Comment développer le conseil pédagogique dans l'enseignement supérieur ?
Bibliographic record
Abstract
Conseiller, former et évaluer sont généralement les trois missions principales des conseillers pédagogiques dans l'enseignement supérieur. Cet ouvrage propose des outils pour l'action et l'analyse de ces trois missions. Co-écrit par une trentaine de contributeurs suisses, français, belges et canadiens, cet ouvrage s’adresse aux conseillers pédagogiques de l’enseignement supérieur, qu’ils soient novices ou expérimentés, et propose à ceux-ci des cadres d’analyse et des outils pratiques pour mener à bien leurs trois principales missions : conseiller, former et évaluer. Une partie de l’ouvrage est également consacrée à la formation et au développement professionnel des conseillers pédagogiques : comment s’initier au métier, comment analyser et évaluer la portée de ses actions, comment concevoir et mener une politique de développement et de valorisation de l’enseignement au sein d’un établissement d’enseignement supérieur ?
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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 | 0.014 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.010 | 0.022 |
| Scholarly communication | 0.014 | 0.018 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.010 | 0.004 |
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".