School Readiness and Early Childhood Education and Care Services Among Dual Language Learners
Notice bibliographique
Résumé
Importance: Dual language learners (DLL) (ie, children learning 2 or more languages) present lower school readiness than non-DLL children, putting DLL children at risk of later school difficulties and adverse outcomes. However, it is unclear whether participation in early childhood education and care (ECEC) services may reduce this gap. Objective: To assess whether ECEC exposure may reduce the school readiness gap between DLL and non-DLL children in a population-based sample. Design, Setting, and Participants: This census survey study was performed from February to May 2022 in the Canadian province of Quebec using data from the Quebec Survey of Child Development in Kindergarten, which includes all children who attended kindergarten in the 2021 to 2022 school year in public and private schools in Quebec (n = 80 587), except for Cree and Inuit territories. Exposure: Children's ECEC arrangement before kindergarten was retrieved from register-based data and teachers and arrangements were categorized as exclusive parental care, childcare, pre-kindergarten only, or childcare and pre-kindergarten. Based on their mother tongue and language of instruction, children were classified as French speaking, English speaking, bilingual French-English speaking, or neither French nor English speaking (allophone) children, the last 2 groups of which represented the DLL category. Main Outcomes and Measures: Vulnerability in school readiness was defined as a score below the 10th percentile in any of the 5 domains of the validated Early Development Instrument (EDI): (1) physical health and well-being; (2) social competence; (3) emotional maturity; (4) language and cognitive development; and (5) communication skills and general knowledge. Results: In total, 80 587 children were surveyed, and 71 585 children were included in analyses. Mean (SD) child age was 6.0 (0.3) years, 34 911 children (48.8%) were female, and 18 341 children (25.6%) were DLL. English-speaking, bilingual French-English-speaking, and allophone children were more likely to be vulnerable in the EDI (769 of 2355 children [32.7%], 4814 of 13 981 children [34.4%], and 1622 of 4360 children [37.2%], respectively) than French-speaking children (13 664 of 50 890 children [26.9%]). In logistic regression analyses adjusted for social selection bias in ECEC arrangement, attending ECEC services was associated with a lower risk of being vulnerable among all language groups compared to parental care, with odds ratios ranging from 0.26 (95% CI, 0.25-0.27) to 0.96 (95% CI, 0.80-1.14), except in the emotional maturity domain. ECEC exposure was associated with reduction in vulnerabilities disparities between DLL and non-DLL children after adjusting for confounding factors, including socioeconomic status. Conclusions and Relevance: ECEC services may foster school readiness for all children, especially DLL, and should be considered to reduce school inequalities.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».