307
Views
0
CrossRef citations to date
0
Altmetric
Articles

The role of L1 self-efficacy in L2 reading comprehension: an exploration of L1–L2 cross-linguistic transfer

ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon
Pages 883-897 | Received 01 Nov 2022, Accepted 11 Sep 2023, Published online: 08 Dec 2023
 

ABSTRACT

Previous research on cross-linguistic transfer has provided evidence about the transfer of reading performance and strategies. However, little knowledge exists regarding how motivational factors (e.g. self-efficacy, intrinsic motivation [IM], extrinsic motivation [EM]) transfer and how they facilitate the transfer of reading from the first language (L1; i.e. Chinese in this study) to the second language (L2; i.e. English in this study). Furthermore, there is little agreement on the relationship between self-efficacy, IM, EM, and reading comprehension in L1 and L2 studies. This study aimed to (1) explore the relationship between self-efficacy, IM, EM, and reading comprehension in both L1 and L2; (2) identify whether self-efficacy, IM, EM, and reading performance can be directly transferred from L1 to L2; (3) and investigate how self-efficacy affects the cross-linguistic transfer of reading comprehension. 2,894 fourth-graders from 38 Hong Kong schools participated in this study. Results found that the relationship between self-efficacy, IM, EM, and reading comprehension was consistent in both L1 and L2. For cross-linguistic transfer, IM, EM, and reading performance can be transferred directly from L1 to L2, but reading self-efficacy cannot. Findings also indicated that self-efficacy indirectly affected L2 reading through several potential pathways. Implications for bilingual reading education are discussed.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Ethics approval statement

This study was approved by Human Research Ethics Committee, HKU (HREC Reference Number: EA1502066).

Additional information

Funding

This study was supported by General Research Fund by the Research Grants Council of Hong Kong SAR [Grant Number 17606415].

Notes on contributors

Yaping Liu

Yaping Liu is a Ph.D. candidate at the University of Hong Kong. Her research interests are Chinese language education, reading literacy assessment, educational measurement and assessment, and cognitive diagnostic assessment.

Choo Mui Cheong

Choo Mui Cheong is an assistant professor at the University of Hong Kong. Her research interests are assessment, testing and measurement, bilingualism and multilingualism, Chinese language and literature education, literacies and languages, and primary and secondary education.

Rex Hung Wai Ng

Rex Hung Wai Ng is the project manager of the Progress in International Reading Literacy Study (PIRLS) 2021 Hong Kong component. He is also a lecturer of the Centre for Advancement of Chinese Language Education and Research of the University of Hong Kong. His research interests are the development of reading, reading instruction, language assessment and evaluation, using ICT in supporting language teaching and learning, and blended learning.

Shek Kam Tse

Shek Kam Tse is the project consultant of the current research and a retired professor at the University of Hong Kong. He is still actively involved in the research of learning and teaching of Chinese, teaching Chinese as a second language, reading literacy, medium of instruction, composing process in writing Chinese and teacher change.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 53.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 339.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.