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.

翻译：高等教育学生在其学术工作中日益广泛地使用生成式人工智能。然而，现有制度实践尚未适应这一转变。通过对23名大学生的半结构化访谈，本研究考察了影响学生使用人工智能的环境与社会因素。研究发现，截止日期、考试周期和评分等制度性压力因素促使学生接触人工智能，即使他们认为这会损害自身学习。社会影响，特别是同伴微社群，无论官方人工智能政策如何，都确立了事实性的人工智能使用规范。校园范围内普遍存在的"人工智能羞耻感"常使人工智能使用转入地下。当前机构的人工智能政策被普遍认为笼统、不一致且令人困惑，导致常规性违规现象。此外，学生虽形成基于价值的自我调节策略，但环境压力在其意图与行为之间制造了鸿沟。我们的研究表明学生使用人工智能是一种情境化实践，并探讨了相关启示，以帮助教育机构、教师和系统工具设计者有效支持学生借助人工智能进行学习。