The Impact of AI-Supported Digital Learning on Academic Performance: Examining The Moderating Effect 0f Digital Self-Efficacy among University Students

Abstract

This study examined the impact of AI-supported digital learning on academic performance among university students, with particular emphasis on the moderating role of digital self-efficacy. The study was significant because the increasing integration of Artificial Intelligence into higher education has created new opportunities for personalized, accessible, and technology-enhanced learning, while students’ ability and confidence to use digital technologies may influence the extent to which they benefit from these opportunities. A quantitative, cross-sectional research design was adopted, and data were collected from 371 university students in Punjab and Sindh, Pakistan, through a structured questionnaire administered using Google Forms. The data were analyzed by using techniques of descriptive statistics, reliability analysis, Pearson correlation, regression analysis, and moderation analysis. The findings demonstrated that AI-supported digital learning was positively associated with academic performance and significantly contributed to explaining differences in students’ academic outcomes. Digital self-efficacy was also positively related to academic performance, indicating that students with greater confidence in using digital technologies tended to achieve better academic outcomes. Furthermore, the findings showed that digital self-efficacy significantly strengthened the relationship between AI-supported digital learning and academic performance, suggesting that students with higher digital self-efficacy were better positioned to benefit from AI-supported learning environments. The study concludes that effective integration of AI into higher education should be accompanied by the development of students’ digital confidence, competence, and responsible AI-use skills. The findings provide useful implications for universities, educators, and policymakers seeking to maximize the educational benefits of AI-supported learning.