‘I Shouldn’t Be Saying This’: Library-Based Student Confessions about AI, Cheating, and Academic Integrity

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Authors: Sarah T. Zipf, Tiffany Alana Petricini, Steve Borrelli
Cited by: 0

Abstract

Students are cheating with AI. But the literature lacks students’ perceptions of cheating and AI. We interviewed thirty students about their AI use, cheating definitions and confessions, and why they turn to AI over other resources. Students’ responses show intention and effort matter when considering what constitutes as “cheating.” They worry for their intellectual development, feel uncertain and fearful, use guilt and fairness to regulate their behavior, and turn to technology instead of personal relationships. By centering the student perspective, academic libraries can develop responsible and responsive AI policies and safe exploration, reinforce human + AI relations, and educate and advocate around environmental concerns.

Fields of Study & Subjects

Academic integrity and plagiarism Artificial Intelligence in Education Library Science and Information Literacy

Publication details

Publication date
14 January 2026
Document type
Preprint