visaTICE : se mesurer aux TIC et se former sous le regard d'un coach
Bibliographic record
Abstract
Cet article est lié à deux thématiques : celle de la maîtrise des TIC et celle des dispositifs d'apprentissage qui les exploitent. Il décrit et commente visaTICE, un dispositif d'apprentissage en ligne qui vise un meilleur usage des TIC chez les futurs bacheliers. VisaTICE est aussi un projet qui teste, sur le terrain, nos travaux de transposition didactique et nos connaissances des dispositifs de FAD. Nous y posons une question fictionnelle : est-il possible de greffer sur le système scolaire, des dispositifs hybrides qui complètent avantageusement les apprentissages de l'élève ? La réponse est intimement dépendante d'un acteur incontournable : le coach. Après avoir décrit la construction des éléments essentiels du dispositif, nous consacrons une partie de notre analyse au rôle du coach et aux enseignements tirés de cette première année d'activité. Cela a conduit à la planification d'une formation au contenu adaptable à un large public: enseignant, formateur, coach en TIC.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".