Adapting academic integrity policies to incorporate generative AI tools
Date
2025
Authors
Sehgal, Manish
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Abstract
The rapid rise of Generative AI (GAI) presents both challenges and opportunities for higher education institutions seeking to uphold academic integrity while embracing technological innovation. This dissertation investigates how top U.S. universities are adapting their academic integrity policies and practices in response to GAI. Through document analysis of 20 institutional policies, surveys of students, faculty, and policy makers, and an autoethnographic reflection on the researcher’s use of ChatGPT, the study provides a multi-faceted view of institutional responses to GAI. The findings reveal alignment across institutions on core ethical principles, but wide variation in policy clarity, specificity, and educational integration. Survey data highlight tensions between stakeholder groups, with students eager to adopt GAI tools but seeking clearer guidance, faculty expressing cautious openness and the need for support, and policy makers prioritizing risk management. The autoethnographic reflection offers insight into the practical and ethical complexities of using GAI in academic leadership. The study concludes that successful integration of GAI requires a holistic approach that combines adaptable policy frameworks with educational initiatives, dialogue, and ongoing review. It calls for higher education institutions to engage in collaborative stewardship of GAI technologies to ensure their responsible and inclusive use.
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Keywords
Academic Integrity, GAI, Artificial Intelligence, Educational Policy