GENERATIVE AI TOOL USAGE AND ACADEMIC PERFORMANCE: THE MEDIATING ROLE OF STUDENT MOTIVATION IN HIGHER EDUCATION

Abstract

The swift development of Generative Artificial Intelligence (AI) tools has reshaped how students learn in higher education institutions, empowering them with advanced cognitive assistance for learning activities. This study investigates the relationship between academic performance and the use of Generative AI tools, mediated by academic motivation among students at the university level. The study used a quantitative cross-sectional research design with 384 students being sampled, and a structured questionnaire was used for data collection. Data were analyzed with Hayes' PROCESS Macro (Model 4) to test direct and indirect relationships between variables. The results showed a positive relationship between the use of Generative AI tools and academic achievement and motivation. Moreover, the study showed that students' motivation had a significant impact on their academic performance. The results of the mediation analysis showed that student motivation partially mediated the relationship between Generative AI tool usage and academic performance, indicating that the tools have a direct effect as well as having an indirect pathway via student motivation. The study concludes that Generative AI tools act as cognitive and motivational enhancers in higher education environments. The effectiveness was maximized if they are used to support not to replace independent learning, but to strengthen the intrinsic motivation of students. The results add to an increasing body of research examining the role of AI in education and provide actionable insights for teachers and leaders on how to implement AI tools effectively within educational settings.