Préférences des apprenants face à l’utilisation de la technologie dans l’apprentissage des langues
Bibliographic record
Abstract
Few researchers have examined learners’ preferences for different types of technological activities in the second-language classroom. This study is an initial effort to identify which technological activities are currently used by university-level FSL students in the language classrooms and which activities and formats these learners prefer and find useful. Data was collected from students taking courses in French as a second language in three different universities. A series of questionnaires was used to assess language skills, gather demographical information and elicit preferences for technological activities. Results indicate that, in general, the students have positive perceptions of the technological activities used in their language classroom even though they don’t use them very often. Students report appreciating some technological activities but don’t find them very useful for language learning while other activities are judged useful but are not appreciated by the students. The results are presented as a continuum of activities ranked by their perceived usefulness and student appreciation. These are followed by recommendations for language teachers about the use of these activities in their classrooms.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".