This study employs network analysis to investigate differences in the core features of creativity between individuals using generative artificial intelligence (GenAI) and those who rely on individual effort without it. This nationwide study employed a stratified random sampling method across six universities, involving a total of 617 university students enrolled in art programs. The results indicate that the core features of creativity among students using GenAI involve generating unique solutions. Conversely, students who do not use GenAI exhibit core features such as flow experiences and active thinking. These differences can be explained from three aspects: the source of creativity, the methods of creativity, and the expressions of creativity. The findings of this study may provide insights for educators and policymakers by illuminating the potential benefits and drawbacks of GenAI in enhancing creativity among university students, thereby guiding the development of more effective educational tools and curricula.
Song et al. (Fri,) studied this question.