qui concernent les manifestations de l’innovation frugale. En s’appuyant sur un cas d’étude qui concerne 139 enseignants, dont la majorité est située au primaire et au collège, l’étude cherche à mettre en perspective le rôle que pourra jouer l’université pour accompagner ces enseignants à « faire plus avec moins » et de manière responsable et inclusive en vue de diffuser les innovations et de répondre, selon les dispositions locales et avec moins de ressources, aux problèmes contextuels qui peuvent entraver la mise en place des changements souhaités.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.010 | 0.040 |
| Scholarly communication | 0.027 | 0.025 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".