L’apprentissage en ligne au Canada : frein ou innovation pédagogique ?
Bibliographic record
Abstract
Cet article porte sur l’apprentissage en ligne comme élément susceptible d’amener un nouveau rapport au savoir. L’autrice considère l’apprentissage en ligne comme un catalyseur qui refait l’image de l’éducation, relie en réseau les établissements universitaires, répond aux orientations gouvernementales et oblige le professeur à réfléchir à son nouveau rôle. L’étude porte sur deux cours offerts à des adultes inscrits aux études supérieures en 2000-2001. Ces cours ont utilisé la recherche dans les banques de données électroniques, la navigation dans des sites reliés aux cours et l’approche collaborative à partir de thématiques, d’histoires de cas, de résolutions de problèmes. Les travaux d’équipes étaient effectués à distance, grâce aux outils de recherche virtuels. Le texte rapporte les grandeurs et les faiblesses de ce mode d’apprentissage.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.019 | 0.012 |
| Scholarly communication | 0.012 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 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".