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Cited by 180Technology Adoption and User BehaviourArtificial Intelligence in EducationEFL/ESL Teaching and Learning

The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.

Factors Influencing Learner Attitudes Towards ChatGPT-Assisted Language Learning in Higher Education

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Cai, Qianqian, Lin, Yupeng, Yu, Zhonggen·2024·International Journal of Human–Computer Interaction
DOI 10.1080/10447318.2023.2261725
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Abstract

Concerns regarding the potential risks associated with learners' misusing ChatGPT necessitate an extensive investigation into learner attitudes towards ChatGPT-assisted language learning. This study adopts a mixed-method approach, combining structural equation modeling techniques and interviews. It aims to examine the influencing factors of learner attitudes regarding ChatGPTassisted language learning under the extended three-tier technology use model from an interdisciplinary perspective, including the technology acceptance model, etc. The study finds that information system quality and hedonic motivation are more significant in contributing to performance expectancy and perceived satisfaction compared to self-regulation in ChatGPTassisted language learning. Behavioral intention is a better predictor of learning effectiveness in ChatGPT-assisted language learning than perceived satisfaction and performance expectancy. This research also examines the partial or full mediating effects of behavioral intention and performance expectancy between other variables. Although this study is limited by some aspects (e.g., the outdated version of ChatGPT-3 or ChatGPT-3.5), it holds substantial implications for future practice and research. It appeals to more attention from future developers on hedonic motivation and information services of ChatGPT and from future researchers on a more comprehensive insight into influencing factors of learner attitudes towards ChatGPT-assisted language learning.

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Research works printed but not linked: 3

  1. Asante, I. O., Jiang, Y., Hossin, A. M., & Luo, X. (2023). Optimization of consumer engagement with artificial intelligence elements on electronic commerce platforms. Journal of Electronic Commerce Research, 24(1), 7–28.
  2. 10.2307/3151312 · DOI · Paper page
  3. Hair, J. F., Hult, G. T. M., & Ringle, C. M. (2014). Partial least squares structural equation modeling (PLS-SEM). SAGE Publications.

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Metadata

Authors
Cai, Q., Lin, Y., & Yu, Z.
Affiliations
  • Beijing Language and Culture University (CN)
  • Faculty of Foreign Studies, Beijing Language and Culture University, Beijing, China
Corresponding author
Yu, Zhonggen
ORCID
Venue
International Journal of Human–Computer Interaction
Publisher
Informa UK Limited
Published
2023-10-15
Volume
40
Issue
22
Pages
7112-7126
ISSN
  • 1044-7318 (ISSN-L)
  • 1532-7590
DOI
10.1080/10447318.2023.2261725
OpenAlex
W4387671439
Cited by
180
References
61
Citations by year
2026: 48 · 2025: 79 · 2024: 52 · 2023: 1
FWCI
46.13
Type
journal article
Language
en
Open access
Locations
  • International Journal of Human-Computer Interaction (publishedVersion)
  • SSRN Electronic Journal (acceptedVersion)
Funders
  • Key Laboratory of Science and Technology on Electromagnetic Environmental Effects and Electro-optical Engineering, People’s Liberation Army University of Science and Technology (CSLS 20230012)
  • Special fund of Beijing Co-construction Project-Research and reform of the “Undergraduate Teaching Reform and Innovation Project” (202010032003)
  • Key Research and Application Project of the Key Laboratory of Key Technologies for Localization Language Services of the State Administration of Press and Publication (20230012)
Topics
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
  • Social Sciences › Education › Artificial Intelligence in Education
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
Keywords
ChatGPT, student attitudes, AI-assisted language learning, higher education, technology acceptance model, information system quality, hedonic motivation, performance expectancy, perceived satisfaction, behavioral intention, self-regulation, mediating effect

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