Les dispositifs groupaux d'analyse des pratiques au service du développement professionnel des enseignants. Quelles analyses ? Quelles pratiques ? Quel professionnel?
Bibliographic record
Abstract
Le développement professionnel des enseignants s’appuie de plus en plus sur des structures invitant les enseignants, en groupe, à analyser leurs propres pratiques. Si ces dispositifs de professionnalisation se multiplient, ils ne se ressemblent pas pour autant. À partir de descriptions de différentes démarches d’analyse de pratiques en groupe, cet article caractérise trois types de dispositifs qui se distinguent quant à leur méthode et leur déroulement, leurs assises conceptuelles et leurs visées. Il découle de cette analyse que chaque type de dispositifs peut contribuer au développement pro-fessionnel des enseignants en privilégiant une dimension de leur professionnalité. \n \nTeachers’ professional development is increasingly based on structures that invite them to analyse their practice in group. Although these devices for professionaliza-tion are more numerous, they are all different. Starting from descriptions of various procedures for practice analysis in group, this article distinguishes three types of de-vices in relation with the method and process, the theoretical foundations, and the purpose. As a result, each type of devices may contribute to a teachers’ professional development by focusing on a particular dimension of the professionality.
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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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.007 | 0.018 |
| Scholarly communication | 0.017 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 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; 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".