Investigating the Reading Strategies Used by French Immersion Pupils as They Engage With Dual-Language Children’s Books: A Multiple Case Study
Bibliographic record
Abstract
Abstract As dual-language children’s books are becoming increasingly popular in language and literacy education, scholars are starting to zero in on how students construct meaning as they read these books. In this paper, in light of the previously mentioned body of literature, we present a qualitative study focusing on the reading strategies that three Grade 3 French immersion pupils schooled in Saskatchewan deployed when they read two types of dual-language books: translated, where the entire text appears in both English and French, and integrated, where passages in French organically complete those in English without providing the exact same information. This multiple case study highlights three distinct reading profiles, and shows how monolingual and cross-linguistic reading strategies can be used by the same student as they read a dual-language book. It also shows that some students were able to adapt their reading strategies as they engaged with different types of dual-language books, whereas others more frequently utilized the same strategies. Keywords: dual-language children’s books, reading strategies, French immersion Résumé Alors que les livres bilingues deviennent de plus en plus populaires en didactique des langues, la recherche commence à s’intéresser aux comportements cognitifs de l’élève qui s’engage dans la lecture de ces œuvres. Dans cet article, à la lumière de ces études, nous relatons les résultats d’une recherche qualitative visant à décrire les stratégies de lecture que trois élèves de 3e année scolarisés en Saskatchewan en immersion française déploient lorsqu’ils lisent deux types de livres bilingues : le livre traduit, dans lequel tout le texte apparait en français et en anglais, et le livre intégré, dans lequel le texte en français complète celui en anglais, sans toutefois offrir au lecteur la même information. Cette étude de cas multiple relève donc trois profils distincts de lecteur et, par son entremise, nous montrons comment des stratégies de lecture monolingues et translinguistiques peuvent être utilisées par un même élève lorsqu’il lit un livre bilingue. Nous révélons en outre que certains élèves sont à même d’adapter leurs stratégies de lecture selon le type de livre bilingue lu, tandis que d’autres font fréquemment usage des mêmes stratégies. Mots-clés : livres bilingues, stratégies de lecture, immersion française
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".