L’utilisation du manuel numérique en contexte postsecondaire : avantages et inconvénients
Bibliographic record
Abstract
Ce texte présente des résultats tirés d’une synthèse des connaissances réalisée en 2015, concernant l’utilisation du manuel numérique en contexte postsecondaire. Les études répertoriées se concentrent sur des applications en milieu universitaire, bien que quelques-unes d’entre elles réfèrent à une formation équivalente à celle du secteur collégial technique québécois. Les articles retenus lors de cette recension proviennent de revues scientifiques essentiellement anglo-saxonnes. Le travail d’analyse a permis de mettre en exergue des avantages et des inconvénients perçus ou vécus en relation avec l’usage du manuel numérique par des enseignants et des étudiants. Les principaux résultats indiquent que l’utilisation du manuel numérique se révèle particulièrement positive quant aux formes d’interactivité qu’il permet. En revanche, différents obstacles se dressent lorsque vient le moment d’accéder à l’outil et de l’utiliser.
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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 | 0.011 | 0.032 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.013 | 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".