Un environnement 3D qui favorise le sentiment d’appartenance en situation de formation à distance
Bibliographic record
Abstract
De plus en plus de plateformes hypermédias sont créées pour combler les besoins de la formation à distance et en ligne. Le langage de modélisation Virtual Reality Modeling Language permet de créer des représentations numériques d'un environnement 3D, imitant un monde réaliste, dans lequel l’apprenant évolue de façon interactive à l’aide d’un avatar. Une étude a été menée auprès de 40 apprenants afin de mesurer l’effet d’un environnement 3D, avec avatars, sur leur sentiment d’appartenance au groupe et sur le taux de rétention. Les apprenants qui ont suivi la formation avec le monde 3D ont affirmé avoir ressenti un sentiment d’appartenance plus élevé que ceux qui ont suivi la formation avec une plateforme de type traditionnel.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".