L'enseignement de la prononciation en français langue seconde : de la cassette au cédérom
Bibliographic record
Abstract
Résumé: Le présent article compare deux approches de l'enseignement de la prononciation dans le cadre d'un cours universitaire de français langue seconde de niveau élémentaire faible : approche traditionnelle avec des cassettes audio et approche multimédia à l'aide d'un cédérom. L'objectif de la recherche était de savoir si, à contenu d'apprentissage identique, il existait une différence significative entre les deux approches, que ce soit au niveau des résultats quantifiables ou au niveau de la satisfaction des utilisateurs. Les résultats suggèrent que, du moins à ce niveau de compétence linguistique, il n'y a aucune différence significative entre les deux groupes bien qu'on note une amélioration plus importante dans le groupe multimédia que dans le groupe traditionnel tant au niveau de la perception qu'à celui de la production de certains sons. De plus, notre étude indique également une réaction positive des apprenants du groupe multimédia face à l'outil multimédia. Abstract: This article compares two approaches for teaching pronunciation in an elementary-level French as a second language university course: the traditional approach, using audio cassettes, and a multimedia approach using software on CD-ROM. The goal of this study was to determine whether there was a significant difference between the two approaches in the 1) perception and production of targeted sounds and, 2) user satisfaction. Although our results show that there were no statistically significant differences between the two groups, the multimedia group made slightly greater gains in both the perception and production of certain sounds. Moreover, the multimedia group had a more positive attitude vis-à-vis the multimedia tool.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".