Élaboration et validation de l’échelle de la perception et du sentiment d’auto-efficacité en vidéocommunication (ÉPAV)
Bibliographic record
Abstract
L’article présente le processus d’élaboration et de validation de l’échelle de la perception et du sentiment d’auto-efficacité des apprenants vis-à-vis de la vidéocommunication (ÉPAV). Basée sur la théorie sociocognitive de Bandura (1977, 1982, 1997/2007), cette échelle permet d’évaluer deux dimensions : la perception générale de la vidéocommunication et celle que l’individu a de son propre niveau de compétence dans ce contexte. Les résultats soutiennent la structure bidimensionnelle ainsi que la cohérence interne de l’ÉPAV. Des corrélations avec des mesures de la motivation et de l’expérience en vidéocommunication ainsi qu’avec des mesures de l’attention en appuient la validité.
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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 | 0.029 | 0.088 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".