Une adaptation française du Questionnaire de Régulation Émotionnelle à la situation d’apprentissage
Bibliographic record
Abstract
Cet article présente deux études de validation de l’Emotion Regulation Question - naire (Gross & John, 2003) traduit en français et adapté à la situation de préparation d’un examen universitaire. Cet outil mesure l’utilisation de deux stratégies de régulation émotionnelle : la réévaluation cognitive (changer sa façon de penser une situation émotionnelle) et la suppression expressive (inhiber l’expression de l’émotion dans une situation émotionnelle). La première étude (1) confirme les qualités psychométriques de l’instrument et (2) explore les corrélations entre le score obtenu au test et les émotions académiques ressenties par les étudiants. La seconde étude (1) confirme les qualités psychométriques de l’instrument chez les deux sexes et (2) investigue les différences de genre dans les scores obtenus au test. L’adaptation de cet outil est prometteuse pour la communauté des chercheurs en éducation soucieuse d’approfondir la question de la régulation émotionnelle en situation 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 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 | 0.017 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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; both teacher heads agree on what is shown here.
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".