Teacher Supervision Practices and Principals’ Characteristics
Bibliographic record
Abstract
A questionnaire was used to determine the individual and collective teacher supervision practices of school principals and vice-principals in Québec (n = 39) who participated in a research-action study on pedagogical supervision. These practices were then analyzed in terms of the principals’ sociodemographic and socioprofessional characteristics and certain aspects of their schools. Results show that the principals favoured individual over collective supervision and tended to forego preliminary meetings. Furthermore, principals in “disadvantaged” areas were more inclined to provide the necessary training and supervision to help their teachers make informed decisions. Recommendations for more effective teacher supervision are proposed for principals to ultimately improve student achievement. Cette étude, menée par questionnaire, a porté sur les pratiques de supervision pédagogique individuelle et collective de directions et de directions adjointes d’établissement scolaire du Québec (n = 39) qui participent à une formation-recherche-action portant sur la supervision pédagogique. Cet article rend compte de leurs pratiques en supervision pédagogique individuelle et collective et établit des liens entre ces pratiques et les caractéristiques (sociodémographiques, socioprofessionnelles et de certaines caractéristiques de leurs établissements) des directions. Les résultats montrent que les directions font plus de supervision pédagogique individuelle que de supervision collective et qu’ils ont tendance à ne pas consacrer du temps aux prérencontres. De plus, les directions des milieux défavorisés tendent à fournir plus de formation et d’encadrement nécessaires pour prendre des décisions avisées. À la lumière de ces résultats nous proposons des recommandations visant un meilleur accompagnement pédagogique de l’équipe-école par les directions, dans l’optique d’amélioration de la réussite des élèves.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".