Les soutiens et les formations à la prise de notes offerts dans les cégeps au Québec
Bibliographic record
Abstract
À l’entrée au Cégep, la capacité à prendre des notes devient primordiale pour la réussite, car les cours sont plus denses et vont plus vite. Cet article interroge la manière dont les cégeps s’y prennent pour soutenir le développement des compétences de prise de notes de leurs étudiantes et de leurs étudiants. Pour cela, un portrait des soutiens à la prise de notes offerts dans les 47 cégeps publics a été dressé par la consultation des sites Web des cégeps et de quelques personnes porteuses de dossiers pour approfondir les informations. Les résultats montrent que les cégeps semblent peu nombreux à offrir des ateliers ou du matériel pour soutenir la prise de notes. Lorsqu’ils le font, la manière dont ils procèdent est contestée au regard des recherches antérieures.
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 | 0.018 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.021 | 0.061 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".