Generative AI in EFL contexts: Q-methodological analysis of cognitive dissonance patterns and self-regulation strategies among Chinese tertiary learners
Open accessAbstract
Generative Artificial Intelligence (GenAI) has recently attracted growing attention in English as a Foreign Language (EFL) education, offering opportunities for personalised learning and efficiency gains. Yet, alongside these benefits, learners also face psychological tensions, particularly cognitive dissonance, that remain underexplored in current research. Prior work has often examined GenAI use through acceptance-oriented models, which is informative but leaves less room to capture coexisting tensions and the ways learners manage them in practice. Grounded in Cognitive Dissonance Theory, this study investigates how Chinese university students experience and regulate dissonance when using GenAI for English learning. Employing Q methodology, 25 participants were invited to sort 45 statements representing diverse perspectives on GenAI-assisted EFL learning. The Q-sorts were analysed using principal component analysis with Varimax rotation, supported by PQMethod and KADE software, to identify shared patterns of subjective viewpoints. The analysis revealed three salient dissonance types: efficiency-capacity dissonance (concerns over competence loss despite efficiency gains), instrumental-traditional dissonance (conflict between appreciation of AI tools and commitment to teacher-led methods), and trust-reliance dissonance (dependence on GenAI coupled with skepticism about its reliability and ethical risks). Post-sort interviews further identified six self-regulation strategies,…
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Overreliance is better understood as a patterned behavioral and psychological response than as mere frequency of use.
“These studies reinforce the idea that overreliance is better understood as a patterned behavioral and psychological response than as mere frequency of use”
From Generative AI, Cognitive Offloading, and Learner Agency in Higher Education: A Scoping Review (2026) · cites this paper as Zheng & Wang, 2026
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Generative AI, Cognitive Offloading, and Learner Agency in Higher Education: A Scoping Review
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“Such findings suggest that dependence is not simply a matter of how often students use GenAI but of how they resolve or fail to resolve these tensions in practice (Hou et al., 2025; Zheng & Wang, 2026).”
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- Authors
- Zheng, C., & Wang, Y.
- Affiliations
- Nanjing Normal University (CN)
- Corresponding author
- Zheng, Chenxi
- Venue
- Acta Psychologica
- Publisher
- Elsevier BV
- Published
- 2026-04
- Volume
- 264
- Pages
- 106531
- ISSN
- 0001-6918 (ISSN-L)
- OpenAlex
- W7131081074
- Cited by
- 4
- References
- 83
- Citations by year
- 2026: 4
- FWCI
- 79.76
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Acta Psychologica (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Social Sciences › Arts and Humanities › Language and Linguistics › EFL/ESL Teaching and Learning
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Social Sciences › Decision Sciences › Management Science and Operations Research › Q Methodology Applications
- Keywords
- generative AI, EFL learning, cognitive dissonance, self-regulation strategies, Chinese university students, AI-assisted language learning, student attitudes toward AI, hybrid instruction, AI ethics in education
- MeSH terms
- Self-Control, Generative Artificial Intelligence, Adult, China, Cognitive Dissonance, Female, Humans, Learning, Male, Students, Multilingualism, Young Adult
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