Apports et limites des tâches web 2.0 dans un projet de télécollaboration asymétrique / Benefits and limitations of web 2.0 tasks in an asymmetrical tele-collaboration project
Bibliographic record
Abstract
Cet article se penche sur un échange en ligne lors duquel des étudiants de Master FLE (futurs enseignants de français) ont fait réaliser une soixantaine de tâches d’apprentissage à distance à des apprenants chypriotes et lettons. Pour un tiers de ces tâches, qui constituent l’objet d’analyse, les étudiants de FLE ont fait appel à des applications du Web 2.0. L’article en propose d’abord une délimitation et une catégorisation. Puis il cherche à comprendre les raisons pour lesquelles ces tâches n’ont pas débouché sur des échanges avec le monde extérieur, ni même, dans certains cas, à une diffusion des productions finales ; il s’oriente pour cela vers la question du ou des destinataire(s) des productions réalisées par les apprenants. This article focuses on an online exchange in which students in a Master FLE (French as a Foreign Language) class (future French language teachers) asked Cypriot and Latvian French-language learners to complete sixty distance-learning tasks. One third of these tasks, which are the focus of this article, used Web 2.0 applications. The article first describes and categorizes the tasks. Then it tries to understand why these tasks have not led to the expected interactions with a wider online audience nor to the anticipated dissemination of the content developed by the learners. It (continues) concludes by exploring the question of who are the intended recipient(s) of the content produced by these learners.
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 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 | 0.012 | 0.027 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".