Exploring Factors Influencing Faculty Well-Being in GenAI-Enhanced Higher Education Using Machine Learning

• In Event: Too much of a good thing? How AI is (re)shaping academic careers in higher education

Abstract

This study investigates the key factors influencing university faculty’s well-being in the context of Generative Artificial Intelligence (GenAI) adoption in higher education. Drawing on established psychological and educational frameworks, machine learning approaches — particularly Random Forest with SHAP analysis — were employed to analyze survey data from 502 faculty members in China. Results highlight AI use effectiveness, human–AI collaboration, AI literacy, social support, and age as the most significant predictors of GenAI-related well-being. The findings offer both theoretical insight and practical implications for faculty development, institutional policy, and ethical AI integration, aiming to support a more human-centered digital transformation in academia.

Authors

• Jiarui Zhao, Shandong University

• Jinyu Wang, National Academy of Education Administration

• Weitong Liu, Shandong University