ORIGINAL RESEARCH article
Front. Educ.
Sec. Mental Health and Wellbeing in Education
Volume 10 - 2025 | doi: 10.3389/feduc.2025.1688902
Balancing Generative AI Integration and Faculty Well-Being: Evidence from Chinese Higher Education
Provisionally accepted
- Education, Henan University, Kaifeng, China
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The rapid expansion of generative artificial intelligence (AI) tools such as ChatGPT and DeepSeek is increasingly influencing higher education, yet their implications for faculty well-being remain underexplored. This study employed a cross-sectional survey design with quantitative analysis using covariance-based structural equation modeling (CB-SEM) and fuzzy-set qualitative comparative analysis (fsQCA). A total of 711 faculty members from Chinese universities participated between and February 18 and 22, 2025, reflecting the local context where DeepSeek is widely accessible and culturally adapted compared to tools such as ChatGPT. Results show that perceived usefulness (p = 0.004), ease of use (p < 0.001), and enjoyment (p < 0.001) significantly predict adoption. In turn, adoption is associated with reduced stress (p < 0.01) and greater happiness (p < 0.001), although its effect on faculty energy was statistically non-significant (p = 0.129). These findings demonstrate both the benefits and limits of AI integration, improving efficiency and happiness but offering less support for energy-related outcomes. Theoretically, this study extends TAM by incorporating hedonic motivation and by combining SEM and fsQCA to capture both linear and configurational adoption pathways. Practically, the results suggest that universities should prioritize structured training programs to build confidence, workload management policies to mitigate stress, and usability improvements to enhance enjoyment. Such strategies can balance innovation with faculty well-being, ensuring that the integration of AI tools like DeepSeek supports sustainable teaching environments.
Keywords: artificial intelligence, Generative AI, deepseek, Technology acceptance model, faculty well-being, Structural Equation Modeling, fsQCA, higher education
Received: 19 Aug 2025; Accepted: 06 Oct 2025.
Copyright: © 2025 Lan, Nneli, Song, Xiao and Jiang. 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: Guoshuai Lan, cqdxlgs@163.com
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