La Boussole numérique éducative : développement d’un outil d’autoévaluation des usages pédagogiques du numérique du personnel enseignant
Bibliographic record
Abstract
Le développement de la compétence numérique du personnel enseignant est un enjeu important pour s’assurer que le potentiel du numérique soit adéquatement opérationnalisé en contexte d’apprentissage. Pour ce faire, les usages pédagogiques du numérique par les enseignants doivent être évalués afin de mettre en place des stratégies qui répondront aux besoins des milieux. Dans cette perspective, cet article a pour objectif d’analyser le développement d’un outil d’autoévaluation des usages pédagogiques du numérique. Basé sur un cadrage conceptuel sur les processus cognitifs et les niveaux d’interaction, c’est avec l’approche méthodologique Design-Based Research que l’outil a été développé en collaboration avec le milieu scolaire.
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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 | 0.026 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".