ASL Phonological Fluency: How Do Second Language Learners Retrieve and Produce Signs?
Published In: Sign Language Studies, 2025, v. 25, n. 4. P. 632 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Beal, Jennifer S.; Bowman, Sarah 3 of 3
Abstract
One component of American Sign Language (ASL) proficiency is knowledge of and ability to manipulate the smallest meaningful units of signs, known as parameters in ASL (i.e. handshape, orientation, location, movement, and nonmanual signals). In this study, we documented university-level second language learners' performance on a receptive comprehension test and a phonological fluency sign retrieval and production task. We investigated if learners used semantic or phonological connections to facilitate sign retrieval among adjacently produced signs. We also investigated correlations between receptive and expressive measures, as well as participant factors that related to performance. Finally, we investigated if a short intervention focused on explicit instruction in ASL phonology significantly changed second modality-second language learners' (M2L2) sign retrieval and production compared to a group who did not receive the intervention. Findings suggest M2L2 learners organize their sign lexicon by shared location and meaning across signs, a strategy that can be utilized within instruction. Additionally, measures correlated. Academic hours of using ASL correlated with ASL comprehension, while learner self-rating and social hours using ASL related to their expressive performance. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Sign Language Studies. 2025/07, Vol. 25, Issue 4, p632
- Document Type:Article
- Subject Area:Language and Linguistics
- Publication Date:2025
- ISSN:0302-1475
- DOI:10.1353/sls.2025.a970565
- Accession Number:188472177
- Copyright Statement:Copyright of Sign Language Studies is the property of Gallaudet University Press for Sign Language Studies 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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