Élaboration de l’Échelle du sentiment d’efficacité personnelle des enseignants en gestion de classe (ÉSEPGC)
Bibliographic record
Abstract
Cet article présente l’élaboration d’une échelle portant sur le sentiment d’efficacité personnelle des enseignants en gestion de la classe. Développée selon les recommandations de Bandura (2006) et la procédure proposée par Dussault, Valois et Frenette (2007), cette échelle porte sur les cinq dimensions de la gestion de classe suggérées par O’Neill et Stephenson (2011). Lors du prétest, des analyses réalisées à partir du modèle de Rasch (Wright & Masters, 1982) ont permis d’élaborer une version constituée de 28 énoncés. De plus, des analyses factorielles confirmatoires soutiennent le modèle théorique à cinq dimensions. Des résultats similaires sont obtenus auprès d’un échantillon tiré de la population. Les forces et les limites de cette recherche sont discutées eu égard à la littérature.
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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 | 0.019 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".