JOURNAL ARTICLE
Academic achievement of minority home language students with special education needs in English language of instruction and French immersion programs.
Published In: Journal of Immersion & Content-Based Language Education, 2024, v. 12, n. 1. P. 1 1 of 3
Database: Communication Source 2 of 3
Authored By: Sutton, Ann; Genesee, Fred; Kay-Raining Bird, Elizabeth; Chen, Xi; Sorenson Duncan, Tamara; Pagan, Stephanie; Oracheski, Joan 3 of 3
Abstract
This study explored the academic achievement of students who speak a minority language (ML) at home (i.e., a language other than the official languages of Canada, English and French) and who have special education needs (SEN), in two educational programs that differed in language of instruction: English language of instruction (ELoI), and Early French Immersion (EFI). The proportion of students (n = 131) meeting the provincial standard in reading, writing, and mathematics and the effect of gender, place of birth, socio-economic status, English proficiency level, and program were analyzed. Writing was the strongest domain, followed by reading and mathematics. ML-SEN students were equally likely to meet the provincial standard whether in ELoI or EFI, and there were few significant predictors of achievement. Participating in EFI did not increase students' risk of academic difficulty. Additional supports may be beneficial to ML-SEN students in ELoI and EFI programs. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Immersion & Content-Based Language Education. 2024/01, Vol. 12, Issue 1, p1
- Document Type:Article
- Subject Area:Language and Linguistics
- Publication Date:2024
- ISSN:2212-8433
- DOI:10.1075/jicb.23015.sut
- Accession Number:176989577
- Copyright Statement:Copyright of Journal of Immersion & Content-Based Language Education 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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