Des balises à la réflexivité : portrait des autoévaluations post-stage en formation des enseignant·e·s
Bibliographic record
Abstract
Des balises à la réflexivité : portrait des autoévaluations post-stage en formation des enseignant.e.s Formation et profession 32(2) 2024 • ésumé Bien que l' écriture d'une autoévaluation post-stage soit couramment utilisée en formation pour favoriser le développement professionnel des futur•e•s enseignant•e•s, elle demeure insuffisamment explorée.Ce manque de documentation est particulièrement notable concernant les moyens de soutien déployés pour faire de cette pratique un réel levier d'apprentissage.Notre étude propose une analyse des balises orientant l'autoévaluation post-stage.À travers une analyse de contenu portant sur 66 balises récoltées auprès des instituts de formation à l' enseignement primaire en Belgique francophone, nous avons mis en lumière les tâches prescrites, telles que l'activation de l'autoréflexion par la complétion d'un canevas, la rédaction d'un texte libre et/ou le remplissage d'une grille critériée.
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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 | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.013 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".