Balados sur les stratégies d’écoute et de prise de notes pour les étudiants d’immersion en français au niveau universitaire : de la conception à l’évaluation des impacts
Bibliographic record
Abstract
Plusieurs études ont suggéré la baladodiffusion comme outil pédagogique pour améliorer les compétences d’écoute en langue seconde (L2) au niveau universitaire. cette optique, nous avons développé une série de sept balados ancrés dans la théorie métacognitive et la théorie de l’écoute en langue étrangère présentent des stratégies d’écoute en L2 et des techniques de prise de notes. Ces balados ont été proposés à 161 étudiants inscrits dans 21 classes du Régime d’immersion en français de l’Université d’Ottawa. Nous avons ensuite mesuré leur impact sur les stratégies d’écoute et de prise de notes des étudiants. Les résultats sont mitigés, avec certaines améliorations plus ou moins significatives sur le plan quantitatif, et d’autres plus marquées sur le plan qualitatif.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".