AI-ENABLED DIGITAL SELF-MANAGEMENT AND PSYCHOLOGICAL RESILIENCE IN HIGHER EDUCATION: A STRUCTURAL EQUATION MODELING INVESTIGATION

This study aimed to examine the extent to which digital self-management supported by artificial intelligence predicts psychological resilience among students at A'Sharqiyah University in the Sultanate of Oman, using structural equation modeling. The study adopted a quantitative correlational-predictive design and was applied to a stratified random sample of 471 male and female students (440 bachelor's, 31 master's). Selected and adapted dimensions from the SRL-O and SNAIL scales were used to measure digital self-management supported by artificial intelligence, while the BRS scale was used to measure psychological resilience. Instrument validity was verified through content validity and construct validity, and its reliability was verified using Cronbach's alpha and composite reliability. Data were analyzed using structural equation modeling via SPSS and AMOS. The results showed a positive and statistically significant correlational relationship between digital self-management supported by artificial intelligence and psychological resilience (r = 0.53, p < 0.001). The structural model also revealed a positive and statistically significant predictive path (β = 0.50, p < 0.001). The model explained 25% of the variance in psychological resilience (R² = 0.25) with a large effect size (f² = 0.33), and the fit indices indicated acceptable model fit (CFI = 0.93, RMSEA = 0.053). The findings indicate that digital self-management supported by artificial intelligence represents an important predictor of psychological resilience among university students. The study recommends integrating digital self-management skills and the critical and ethical use of artificial intelligence into training and counseling programs for higher education students.