ORIGINAL RESEARCH article
Front. Psychol.
Sec. Educational Psychology
The Mediating Role of Psychological Resilience in the Relationship Between Deep Learning Approach and Mathematical Creativity: Integrating Structural Equation Model and Network Analysis
Provisionally accepted
- 1South China Normal University, Guangzhou, China
- 2Beijing Normal University, Beijing, China
- 3Fujian Normal University, Fuzhou, China
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Background: Previous scholars have conducted a series of explorations on the relationship between learning approaches and mathematical creativity, but it remains unclear how deep learning approach predicts mathematical creativity. According to the componential theory of creativity, psychological resilience may be one of the mediating processes, but the network relationships among psychological resilience, learning approaches, and mathematical creativity are currently unclear. Methods: To clarify these relationships, we recruited 986 Chinese university students to complete questionnaire surveys, employing an integrated approach combining structural equation modeling and network analysis for the first time to reveal the mediating relationship and network relationships among learning approaches, psychological resilience, and mathematical creativity. Results: The study found that deep learning approach positively predicted mathematical creativity through the mediation of psychological resilience. In the network, node centrality demonstrates the strongest characteristics across three dimensions: strength, closeness, and expected influences, followed by psychological resilience, while deep learning methods exhibit the weakest characteristics. Therefore, compared to stimulating mathematical creativity at the motivational level, directly stimulating it from the volitional level like psychological resilience would be a more effective approach. Conclusions: The findings of this study contribute to helping educational practitioners understand the internal relationships among learning approaches, psychological resilience, and mathematical creativity.
Keywords: Mathematical creativity, psychological resilience, Learning approaches, deep learning, Network analysis
Received: 02 Sep 2025; Accepted: 12 Nov 2025.
Copyright: © 2025 Zeng, Zhuo, Lin, He, Liu, Liu and Yang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Wanlun Liu, 20230588@m.scnu.deu.cn
Xiantong Yang, xtyang93@foxmail.com
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