Chat or cheat? Academic dishonesty, risk perceptions, and ChatGPT usage in higher education students

Chat or cheat? — a survey of 468 undergraduates examining how students' Perception of Academic Dishonesty (PAD) and their perceptions of the risks of ChatGPT are linked to reduced use frequency and intention to use the tool. Findings show a negative relationship between perceived risk and ChatGPT usage, with perceived risk mediating the PAD–usage link: students who perceive academic dishonesty as a serious problem are more aware of ChatGPT's risks and consequently use it less.

Ortiz-Bonnin & Blahopoulou (2025) address the tension between ChatGPT's educational benefits (Accessibility of information, personalized learning) and its risks (inaccurate information, facilitation of academic dishonesty such as cheating and plagiarism). Rather than asking whether students use AI, they ask why some students restrain their use — and find that perception of risk is the key gatekeeper.

Method

• Sample: 468 undergraduate students who completed an online survey.
• Constructs: Perception of Academic Dishonesty (PAD), perceived risk of ChatGPT use, self-reported use frequency, and intention to use ChatGPT in the future.
• Analysis: Regression examining direct effects of perceived risk on usage, plus mediation testing whether perceived risk transmits the effect of PAD on usage.

Key Findings

• Perceived risk → lower use. A negative and significant relationship exists between perceived risk of ChatGPT and both current use frequency and future intention to use it.
• Perceived risk mediates PAD. Perceived risk statistically mediates the relationship between Perception of Academic Dishonesty and ChatGPT usage patterns.
• First demonstration of the chain. This is the first study to show that students with high PAD present higher awareness of ChatGPT's risks, which is associated with lower frequency of use and lower intention to use.
• The ethical-versus-convenience tension. Students who take academic dishonesty seriously internalize the risks (accuracy, Privacy, integrity) and self-limit their AI use accordingly — rather than simply being deterred by institutional rules.

Implications

• For developers: Users must feel safe using AI tools. Improvements to data protection, cybersecurity, training-data transparency, and information accuracy (e.g. citing real references) reduce perceived risk and, in turn, promote more responsible adoption.
• For institutions and educators: Integrating AI responsibly means carefully considering ethical issues and students' perceptions of risk — not just prohibiting or mandating AI, but shaping the perceived-risk environment.
• For AI Anxiety And Stress: Perceived risk and the fear of committing academic dishonesty are a source of student anxiety around AI use; this study quantifies how that risk perception behaviorally suppresses use. It connects the integrity and anxiety dimensions of AI use.

Connected Concepts

• Academic Integrity
• Generative AI
• Higher Ed
• AI Detection
• Privacy
• Student Experience
• AI Anxiety And Stress
• Ethics
• AI Literacy
• Trust

Connected Articles

• AI Tools Academic Work Cheating 2026 — whether using AI tools for academic work counts as cheating
• Qu Wang Disclose Or Not GenAI 2026 — peer influence and psychological factors in disclosing GenAI use
• Moral Panic GenAI Classroom — moral panic and appropriate GenAI use
• Best Response Student AI Dialog 2026 — student reasoning about AI use
• AI Anxiety Strategic Regulation Writing 2026 — AI anxiety as a productive signal

Citation

Ortiz-Bonnin, S., & Blahopoulou, J. (2025). Chat or cheat? Academic dishonesty, risk perceptions, and ChatGPT usage in higher education students. Social Psychology of Education, 28, 113. https://doi.org/10.1007/s11218-025-10080-2