Early Pre-Reading Assessment in Bilingual Children: Establishing Predictive Validity Clinical/Theoretical Relevance of a Linguistically-Appropriate Urdu Phonological Tele-Assessment (U-PASS) Tool
Notice bibliographique
Résumé
A significant percentage of children have inadequate reading skills, internationally and in Canada (UNESCO, 2017). This is of concern as reading acquisition is crucial for age-appropriate academic and reading growth. It is important for speech-language pathologists (SLPs) and educators to provide early reading intervention prior to Grade 3, when children use established reading skills to acquire new information and understand increasing complex text. A major component of early intervention is pre-reading assessment tools. Pre-reading skills include phonological processing (i.e., recognition and manipulation of spoken sound structures), a cognitive-linguistic skill which contributes to reading abilities in monolingual and bilingual children. Pre-reading assessment tools commonly use phonological processing skills to identify children at risk for potential reading difficulties, prior to manifestation at later grades. However, pre-reading assessment tools have been predominantly developed and validated for English-speaking monolinguals, despite over 50% of the world’s population being bilingual (Grosjean, 2010; Ryan, 2013). Bilingual children are disproportionately under-identified for language and reading difficulties at primary grade levels (Levey et al., 2020; Muñoz et al., 2014; Samson & Lesaux, 2009). This is partially due to inadequate heritage-language pre-reading assessment tools, which results in delayed reading assessment and intervention. As well, current reading models and research studies are predominantly based on English and other Latin-based alphabetic languages, such as Spanish and French. This Anglo/Latin script bias limits comprehensive assessment and understandings of reading development in bilinguals speaking diverse alphabetic language combinations, such as Urdu and English. The investigated Urdu-English bilingual language combination differs from better-studied language combinations in terms of phonological and orthographic properties, including orthographic depth and script. Objectives: To address the evident English-centric clinical and research focus, our longitudinal project focused on predictive validation of a novel Urdu Phonological Tele-Assessment Tool (U-PASS) for 154 Urdu-English simultaneous bilingual children at the kindergarten (Timepoint 1) and Grade 1 (Timepoint 2) levels in two bilingual contexts: Pakistan (n = 104), where Urdu is spoken as a national/societal language, and Canada (n = 50), where Urdu is spoken as a heritage language. In addition — by using the novel tool — we investigated cross-language transfer between Urdu and English pre-reading and reading skills, in addition to the relationship between three phonological processing components and reading outcomes. Study 1 (see Chapter 2) examined whether the U-PASS, as assessed in kindergarten, is a predictor of future Grade 1 Urdu word and non-word reading accuracy and fluency abilities. Our hierarchical linear regression analyses established predictive validity of the U-PASS, which measured phonological awareness and rapid automatized naming (RAN), for Urdu reading accuracy and fluency outcomes across the two country contexts. In Study 2 (see Chapter 3), we examined cross-language transfer, by testing whether kindergarten-level Urdu phonological awareness and RAN skills predict Grade 1 English reading accuracy. We demonstrated consistent cross-language transfer between Urdu phonological awareness and the English word and non-word reading accuracy measures in both Pakistan and Canada, with predictive strength differences evident between RAN and reading outcomes based on country-specific contexts. In Study 3 (see Chapter 4), we compared within-language longitudinal contributions of the three phonological processing components — phonological awareness, phonological memory, and RAN — at the kindergarten level in relation to future Grade 1 word/non-word reading accuracy and fluency. We examined these skills in two separate alphabetic languages, differing in degree of orthographic depth and type of written script: The orthographically-transparent Urdu with a Perso-Arabic script and the comparatively opaque English with a Latin script. Overall, phonological awareness and RAN were important predictors of reading accuracy and fluency outcomes in both Urdu and English, with evident predictive strength differences. Phonological awareness contributed greater variance to the reading accuracy measure across both languages, and particularly in Urdu. RAN contributed greater variance to reading fluency in the orthographically-transparent Urdu script. Phonological memory did not emerge as a significant predictor across both Urdu and English. Relevance: Our studies facilitate equitable access to early pre-reading assessment, and enable speech-language pathologists and educators to provide linguistically-appropriate reading assessment for Urdu-speaking children (see Study 1 and Study 2). From a research perspective, our studies enhance understandings of pre-reading and reading development, including cross-language transfer and the relationship between phonological processing components and reading outcomes across the heritage and societal languages of Urdu-English bilingual children (see Study 2 and Study 3). We examined pre-reading and reading skills in Urdu – a commonly-spoken, yet under-researched, language globally. As well, our investigated bilingual language combination – Urdu and English – differs across linguistic distance, orthographic depth, and script, thereby contributing to linguistic diversity in child language and reading research.
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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 | 0,006 | 0,015 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,003 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,003 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
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