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Cited by 16Artificial Intelligence in EducationArtificial Intelligence in Healthcare and EducationEthics and Social Impacts of AI

In ChatGPT they trust: a study of students' perceptions and misuse of ChatGPT in higher education

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Yeung, Lorraine Ka Chung, Chow, Daisy Pui Lun, Wong, Pak Hang, Lau, Sam Shun Shun·2026·AI and Ethics
DOI 10.1007/s43681-025-00855-w
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Abstract

Generative artificial intelligence like ChatGPT paints a promising picture of enhancing students’ learning in higher education. However, little is known regarding whether the university students actually adopt ChatGPT for enhancement or misuse it for disburdenment. This study employed a qualitative descriptive research approach to investigate if there is the problem of misuse through an examination of the adoption journey of 20 university students in Hong Kong. Our findings show only a few interviewees did not use ChatGPT for disburdenment while the majority allow the cognitive artifact to liberate them from burdens of learning. Moreover, reports from misusers also show more pronounced automation bias and perception of AI agency than non-misusers. Among the misusers who are aware of the problem of AI hallucination, some exhibit a paradoxical approach of adoption behavior: they continue to rely on ChatGPT despite noticing that the new burdens of cross-checking its output may be induced. Such a decision calls into question the reasons for continuous reliance on ChatGPT. Our finding suggests that this may be associated with the students’ perception of ChatGPT as agentic, a factor known to positively shape users’ affect-based trust in AI. This study illuminates how actual cases of misuse and problematic adoption behavior unfold, offering useful directions for education of sensible, responsible and effective use of AI in the higher education context.

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  • Users' trust in AI output depends on expertise; less skilled users tend to overestimate quality while more knowledgeable users prefer critical approaches.

    “Users’ trust in the output generated by AI solutions also depends on their level of expertise, and in accordance with Yeung et al. (2026), less skilled users tend to overestimate the quality of the work while more knowledgeable people prefer critical approaches.”

    From Mapping the impact of generative AI in higher education: A scoping review of psychological and equity dimensions. (2026) · cites this paper as Yeung et al. (2026)

    Section 5.2 describes some students over-trusting ChatGPT’s accuracy, while others recognized errors and said its answers should be fact-checked. But the paper does not establish that these differences depend on users’ expertise, or that less skilled users overestimate quality while more knowledgeable users take a critical approach. No page numbers were available in our copy. (LLM, conf=0.83)

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Cited by

Sorted by citations

Authors
Yeung, L. K. C., Chow, D. P. L., Wong, P. H., & Lau, S. S. S.
Affiliations
  • Hong Kong Baptist University (HK)
  • Chinese University of Hong Kong (HK)
Corresponding author
Yeung, Lorraine Ka Chung
ORCID
Venue
AI and Ethics
Publisher
Springer Science and Business Media LLC
Published
2025-12-01
Volume
6
Issue
1
ISSN
  • 2730-5953 (ISSN-L)
  • 2730-5961
DOI
10.1007/s43681-025-00855-w
OpenAlex
W4416838436
Cited by
16
References
22
Citations by year
2026: 16
FWCI
16.72
Type
journal article
Language
en
Open access
Licence
Locations
AI and Ethics (publishedVersion, cc-by)
Funders
Hong Kong Baptist University
Topics
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
ChatGPT, generative AI, AI misuse, student perceptions, higher education, automation bias, AI agency, AI hallucination, trust in AI, responsible AI use

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