La formation Bricoleur : un modèle informé par les expériences et voix du personnel enseignant
Bibliographic record
Abstract
Cet article met en lumière les expériences d’apprentissage de 21 membres du personnel enseignant qui ont suivi une formation Bricoleur (Maker) de cinq jours. Nos analyses, fondées sur des données multimodales (gazouillis, cartes de réflexion et messages Padlet) et des entrevues, nous permettent de proposer un modèle de formation Bricoleur, destiné au personnel enseignant, qui souligne l’importance de : s’orienter vers la communauté, se situer dans un espace bricoleur, collaborer, explorer et bricoler, réfléchir, construire son identité et s’engager avec des recherches. Notre étude fait ainsi avancer les réflexions théoriques sur cette question en partageant les expériences d’apprentissage de nos participants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.015 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".