Redefining creativity differences for art students who use and those who do not use GenAI: evidence from network analysis

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.

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Publication Details

Journal
Humanities and Social Sciences Communications
Published
2026-03-13
DOI
https://doi.org/10.1057/s41599-026-06897-7
Primary Topic
Creativity in Education and Neuroscience
Type
article
Field-Weighted Citation Impact
0.00
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article

Redefining creativity differences for art students who use and those who do not use GenAI: evidence from network analysis

Liang Zhang, Lin-Ying Li, Xin-Chun Nie, Wei-Mun Chin et al.
Humanities and Social Sciences Communications
Creativity in Education and Neuroscience
article

Redefining creativity differences for art students who use and those who do not use GenAI: evidence from network analysis

Liang Zhang, Lin-Ying Li, Xin-Chun Nie, Wei-Mun Chin, Pu Song, Yu-Jia Yang, Mengmeng Zhong
article en

Abstract

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.

Humanities and Social Sciences Communications
Jiangxi University of Water Resources and Electric Power (CN), Southwest University (CN), Guangxi University of Science and Technology (CN), Yili Normal University (CN), Liuzhou Maternal and Child Health Hospital (CN), Luoyang Normal University (CN), Education Department of Jiangxi Province (CN), Srinakharinwirot University (TH), SEGi University (MY)
Reduced inequalities
Openalex Percentile: Top 28%
Creativity in Education and Neuroscience
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