Pratiques gagnantes de directions d’établissement scolaire pour surmonter les obstacles rencontrés en supervision pédagogique 1
Bibliographic record
Abstract
La supervision pédagogique comme composante de la qualité d’enseignement constitue un défi pour les directions d’établissement, responsables de la gestion pédagogique. À cet égard, cette recherche collaborative a amené 21 directions à traiter de leurs pratiques gagnantes pour surmonter les obstacles qu’elles rencontrent en supervision. Nous avons classé chaque type d’obstacles en fonction des capacités transversales du ministère de l’Éducation, du Loisir et du Sport du Québec (2008). Par le biais d’un partage d'expertises lors de dix rencontres en groupe focalisé, deux groupes et praticiens et des chercheurs ont répertorié collectivement un ensemble de pratiques gagnantes mises de l’avant pour surmonter chacun de ces types d’obstacles. Les participants de cette étude ont surtout ciblé les structures collaboratives en termes de pratiques gagnantes et les implications des modes d’accompagnement individuel comme obstacles à surmonter. De plus, les politiques de reddition de comptes apparaissent à la fois comme des outils de contrôle et comme des leviers à la supervision.
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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 | 0.044 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.005 | 0.009 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".