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Cited by 243EFL/ESL Teaching and LearningArtificial Intelligence in EducationEnglish Language Learning and Teaching

Modelling Generative AI Acceptance, Perceived Teachers' Enthusiasm and Self‐Efficacy to English as a Foreign Language Learners' Well‐Being in the Digital Era

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Huang, Fangwei, Wang, Yongliang, Zhang, Haijing·2024·European Journal of Education
DOI 10.1111/ejed.12770
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Abstract

As artificial intelligence (AI) has been integrated into foreign language (FL) education, learners' well‐being is influenced by various factors, including technological, personal and contextual elements. However, few studies explored how external and internal factors jointly shape FL learners' well‐being in the era of generative AI. To fill this gap, this study explores the effects of generative AI acceptance, perceived teachers' enthusiasm and self‐efficacy on FL learners' well‐being by investigating 613 university learners of English as a foreign language (EFL). The structural equation modelling results reveal that (1) generative AI acceptance positively predicts EFL learners' well‐being and self‐efficacy; (2) perceived teachers' enthusiasm does not predict learners' well‐being and positively predicts EFL learners' self‐efficacy; and (3) the self‐efficacy for receptive skills mediates the relationship between generative AI acceptance/perceived teachers' enthusiasm and EFL learners' well‐being, whereas self‐efficacy for productive skills does not play the mediation role. This research broadens the understanding of the antecedents of EFL learners' well‐being and extends the application of self‐efficacy theory in the AI‐driven educational environment, providing significant pedagogical implications.

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Cited by

Sorted by citations

Authors
Huang, F., Wang, Y., & Zhang, H.
Affiliations
  • Peking University (CN)
  • North China University of Water Resources and Electric Power (CN)
  • Education University of Hong Kong (HK)
Corresponding author
Wang, Yongliang
ORCID
Venue
European Journal of Education
Publisher
Wiley
Published
2024-09-28
Volume
59
Issue
4
ISSN
  • 0141-8211 (ISSN-L)
  • 1465-3435
DOI
10.1111/ejed.12770
OpenAlex
W4402961932
Cited by
243
References
15
Citations by year
2026: 102 · 2025: 114 · 2024: 27
FWCI
383.27
Type
journal article
Language
en
Open access
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
European Journal of Education (publishedVersion)
Topics
  • Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Physical Sciences › Computer Science › Information Systems › English Language Learning and Teaching
Keywords
self-efficacy, student well-being, EFL learners, university students, receptive skills, productive skills, mediation

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

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