AI Based Learning Systems and Academic Performance: Mediating Role of Cognitive Engagement

Abstract

Artificial Intelligence (AI) has emerged as a transformative force in education, providing personalized learning experiences, adaptive assessments, intelligent tutoring systems, and real time feedback mechanisms. The growing integration of AI based learning systems in educational institutions has raised significant interest among researchers regarding their impact on students' academic performance. While previous studies have established a positive relationship between educational technologies and learning outcomes, limited attention has been paid to the psychological mechanisms through which AI based learning systems influence academic achievement. Therefore, this study investigates the mediating role of cognitive engagement in the relationship between AI based learning systems and academic performance among university students.

Drawing upon Constructivist Learning Theory and Technology Acceptance Theory, the study proposes that AI based learning systems facilitate meaningful learning experiences by enhancing students' cognitive engagement, which subsequently improves academic performance. A quantitative research design was adopted using a cross sectional survey approach. Data were collected from university students who actively utilized AI supported educational platforms. SmartPLS was employed to evaluate the measurement model and structural relationships among the constructs. The findings indicate that AI based learning systems significantly influence cognitive engagement and academic performance. Furthermore, cognitive engagement was found to partially mediate the relationship between AI based learning systems and academic performance, suggesting that students who actively invest cognitive effort in learning activities achieve superior academic outcomes.

The study contributes to the emerging literature on AI enabled education by highlighting the importance of cognitive engagement as a critical mechanism linking technology adoption to educational success. The findings provide practical implications for educational institutions, policymakers, and technology developers seeking to maximize the effectiveness of AI driven learning environments. Future research may explore additional mediating and moderating variables such as self efficacy, motivation, and digital literacy across diverse educational contexts.