How Generative Artificial Intelligence (GAI) reshapes students’ creativity in higher education: A chain path modeling Study from “Exploration–Exploitation” to “Co-Creation–Reflection”

With the widespread integration of Generative Artificial Intelligence (GAI) into higher education, its relationship with students’ creativity has become a growing focus of scholarly inquiry. Drawing on data from 424 survey responses and in-depth interviews with eight students, this study constructs and examines a chain path model of Exploration–Exploitation–Co-Creation–Reflection to investigate how GAI-assisted learning processes are associated with students’ creativity. Quantitative analyses indicate that exploratory and exploitative behaviors are positively associated with creativity, and these associations are observed alongside perceived cognitive stimulation. Furthermore, co-creation and reflection are significantly associated with flow experience and creative self-efficacy, which are related to students’ creative performance. The qualitative findings complement the quantitative results by showing that students’ engagement in exploration, knowledge utilization, collaborative co-creation, and reflection during GAI-assisted learning is accompanied by cognitive inspiration and psychological engagement. Overall, this study provides insight into how GAI-assisted learning processes may be associated with creativity development in higher education through the interplay of behavioral, cognitive, and psychological mechanisms, offering implications for educational practice and theoretical advancement.