The Use of Video in Knowledge Transfer of Teacher-Led Psychosocial Interventions: Feeling Competent to Adopt a Different Role in the Classroom (L'utilisation de la vidéo dans le transfert de connaissances dans les interventions psychosociales menées par les enseignants : sentir que l'on a la compétence d'adopter un rôle différent dans la salle de classe).
Bibliographic record
Abstract
Because they propose a form of modeling, videos have been recognised to be useful to transfer knowledge about practices requiring teachers to adopt a different role. This paper describes the results of a satisfaction survey with 98 teachers, school administrators and professionals regarding their appreciation of training videos showing teacher-led psychosocial interventions. The association between teachers’ appreciation of the video and their desire to implement the intervention are explored in terms of authenticity, vicarious learning and self-efficacy, in an attempt to further comprehend how the use of video supports different aspects of modeling (skills - know-how, attitudes - know-how to be). The authors suggest that training videos featuring teachers leading psychosocial interventions support knowledge transfer because learners can relate to successful peers and can think of themselves as competent to replicate the intervention and comfortable to adopt a different role in the classroom.
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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 | 0.003 | 0.014 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".