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Cited by 29Academic integrity and plagiarismArtificial Intelligence in EducationEthics and Social Impacts of AI

The impact of AI guilt on students’ use of ChatGPT for academic tasks: Examining disciplinary differences

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Qu, Yao, Wang, Jue·2025·Journal of Academic Ethics
DOI 10.1007/s10805-025-09643-x
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Abstract

Generative artificial intelligence (GenAI) tools like ChatGPT are reshaping higher education, raising concerns about academic integrity alongside potential benefits. The psychological tension accompanying the decision whether to use GenAI or not for a particular task may lead to “AI guilt”—students’ moral discomfort when using GenAI for traditionally human tasks. This study examines the impact of AI guilt on students’ use of ChatGPT for academic tasks, focusing on disciplinary differences between pure and applied fields. We conducted a survey at a Singaporean university, measuring AI guilt and ChatGPT usage. Using logistic regression analysis, we found that AI guilt significantly reduces ChatGPT use for creativity-based tasks but not for routine-based tasks. The relationship between AI guilt and ChatGPT use is linear in pure fields, while applied fields show a nonlinear pattern. Specifically, the perceived risk of being detected and potential academic penalties decreases ChatGPT use in creativity-based tasks for all samples, while rationalization tendencies increase it. Interestingly, the interaction between rationalization tendencies and perceived social norms reduces usage, reflecting the tension between internal justification and external pressures. Heterogeneous analysis shows that rationalization tendencies and perceived risk influence pure fields more, whereas social norms drive applied fields more. These results show how AI guilt varies across disciplines and affects task-level GenAI tool use, offering insights for developing tailored ethical guidelines and integration strategies in higher education.

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  • Academic integrity enforcement emerged as a central concern, particularly regarding unauthorised AI use in assessments and the difficulty of detecting AI-generated content.

    “Academic integrity enforcement emerged as a central concern, particularly regarding unauthorised AI use in assessments and the difficulty of detecting AI-generated content.”

    From Six Institutional Intervention Areas to Support Ethical and Effective Student Use of Generative AI in Higher Education: A Narrative Review (2026) · cites this paper as Qu & Wang, 2025

    The Implications section recommends rules for undisclosed GenAI use and assessments that specify when GenAI assistance is prohibited, supporting the concern about unauthorised use. The section on creativity-based tasks discusses students’ fear of being detected and penalised; it does not say that detecting AI-generated content is difficult. (LLM, conf=0.87)

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Cited by

Sorted by citations

Authors
Qu, Y., & Wang, J.
Affiliations
Nanyang Technological University (SG)
Corresponding author
Wang, Jue
ORCID
Venue
Journal of Academic Ethics
Publisher
Springer Science and Business Media LLC
Published
2025-05-10
Volume
23
Issue
4
Pages
2087-2110
ISSN
  • 1570-1727 (ISSN-L)
  • 1572-8544
DOI
10.1007/s10805-025-09643-x
OpenAlex
W4410258330
Cited by
29
References
15
Citations by year
2026: 22 · 2025: 7
FWCI
30.01
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Academic Ethics (publishedVersion, cc-by-nc-nd)
  • DR-NTU (Nanyang Technological University) (publishedVersion, cc-by-nc-nd)
Funders
Institute for Pedagogical Innovation, Research & Excellence (InsPIRE) at Nanyang Technological University
Topics
  • Social Sciences › Safety Research › Academic integrity and plagiarism
  • Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
Keywords
ChatGPT, generative AI, academic integrity, student use of AI, disciplinary differences, risk perception, perceived social norms, higher education

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