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Record W4404518382 · doi:10.18162/ritpu-2024-v21n2-08

Le MOOC : un dispositif prometteur pour favoriser le bien-être du personnel scolaire?

2024· article· fr· W4404518382 on OpenAlexaffvenue
Marie-Pier Duchaine, Nancy Gaudreau, Éric Frénette, F. Sow Dia

Bibliographic record

VenueRevue internationale des technologies en pédagogie universitaire · 2024
Typearticle
Languagefr
FieldSocial Sciences
TopicEducation, sociology, and vocational training
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHumanitiesPsychologyPolitical scienceArt

Abstract

fetched live from OpenAlex

Cet article présente les résultats d'un projet de recherche visant à évaluer les effets perçus d'un MOOC sur le développement du sentiment d'efficacité personnelle (SEP) du personnel scolaire québécois.À partir d'un devis préexpérimental, 122 membres du personnel scolaire ont rempli un questionnaire en ligne mesurant leur SEP à intervenir auprès des élèves présentant des difficultés d'adaptation avant le début et après la fin de la formation.Les résultats des comparaisons de moyennes (test t pour groupes appariés) révèlent des effets positifs sur le SEP des personnes participantes.Ces résultats sont discutés pour fournir des recommandations aux universités en vue de soutenir le bien-être du personnel scolaire dans un contexte de formation. Mots-clésSentiment d'efficacité personnelle, bien-être, personnel scolaire, formation en ligne ouverte à tous, développement professionnel

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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.

Opus teacher head0.066
GPT teacher head0.334
Teacher spread0.268 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2024
Admission routes2
Has abstractyes

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