Les universités traditionnelles : à l'heure des innovations pédagogiques?
Bibliographic record
Abstract
Résumé L’examen des travaux portant sur les innovations pédagogiques en enseignement supérieur nous invite à reconnaître que la réflexion théorique est peu développée puisque l’attention est centrée sur les descriptions des projets, les multiples rôles des innovateurs et les facteurs qui encouragent ou inhibent l’implantation de telles initiatives. Notre but est de tenter d’intégrer les éléments disponibles dans les écrits descriptifs. Cela nous amène à cerner les thèmes qui se rapportent à l’organisation universitaire innovante et aux acteurs qui s’engagent dans le processus de l’innovation pédagogique. Cet article propose ainsi une grille de lecture construite à partir de la contribution des sciences sociales et de l’éducation concernant la problématique de l’innovation pédagogique. Quelques pistes de réflexion sont suggérées aux différents décideurs des établissements de l’enseignement supérieur qui désirent se lancer dans cette voie entrepreneuriale.
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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 | 0.016 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.014 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 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".