Construction d’un hub social et formation des étudiants en ingénierie pédagogique
Bibliographic record
Abstract
Notre article présente et analyse un dispositif, mis en place progressivement, d’un espace numérique d’échanges dans une formation de l’enseignement supérieur français se destinant au métier de l’ingénierie pédagogique répondant à une compétence de formation : répondre à un appel à projet fictif. Nous tentons de démontrer, en relatant la dernière année de formation, que cette pratique de formation intentionnelle de la part de l’enseignant fait apparaître toutes les caractéristiques d’un hub social (Gobert, 2009, 2020) dans la formation, mais aussi dans les six mois qui la suivent. Par ailleurs, nous témoignons que le hub social construit ainsi des pratiques professionnelles d’anciens étudiants aujourd’hui praticiens, puisque les interactions sont encore effectives bien après la formation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 teacher head, 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".