Étude préliminaire des pratiques de navigation dans un environnement d’apprentissage informatique et mesure de leur efficacité pédagogique
Bibliographic record
Abstract
Inscrite dans une expérience plus vaste centrée sur l’à-propos d’introduire des objets d’apprentissage dans la formation en statistique des étudiants de premier cycle, cette recherche vise plus précisément à étudier l’usage effectif des ressources accessibles dans un environnement informatisé d’apprentissage. L’analyse met en jeu le registre des logs fournis par la plateforme Moodle. Les résultats montrent que l’analyse de la navigation recèle une information à portée pédagogique intéressante, relative à la définition de stratégies d’apprentissage en ligne et à la mesure de l’efficacité pédagogique de ces dernières. Il semble exister, en effet, une relation entre l’intensité d’utilisation des ressources en ligne et la note obtenue à la fin de la formation.
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 | 0.004 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".