Factors influencing faculty decision-making on student use of generative AI in higher education

As generative AI (GenAI) becomes increasingly integrated into higher education, faculty encounter growing uncertainty and complexity in responding to student use of these tools. This study examines how faculty make sense of and navigate decisions about student use of GenAI in graduate-level courses, with particular attention to student learning processes. Drawing on sociotechnical systems theory and sensemaking theory, this study employed reflexive thematic analysis of open-ended interviews with 15 full-time faculty in graduate-level Library and Information Science (LIS) programs in the United States. The findings revealed the nuanced nature of faculty decision-making when navigating students’ AI use, highlighting how they engage in ongoing sensemaking as they interpret ambiguous situations, weigh competing pedagogical and professional priorities, and adapt to evolving academic expectations.