"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
arXiv:2602.17720v1 Announce Type: cross Abstract: Higher education students are increasingly using generative AI in their academic work. However, existing institutional practices have not yet adapted to this shift. Through semi-structured interviews with 23 college students, our study examines the environmental and social factors that influence students' use of AI. 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. Social influences, particularly peer micro-communities, establish de-facto AI norms regardless of official AI policies. Campus-wide ``AI shame'' is prevalent, often pushing AI use underground. Current institutional AI policies are perceived as generic, inconsistent, and confusing, resulting in routine noncompliance. Additionally, students develop value-based self-regulation strategies, but environmental pressures create a gap between students' intention
arXiv:2602.17720v1 Announce Type: cross Abstract: Higher education students are increasingly using generative AI in their academic work. However, existing institutional practices have not yet adapted to this shift. Through semi-structured interviews with 23 college students, our study examines the environmental and social factors that influence students' use of AI. 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. Social influences, particularly peer micro-communities, establish de-facto AI norms regardless of official AI policies. Campus-wide ``AI shame'' is prevalent, often pushing AI use underground. Current institutional AI policies are perceived as generic, inconsistent, and confusing, resulting in routine noncompliance. Additionally, students develop value-based self-regulation strategies, but environmental pressures create a gap between students' intentions and their behaviors. Our findings show student AI use to be a situated practice, and we discuss implications for institutions, instructors, and system tool designers to effectively support student learning with AI.
Executive Summary
This article presents a timely and thought-provoking study on the intersection of generative AI and higher education. Through semi-structured interviews with 23 college students, the authors shed light on the environmental and social factors influencing AI use in academic settings. Key findings include institutional pressure, social influences, and campus-wide 'AI shame' contributing to a culture of noncompliance with existing AI policies. The study highlights the need for institutions, instructors, and system tool designers to adapt and support student learning with AI. The research underscores the importance of understanding AI use as a situated practice, rather than a binary issue of 'use' or 'non-use'.
Key Points
- ▸ Institutional pressure factors drive students to use AI, even when they perceive it as undermining learning.
- ▸ Social influences, particularly peer micro-communities, establish AI norms despite official policies.
- ▸ Campus-wide 'AI shame' contributes to a culture of noncompliance with AI policies.
Merits
Strength
The study's use of semi-structured interviews provides rich, qualitative data on students' experiences with AI in higher education.
Strength
The research highlights the importance of understanding AI use as a situated practice, rather than a binary issue of 'use' or 'non-use'.
Demerits
Limitation
The study's sample size of 23 students may not be representative of the broader higher education population.
Limitation
The research focuses on a specific institution and may not be generalizable to other educational settings.
Expert Commentary
This study provides a nuanced and contextualized understanding of AI use in higher education, one that challenges simplistic notions of 'use' or 'non-use.' The research highlights the need for institutions to move beyond generic policies and instead develop targeted support systems to help students navigate the complexities of AI use. By recognizing AI use as a situated practice, educators can begin to develop more effective strategies for supporting student learning in this rapidly evolving academic environment.
Recommendations
- ✓ Future research should investigate the impact of institutional AI policies on students' AI use and attitudes towards AI.
- ✓ Educational institutions should establish clear guidelines for AI use and provide students with regular opportunities for reflective practice and self-regulation.