Regards croisés de chercheurs praticiens sur le dispositif de formation hybride FORSE : comment les enseignants transforment-ils leur modèle pédagogique en intervenant en ligne?
Bibliographic record
Abstract
Cet article s’appuie sur la confrontation des points de vue de trois enseignants universitaires intervenant dans le dispositif FORSE (Université Lyon 2). Le témoignage de leurs expériences, en tant que responsables, concepteurs, enseignants ou tuteurs, soulève tout spécialement la question de savoir en quoi et comment les travaux de recherche peuvent inspirer et guider les pratiques professionnelles. En montrant comment leurs pratiques reposent sur l’instrumentation et l’appropriation d’un outil/d’une formation, ces enseignants-chercheurs traduisent toute la dynamique qui favorise l’évolution de leurs scénarios pédagogiques. Ils pointent un certain nombre d’invariants qui ponctuent la conception et l’animation pédagogique de leurs scénarios ainsi que les questions posées au fil de leurs expériences croisées de chercheurs et d’enseignants.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.012 | 0.015 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 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".