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Motivation to learn artificial intelligence applications and mental well-being in university students: A
Afaf Abdelah Othman1, Huda Saleh Abdul Rahman Al-Shimeimri2, Wafaa Mohamed Ibrahim El Bana3
1Department of Education and Psychology, Faculty of Education, Najran University, Saudi Arabia.
Background:
Artificial intelligence (AI) is increasingly integrated into higher education, while students' mental well-being has become a critical concern. The relationship between AI learning motivation and mental well-being was investigated.
Materials And Methods:
A cross-sectional correlational study was conducted among 195 students at the Faculty of Education, Najran University, Saudi Arabia, during the first semester of 2025-2026. Data were collected using the motivation to learn AI applications scale and a researchers-developed mental well-being scale (Cronbach's α = 0.792). Data were analyzed using Statistical Package for the Social Sciences version 26 with Pearson correlation, independent samples t-test, and linear regression (P ≤ 0.050).
Results:
Motivation to learn AI applications showed a significant positive correlation with mental well-being (r = 0.458, P < 0.001). Students with higher motivation reported significantly higher mental well-being (P < 0.001). Female students showed higher motivation (P = 0.007), while no significant gender differences were found in mental well-being (P = 0.421). Motivation significantly predicted mental well-being (β = 0.233, R 2 = 0.184, P < 0.001).
Conclusion:
Motivation to learn AI applications was positively associated with students' mental well-being and explained a modest proportion of its variance.