Séquences de changement de formatrices universitaires dans une formation intersectorielle sur la compétence numérique en éducation
Bibliographic record
Abstract
La formation ACTION (Attestation des Compétences en Technopédagogie et en Intégration des Outils Numériques) a été vécue durant l’automne 2019. Elle était offerte à des formateurs universitaires et certains de leurs étudiants de baccalauréat en enseignement. Ce modèle unique visait le développement de la compétence numérique de ces personnes. Exploitant le cadre théorique de la croissance professionnelle de Clarke et Hollingsworth (2002), cette recherche visait à identifier les séquences de changement générées grâce à cette formation afin de comprendre son apport pour le développement de la compétence numérique (MEES, 2019) chez les différentes personnes impliquées. Elle a permis de comprendre que ce modèle innovant de formation présente un potentiel fort intéressant pour le développement professionnel des formateurs universitaires.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 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".