How Generative Artificial Intelligence (GAI) reshapes students’ creativity in higher education: A chain path modeling Study from “Exploration–Exploitation” to “Co-Creation–Reflection”
- 1Institute of Creative Arts and Design, UCSI University, Kuala Lumpur, Malaysia
- 2Faculty of Social Sciences and Liberal Arts, UCSI University, Kuala Lumpur, Malaysia
Abstract
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.
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BibTeX
@article{xu2026generative,
title = {{How Generative Artificial Intelligence (GAI) reshapes students’ creativity in higher education: A chain path modeling Study from “Exploration–Exploitation” to “Co-Creation–Reflection”}},
author = {Jie Xu and Yixuan Zeng},
journal = {PLOS One},
year = {2026},
month = sep,
doi = {10.1371/journal.pone.0358186},
url = {https://doi.org/10.1371/journal.pone.0358186},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - How Generative Artificial Intelligence (GAI) reshapes students’ creativity in higher education: A chain path modeling Study from “Exploration–Exploitation” to “Co-Creation–Reflection”
AU - Jie Xu
AU - Yixuan Zeng
PY - 2026
DA - 2026/09/24
JO - PLOS One
DO - 10.1371/journal.pone.0358186
UR - https://doi.org/10.1371/journal.pone.0358186
AB - 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.
SN - 1932-6203
ER -