"Stuck in a Spiral": Shame and Guilt as Social Regulators of AI Use in Computing Education

2026-06-12

AI Summary

This study investigates how shame and guilt modulate computer science students’ use of AI tools and their associated social interaction dynamics. Grounded in functionalist emotion theory, the research draws on semi-structured interviews and qualitative analysis with 19 students, marking the first integration of shame and guilt into the discourse on AI use in educational contexts. It reveals how these emotions shape the visibility of AI usage, trigger concealment behaviors and selective disclosure, and generate tension with students’ professional identities. The study introduces the concept of a “spiral dilemma” to capture the moral distress and diminished agency students experience through sustained AI engagement, often interpreting their behavior through metaphors of addiction. These findings underscore the necessity of incorporating socio-emotional dimensions into AI education policies and advocate for fostering open dialogue and responsible use.

Abstract

While prior work has examined patterns of adoption and social norms around AI use, less is known about how emotional factors, such as shame and guilt, shape students use of AI tools. We present an interview study with 19 computing students through a functionalist perspective of shame and guilt, which interprets emotions as social signals that regulate behavior. Our findings show that these emotions regulate when and how students make their use visible, as they engage in hiding behaviors and selective disclosure. Students described shaming themselves, their peers, and even faculty for using AI. Shame and guilt often coexist with continued AI use, creating cycles of reduced agency and moral tension rather than promoting behavior change. Students described feeling tensions between their AI use and their identities as competent, hardworking, or ethical computing students. Students also used language and metaphors of addiction to describe their experiences. These results highlight the need to consider the socio-emotional aspects of AI use, which may be influenced by how AI policies are implemented and enforced. We discuss classroom practices that can foster healthy, open discussion and support responsible AI use.

Problem

• shame
• guilt
• AI use
• computing education
• social regulation

Innovation

• shame
• guilt
• AI use
• computing education
• emotional regulation