Normalisation des compétences et rationalisation pédagogique. Le cas de la formation technique au Québec
Bibliographic record
Abstract
Les politiques éducatives tendent à se placer sous l’égide du référentiel de l’efficacité. Il en résulte, de toutepart, de nouveaux modes de management public marqués par l’autonomie des établissements, la contractualisation, l’évaluation. Mais la quête d’efficacité passe également par une rationalisation pédagogique contribuant à faire évoluer les référents cognitifs de l’activité éducative. C’est l’hypothèse que nous explorons dans cet article, à propos de l’analyse du Renouveau collégial de 1993 au Québec, au cours duquel a été instauré un nouveau mode d’élaboration des curricula en termes d’approche par compétence. A partir de l’exemple des programmes d’études techniques, nous montrerons que la normalisation des compétences qui en résulte s’inscrit moins dans un renouvellement des théories de l’apprentissage que dans une structuration de la formation en fonction des exigences du marché, laissant ouverte la question des pédagogies requises à cette fin.
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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 | 0.006 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".