La formation des formateurs à l’ère de la numérisation de la société et de la mondialisation. Les leçons de la pandémie, les apports des sciences cognitives
Bibliographic record
Abstract
La pandémie de la covid 19 a touché plus de 1,5 milliard d’élèves et d’étudiants dans 165 pays. Elle a obligé les enseignants à concevoir de nouvelles méthodes d’enseignement, avec la mise en œuvre de l’enseignement à distance comme seule alternative à la poursuite de la continuité pédagogique. Cette situation a entrainé de nombreuses difficultés, en particulier l’absence de contacts, les problèmes techniques et les difficultés de connexion. De plus, de nombreux enseignants estiment ne pas avoir suffisamment de compétences dans le domaine des technologies numériques. Nous présentons quelques résultats qui montrent les apports des sciences cognitives dans le domaine du co-apprentissage à distance, ce qui impose une formation spécifique des formateurs à l’ère de la numérisation de la société.
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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 | 0.007 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.018 | 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".