Academic Integrity and Students’ Ethical Use of ChatGPT in Higher Education

Aim/Purpose To examine how ethical awareness, cognitive appraisal (trust and perceived usefulness), digital competence, academic performance, and gender influence university students’ ethical use of ChatGPT and academic integrity. Background This study explores how university students’ use of ChatGPT influences academic integrity in higher education. It responds to emerging integrity challenges posed by generative AI by empirically testing a model that links transparency, plagiarism avoidance, bias awareness, and responsible use to academic integrity outcomes across universities in the Gulf region. Methodology PLS-SEM analysis of survey data from 318 students across five Gulf-region universities; tests direct effects of four ethical variables, mediation by trust in AI and perceived usefulness, and moderation by digital literacy and CGPA. Contribution This study provides empirical evidence that core ethical-use dimensions significantly enhance academic integrity; clarifies the mediating roles of trust/usefulness and the moderating roles of digital literacy/CGPA; and documents gender and discipline differences in usage. Findings All four ethical variables positively and significantly predict academic integrity: Trust in AI and perceived usefulness act as partial mediators. Digital literacy and CGPA significantly moderate several relationships. High-performing and senior students report more frequent and effective use of ChatGPT; gender and discipline differences are evident. Recommendations for Practitioners Embed digital literacy and ethical-AI training (transparency, anti-plagiarism, bias awareness, responsible use) into curricula; implement inclusive AI policies; and guide trust calibration and verification workflows to support responsible use. Recommendations for Researchers Extend the model across countries and disciplines; examine longitudinal effects; test additional mediators (e.g., AI anxiety, institutional policy clarity) and moderators (e.g., year of study, assessment type); compare alternative SEM and causal designs. Impact on Society Promotes responsible AI adoption that safeguards academic ethics, supports equitable student outcomes, and informs policy for trustworthy AI use in higher education ecosystems. Future Research Conduct multi-institutional replications, experimental interventions on ethics/digital literacy training, and studies of assessment design that balance AI use with integrity (e.g., oral/ authentic assessments).