Appropriation de connaissances et de pratiques par des enseignants dans un projet de recherche en lecture-écriture
Bibliographic record
Abstract
Appropriation de connaissances et de pratiques par des enseignants dans un projet de recherche en lecture-écriture Formation et profession 30(3) 2022 • ésumé L' enseignement de la lecture et de l' écriture de textes informatifs s'avère complexe au primaire, en raison d'un manque de connaissances sur les caractéristiques de ces textes et sur leur didactique.Une recherche-action-formation a été réalisée avec 11 enseignants (4e à la 6e année) afin de soutenir leur appropriation de savoirs et de pratiques liés à ce genre de texte.Des données venant d' entretiens individuels mettent en lumière les savoirs spécifiques sur ces textes, de même que les nouvelles pratiques d' enseignement et d'articulation lecture-écriture développées pendant le projet.Cet article apporte un éclairage sur les conditions permettant le développement professionnel en didactique du français.
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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 | 0.029 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".