AI Dependence and Academic Motivation as Predictors of Academic Self-Efficacy Among Undergraduate Students
Abstract
Academic self-efficacy is an important psychological construct in higher education, particularly as artificial intelligence (AI) becomes increasingly integrated into students’ academic experiences. This study employed a cross-sectional quantitative design to examine the levels and relationships of AI dependence, academic motivation, and academic self-efficacy, and determined whether AI dependence and academic motivation significantly predicted academic self-efficacy among undergraduate students. The sample included 228 undergraduate students from three private universities in Cebu, Philippines. Data were collected electronically using the Artificial Intelligence Dependence Questionnaire (AIDQ), Academic Motivation Scale-College Version (AMS-C 28), and General Academic Self-efficacy Scale (GASE). Descriptive statistics, Pearson product-moment correlation, and multiple linear regression were conducted to analyze the data. Results indicated moderate levels of AI dependence (M = 2.5, SD = 0.601), moderate academic motivation (M = 3.5, SD = 0.401), and high academic self-efficacy (M = 3.8, SD = 0.646). AI dependence was negatively associated with academic self-efficacy (r = −.220, p < .001), whereas academic motivation was positively associated with academic self-efficacy (r = .377, p < .001). Multiple regression analysis showed that both AI dependence (β = −.169, p = .006) and academic motivation (β = .353, p < .001) significantly predicted academic self-efficacy, collectively explaining 17% of its variance (R² = .170, p < .001). Overall, the results of the study underscore the relevance of both students’ motivational resources and their reliance on AI in understanding academic self-efficacy in higher education. These findings highlight the importance of strengthening academic motivation and promoting balanced, responsible AI use to support students’ confidence in independently accomplishing academic tasks.