Technologies immersives et acquisition de compétences : une discussion
Bibliographic record
Abstract
Durant les dernières années, les outils numériques ont permis de concevoir et d’animer des formations dans un autre espace-temps. Toutefois, les interfaces classiques de visioconférence montrent leurs limites en face à face à travers un écran. L’essor des technologies immersives (réalité augmentée, réalité virtuelle, visites immersives, systèmes de téléprésence…) permet d’envisager de nouvelles dynamiques de formations et de nouvelles possibilités d’interactions, soutenant alors la démarche d’acquisition de compétences essentielles au monde du travail. Au regard de la diversité des domaines d’utilisation de ces technologies, de leurs usages et des publics auxquels elles s’adressent, cet article s’interroge sur les intentions pédagogiques lors de l’utilisation de ces outils ainsi que leurs limites éventuelles.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".