THE PREDICTIVE ABILIY OF ARTIFICIAL INTELLIGENCE AND CREATIVE SELF-EFFICACY IN LIFE SATISFACTION

This study aimed to determine the predictive ability of artificial intelligence use and creative self-efficacy in life satisfaction, as well as to reveal the level of life satisfaction, creative self-efficacy, and use of AI tools among students at Jerash Private University. Methodology and Tools: The study adopted a descriptive-analytical approach and was applied to a sample of (588) male and female students selected using convenience sampling. To collect data, three scales were developed and used: The Artificial Intelligence Use Scale (Barcelona & Cruz, 2025) and the Creative Self-Efficacy Scale developed by Karwowski et al. (Karwowski et al., 2018). The study used the Life Satisfaction Scale developed by Pavot and Diener (1993). The results showed that life satisfaction, creative self-efficacy, and the use of artificial intelligence tools were all at high levels. Stepwise multiple regression analysis revealed statistically significant predictive power for the two independent variables, with the model explaining 53% of the variance in life satisfaction. Creative self-efficacy was the variable with the strongest predictive power for life satisfaction, followed by artificial intelligence tools.