Collaborer pour soutenir les nouveaux enseignants en formation professionnelle, enjeu d’une recherche-action
Bibliographic record
Abstract
Pour soutenir l’entrée des enseignants dans le monde de l’enseignement en formation professionnelle (FP), les centres de formation professionnelle (CFP) disposent de mécanismes d’accompagnement tels que des structures d’accueil et des systèmes de parrainage (Coulombe, Zourhlal et Allaire, 2010). Malgré tous les mécanismes en place, les nouveaux enseignants continuent à éprouver des besoins de soutien liés à l’apprentissage de leurs tâches de travail. Selon Coulombe, Zourhlal et Allaire (2010), ils ont notamment besoin de comprendre la tâche enseignante, d’être capables de planifier l’enseignement et l’apprentissage, d’être en mesure de gérer les groupes-classes et de soutenir les élèves ayant des besoins particuliers. En collaboration avec des enseignants expérimentés, une conseillère pédagogique et des directions de deux CFP de la région du Saguenay–Lac-Saint-Jean, nous avons donc choisi de mettre à l’essai deux groupes de codéveloppement professionnel (un par CFP participant) pour soutenir les nouveaux enseignants.
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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 | 0.031 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.012 | 0.009 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.022 | 0.008 |
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".