MÉTACOGNITION, ÉTATS AFFECTIFS ET ENGAGEMENT COGNITIF CHEZ DES ÉTUDIANTS UNIVERSITAIRES: TRIADE PERCUTANTE POUR L’APPRENTISSAGE ET L’INCLUSION
Bibliographic record
Abstract
L’article fait état des liens qui peuvent être établis entre les stratégies métacognitives, les états affectifs et la performance des étudiants universitaires. Il présente une analyse qualitative d’autoévaluations produites par des étudiants du premier cycle, dans le cadre d’un cours d’introduction à la statistique, au terme de la réalisation d’une situation d’évaluation comportant une tâche complexe. Les résultats suggèrent que l’engagement cognitif de l’étudiant dépend de sa prise de conscience et de sa participation active tant sur le plan motivationnel que sur le plan des actions à entreprendre. En outre, ils mettent en évidence l’importance de la mise en œuvre de situations d’évaluation qui privilégie l’autonomie, l’apprentissage en profondeur et la participation active des étudiants dans leurs propres évaluations visant à favoriser l’autorégulation ainsi qu’à encourager l’accessibilité, l’inclusion et le succès académique des étudiants universitaires.
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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 | 0.006 | 0.027 |
| 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 | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".