Évaluer la production « spontanée » de récits oraux au secondaire obligatoire : Un design de validation d’outils d’évaluation
Bibliographic record
Abstract
Dans cet article, nous nous focalisons sur la portion du projet de recherche design consacrée à la conception-expérimentation d’une séquence portant sur la transformation d’une nouvelle très courte en un récit oral destiné à des élèves de secondaire 1. La contribution cherche à penser la didactisation et l’évaluation du court récit oral spontané. Nous abordons la question de la réception des outils d’évaluation par les enseignants. Notre analyse révèle que les enseignants reconnaissent la pertinence des dimensions de la grille d’évaluation, tout en souhaitant octroyer des points supplémentaires aux critères relatifs à l’oralité, au détriment des éléments appartenant à la structure narrative. L’enregistrement des productions et la co-évaluation par les pairs se révèlent comme des remparts aux difficultés relatives à l’évaluation de l’oral en classe.
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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 | 0.093 | 0.190 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".