Zhang, Qi ORCID: 0000-0002-1061-4036, Lin, Xu and Osborne, Caitriona ORCID: 0000-0002-7989-4128 (2022) A think-aloud method of investigating translanguaging strategies in learning Chinese characters. Applied Linguistics Review . ISSN 1868-6303
Abstract
Asian scripts that are significantly different from Roman-derived alphabets usually impose difficulties in learning. Translanguaging has therefore been explored as a pedagogical tool for the language classroom, including Chinese. While learning Chinese characters is thought to be one of the main challenges for students learning Chinese as a foreign language (CFL), there seems to be a paucity of up-to-date research into the strategies that adult students use to learn this logographic script. Situated in the translanguaging framework, this study employs the think-aloud method to investigate strategies utilised by a group of CFL beginner adult learners when learning characters. Drawing on the results of five think-aloud exercises with CFL learners over five weeks, as well as follow-up tests of their long-term memory of Chinese characters, this study shows that a variety of translanguaging strategies were utilised during the process of learning Chinese characters, and that overall three types of translanguaging strategies were observed: a) embodiment, b) translanguaging resemblance, and c) hybrid. The proposed typology of translanguaging strategies contributes to the further application of translanguaging as a methodology. It also sheds light on future learning strategy research across different linguistic systems.
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Subjects: | Humanities > Language Social Sciences > Education |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Humanities and Social Science > School of Applied Language and Intercultural Studies |
Publisher: | Walter De Gruyter |
Official URL: | https://doi.org/10.1515/applirev-2022-0135 |
Copyright Information: | © 2022 Walter de Gruyter |
ID Code: | 29155 |
Deposited On: | 24 Oct 2023 15:15 by Qi Zhang . Last Modified 24 Oct 2023 15:15 |
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