In GenAI we trust: An investigation of university students’ reliance on and resistance to generative AI in language learning

Abstract Advances in generative artificial intelligence (GenAI) have the potential to transform learning. As research increasingly calls for transforming the human-GenAI relationship from mere tool use to a collaborative partnership, there remains a notable gap in exploring an important factor influencing this relationship: trust in GenAI, being crucial amidst growing concerns about disuse, misuse, and abuse of GenAI in learner-GenAI interaction primarily via language. This study seeks to address the gap by investigating university students’ trust in GenAI, its related factors of reliance and resistance, and boundary conditions in using GenAI for language learning. The research utilized an explanatory sequential mixed-methods design. In Study 1, a proposed conceptual model within the stimulus-organism-response framework was quantitatively tested through structural equation modeling using a survey. Data were collected from 682 university students who used GenAI in language learning. Study 2 further confirmed the results through 40 qualitative interviews and refined the conceptual model by offering a deeper understanding of the relationships. The findings indicate that trust in GenAI is a significant factor in university students’ use of GenAI for language learning, with its influence on behavioral intention to use mediated through reliance and resistance. Moreover, forms of the five factors are identified: trust in GenAI, reliance, resistance, perceived risk, and actual use. Additionally, two boundary conditions are identified: perceived risk between trust in GenAI and reliance/resistance, and self-directed learning between behavioral intention to use and actual use. These findings provide theoretical, research, and practical implications regarding the appropriate use of GenAI in education.

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Publication Details

Journal
International Journal of Educational Technology in Higher Education
Published
2025-08-19
DOI
https://doi.org/10.1186/s41239-025-00547-9
Citations
12
Primary Topic
AI in Service Interactions
Type
article
Field-Weighted Citation Impact
29.77
Controls
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article

In GenAI we trust: An investigation of university students’ reliance on and resistance to generative AI in language learning

Feifei Wang, Gary K. W. Wong, Nuoen Li, Alan Cheung
12 citations
International Journal of Educational Technology in Higher Education
AI in Service Interactions
29.77
article

In GenAI we trust: An investigation of university students’ reliance on and resistance to generative AI in language learning

Feifei Wang, Gary K. W. Wong, Nuoen Li, Alan Cheung
article en
12 citations

Abstract

Abstract Advances in generative artificial intelligence (GenAI) have the potential to transform learning. As research increasingly calls for transforming the human-GenAI relationship from mere tool use to a collaborative partnership, there remains a notable gap in exploring an important factor influencing this relationship: trust in GenAI, being crucial amidst growing concerns about disuse, misuse, and abuse of GenAI in learner-GenAI interaction primarily via language. This study seeks to address the gap by investigating university students’ trust in GenAI, its related factors of reliance and resistance, and boundary conditions in using GenAI for language learning. The research utilized an explanatory sequential mixed-methods design. In Study 1, a proposed conceptual model within the stimulus-organism-response framework was quantitatively tested through structural equation modeling using a survey. Data were collected from 682 university students who used GenAI in language learning. Study 2 further confirmed the results through 40 qualitative interviews and refined the conceptual model by offering a deeper understanding of the relationships. The findings indicate that trust in GenAI is a significant factor in university students’ use of GenAI for language learning, with its influence on behavioral intention to use mediated through reliance and resistance. Moreover, forms of the five factors are identified: trust in GenAI, reliance, resistance, perceived risk, and actual use. Additionally, two boundary conditions are identified: perceived risk between trust in GenAI and reliance/resistance, and self-directed learning between behavioral intention to use and actual use. These findings provide theoretical, research, and practical implications regarding the appropriate use of GenAI in education.

International Journal of Educational Technology in Higher EducationVol. 22(1)
Chinese University of Hong Kong (HK), Education University of Hong Kong (HK), University of Hong Kong (HK)
Openalex Percentile: Top 0%
AI in Service Interactions
29.77
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