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Record W2155265344

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).

2015· article· fr· W2155265344 on OpenAlexvenueno aff
Caroline Beauregard, Cécile Rousseau, Sally Mustafa

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2015
Typearticle
Languagefr
FieldSocial Sciences
TopicTeacher Education and Leadership Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychosocialPsychologyPsychological interventionIntervention (counseling)FeelingTransfer of trainingKnowledge transferPedagogySocial psychologyPsychotherapistKnowledge managementComputer science
DOInot available

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.429
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.121
GPT teacher head0.354
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2015
Admission routes1
Has abstractyes

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