Academic Integrity and Emotional Responses to Inappropriate LLM Use in Software Engineering Education
For educators and policymakers in software engineering education, this study reveals that students often feel indifferent about inappropriate LLM use, highlighting a gap between awareness of academic integrity risks and emotional engagement.
This study surveyed 116 undergraduate software engineering students about their emotional responses to using LLMs in ways they considered academically inappropriate. The most common emotional response was indifference, even among students aware of risks to learning and academic standing, while guilt, anxiety, relief, and satisfaction were also reported depending on context.
Academic integrity in higher education is increasingly shaped by complex socio-technical environments marked by automated tools, evolving institutional practices, and heightened performance pressures. Within this context, large language models (LLMs) are becoming prevalent in software engineering education, further blurring boundaries around acceptable assistance and authorship. This study investigates how software engineering students describe their emotional experiences after using LLMs in ways they perceive as academically inappropriate. We conducted a cross-sectional survey with 116 undergraduate students. Results show emotionally heterogeneous responses. Indifference was most frequent, including among students who recognized risks to learning and academic standing. Guilt and anxiety were reported in relation to moral discomfort and concern about penalties. Relief and satisfaction were evident primarily in deadline-driven contexts and situations of unclear guidance.