Le rappel stimulé pour mieux comprendre les stratégies de lecture d'élèves du primaire à risque et compétents
Bibliographic record
Abstract
Cet article decrit de quelle facon la methode du rappel stimule, utilisee apres une tâche de comprehension d’un texte informatif, amene une meilleure connaissance des strategies de lecture de trois eleves de sixieme annee ayant des portraits de lecteur differents. Les explicitations et commentaires rappeles de ces eleves portant sur leurs actions et pensees permettent de degager leurs procedures pour comprendre un texte, en utilisant ou non des strategies efficaces, qui elles-memes se referent a des connaissances differentes. Les contributions et les limites du rappel stimule utilisees aupres d’eleves sont discutees. Abstract This article describes how a stimulated recall method used after a reading comprehension task contributes to a better understanding of the strategies employed by three different Grade 6 readers. After reading an informative text, the students explained and commented on their own actions and thoughts, exposing how they proceeded to understand their reading and whether or not they used strategies based on multiple knowledge types. Contributions and limits of the stimulated recall method for students are discussed.
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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 | 0.005 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".