Technologies éducatives et apprentissages : l’histoire de TECFA, une unité de recherche et d’enseignement de l’Université de Genève - Entretien avec Daniel Peraya
Bibliographic record
Abstract
Chercheur renommé dans le domaine des technologies éducatives, Daniel Peraya parle dans cet entretien de l’histoire de TECFA (Technologies de formation et apprentissage), une unité de recherche et d’enseignement de l’Université de Genève qui a joué un rôle important dans de nombreux projets de formation hybride et à distance en Suisse, en Europe et dans les pays du Sud. Il explique comment cette unité a été créée et a évolué en termes de recherche et d’enseignement et offre ainsi un éclairage sur la manière dont les nombreuses collaborations avec des partenaires ou financeurs suisses, européens et internationaux ont permis à TECFA d’impulser de nouveaux programmes et de favoriser le développement de la formation à distance, devenant ainsi un centre de référence dans le domaine.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.006 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".