Validation d’un système d’observation du climat d’apprentissage en activité physique
Bibliographic record
Abstract
L'article a pour objectif la validation d'un système d'observation du climat d'apprentissage (SOCA) qui constitue une stratégie novatrice d'analyse du processus d'enseignement-apprentissage. Son originalité repose sur l'observation des types d'implication (déviance, passivité, inconsistance, application, enthousiasme) manifestés par des participants lors de séances d'enseignement en activité physique. Son développement est basé sur la notion de climat d'apprentissage; celui-ci correspond à l'ambiance de travail qui règne pendant une séance d'enseignement et qui se manifeste par le degré d'implication des participants dans la réalisation des tâches proposées par l'intervenant. Les cinq procédures de validation (validation de contenu, justesse de codification, fidélité interanalyste, validité d'utilisateurs potentiels, validité de construit) confirment la validité et la fiabilité du SOCA pour décrire des comportements de participants représentatifs du climat d'apprentissage.
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 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 | 0.018 | 0.068 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".