"Stuck in a Spiral": Shame and Guilt as Social Regulators of AI Use in Computing Education
- URL: http://arxiv.org/abs/2606.14920v1
- Date: Fri, 12 Jun 2026 19:55:52 GMT
- Title: "Stuck in a Spiral": Shame and Guilt as Social Regulators of AI Use in Computing Education
- Abstract summary: We present an interview study with 19 computing students through a functionalist perspective of shame and guilt.<n>Students described shaming themselves, their peers, and even faculty for using AI.<n>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.
- Score: 0.20524609401792393
- License: http://creativecommons.org/licenses/by-sa/4.0/
- 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.
Related papers
- When Should AI Read the Room? Public Perceptions of Social Intelligence in AI Agents [61.06747336710885]
Social-AI agents are increasingly deployed in everyday settings.<n>Public perceptions of social intelligence in AI agents and the acceptability of these agents remain largely understudied.<n>We present a mixed-methods survey of adults in the United States.
arXiv Detail & Related papers (2026-05-28T13:49:47Z) - Sycophantic AI makes human interaction feel more effortful and less satisfying over time [41.009652609144794]
We show that sycophantic AI immediately delivers the emotional and esteem support users typically associate with close friends and family.<n>When given a choice among AI response styles, a majority preferred sycophantic AI -- not for the quality of its advice, but because it made them feel most understood.
arXiv Detail & Related papers (2026-05-08T15:50:06Z) - Filipino Students' Willingness to Use AI for Mental Health Support: A Path Analysis of Behavioral, Emotional, and Contextual Factors [0.0]
This study examined how behavioral, emotional, and contextual factors influence Filipino students' willingness to use artificial intelligence (AI) for mental health support.<n>Students who used AI tools regularly felt more confident and open to relying on them for emotional support.<n>The study recommends AI literacy programs, empathic design, and ethical policies that support responsible and culturally sensitive use of AI for student mental health care.
arXiv Detail & Related papers (2026-03-30T03:35:06Z) - What Drives Students' Use of AI Chatbots? Technology Acceptance in Conversational AI [0.17188280334580194]
We examine how perceived usefulness and perceived ease of use relate to students' behavioral intention to use conversational AI.<n>We find perceived usefulness remains the strongest predictor of students' intention to use conversational AI.<n>Trust and subjective norms significantly influence perceptions of usefulness, while perceived enjoyment exerts both a direct and indirect effect on usage intentions.
arXiv Detail & Related papers (2026-02-24T05:00:41Z) - "Everyone's using it, but no one is allowed to talk about it": College Students' Experiences Navigating the Higher Education Environment in a Generative AI World [13.109430455513882]
Findings show that institutional pressure factors like deadlines, exam cycles, and grading lead students to engage with AI even when they think it undermines their learning.<n>Current institutional AI policies are perceived as generic, inconsistent, and confusing, resulting in routine noncompliance.<n>Students develop value-based self-regulation strategies, but environmental pressures create a gap between students' intentions and their behaviors.
arXiv Detail & Related papers (2026-02-17T19:00:28Z) - "All Roads Lead to ChatGPT": How Generative AI is Eroding Social Interactions and Student Learning Communities [0.4188114563181615]
We investigate the potential impacts of generative AI on social interactions, peer learning, and classroom dynamics.<n>Our findings suggest that help-seeking requests are now often mediated by generative AI.<n>Students reported feeling increasingly isolated and demotivated as the social support systems they rely on begin to break.
arXiv Detail & Related papers (2025-04-14T00:40:58Z) - Let people fail! Exploring the influence of explainable virtual and robotic agents in learning-by-doing tasks [45.23431596135002]
This study compares the effects of classic vs. partner-aware explanations on human behavior and performance during a learning-by-doing task.
Results indicated that partner-aware explanations influenced participants differently based on the type of artificial agents involved.
arXiv Detail & Related papers (2024-11-15T13:22:04Z) - I would love this to be like an assistant, not the teacher: a voice of the customer perspective of what distance learning students want from an Artificial Intelligence Digital Assistant [0.0]
This study examined the perceptions of ten online and distance learning students regarding the design of a hypothetical AI Digital Assistant (AIDA)
All participants agreed on the usefulness of such an AI tool while studying and reported benefits from using it for real-time assistance and query resolution, support for academic tasks, personalisation and accessibility, together with emotional and social support.
Students' concerns related to the ethical and social implications of implementing AIDA, data privacy and data use, operational challenges, academic integrity and misuse, and the future of education.
arXiv Detail & Related papers (2024-02-16T08:10:41Z) - The Good, The Bad, and Why: Unveiling Emotions in Generative AI [73.94035652867618]
We show that EmotionPrompt can boost the performance of AI models while EmotionAttack can hinder it.
EmotionDecode reveals that AI models can comprehend emotional stimuli akin to the mechanism of dopamine in the human brain.
arXiv Detail & Related papers (2023-12-18T11:19:45Z) - Exploring User Perspectives on ChatGPT: Applications, Perceptions, and
Implications for AI-Integrated Education [40.38809129759498]
ChatGPT is most commonly used in the domains of higher education, K-12 education, and practical skills training.
On one hand, some users view it as a transformative tool capable of amplifying student self-efficacy and learning motivation.
On the other hand, there is a degree of apprehension among concerned users.
arXiv Detail & Related papers (2023-05-22T15:13:14Z) - Seamful XAI: Operationalizing Seamful Design in Explainable AI [59.89011292395202]
Mistakes in AI systems are inevitable, arising from both technical limitations and sociotechnical gaps.
We propose that seamful design can foster AI explainability by revealing sociotechnical and infrastructural mismatches.
We explore this process with 43 AI practitioners and real end-users.
arXiv Detail & Related papers (2022-11-12T21:54:05Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.