JOURNAL ARTICLE
The role of existing language knowledge in bilingual and multilingual toddlers' repetition of cross-linguistic and language-specific nonwords.
Published In: Linguistic Approaches to Bilingualism, 2023, v. 13, n. 3. P. 315 1 of 3
Database: Communication Source 2 of 3
Authored By: Verhagen, Josje; Andringa, Sible 3 of 3
Abstract
Previous studies have shown that bilingual children typically score more poorly on nonword repetition (NWR) tasks than monolingual peers, which has been attributed to bilinguals' lower proficiency in the language that the NWR task is based on. To enable fairer assessments of bilingual children, Cross-Linguistic NWR tasks (CL-NWR tasks) have been developed that are based on the linguistic properties of many languages. The aim of this study is to investigate whether young children's performance on a CL-NWR is less dependent on existing knowledge of a specific language than performance on a Language-Specific (Dutch-based) NWR (LS-NWR). Bilingual and multilingual two- and three-year-olds (N = 216) completed a CL-NWR and LS-NWR, as well as a Dutch receptive vocabulary task. Parents reported the number of languages children spoke other than Dutch. Results of linear mixed-effect regressions showed that Dutch vocabulary scores related to performance on the CL-NWR task less strongly than to performance on the LS-NWR task. The number of non-Dutch languages spoken did not differentially relate to performance on the two tasks. These findings indicate that CL-NWR tasks – at least as used here – allow for more language-neutral NWR assessments within linguistically diverse samples, already at toddler age. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Linguistic Approaches to Bilingualism. 2023/05, Vol. 13, Issue 3, p315
- Document Type:Article
- Subject Area:Language and Linguistics
- Publication Date:2023
- ISSN:1879-9264
- DOI:10.1075/lab.20050.ver
- Accession Number:164178646
- Copyright Statement:Copyright of Linguistic Approaches to Bilingualism is the property of John Benjamins Publishing Co. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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