“It’s OK Because…”: Students’ Rationalization of AI Use in Academic Writing

Abstract

Generative AI challenges academic integrity not only by enabling students to delegate substantial portions of their academic work, but also by blurring the ethical boundaries between acceptable assistance and misconduct. Drawing on semi-structured interviews (n=20), AI chat logs, and course documents (syllabi, submitted assignments), we investigated how students themselves make moral sense of AI use in academic writing. Our analysis results in the following main novel findings: First, students use at least 23 distinct rationalizations to justify AI use, such as that copying AI-generated text is victimless; that any AI text reflecting their own beliefs or their own style is their own writing; or that they are learning more by using AI. We present a taxonomy of these rationalizations, comprising six core categories. Second, students' rationalizations occur in both an ad hoc and post hoc manner and are sometimes lacking in normative grounding. These findings suggest that AI presents a slippery slope that students conceptually slide down, landing far outside the pedagogical goals and expectations of instructors. We discuss implications for educational design and AI policy.