LEVERAGING ARTIFICIAL INTELLIGENCE FOR LEARNING ANALYTICS-DRIVEN PERSONALIZED LEARNING TO IMPROVE STUDENT ENGAGEMENT AND LEARNING OUTCOMES Dina Dahliana, Andri, Rahmat Ilahi, Akmal Yandi
STAI Solok Nan Indah
Abstract
The rapid advancement of Artificial Intelligence (AI) has created new opportunities for developing adaptive and personalized learning environments. However, the implementation of AI-based personalized learning in higher education still faces significant challenges, particularly in enhancing student engagement and learning outcomes. This study aims to examine the use of Artificial Intelligence supported by learning analytics in facilitating personalized learning and its impact on student engagement and academic performance. This research employs a quantitative approach with a quasi-experimental design involving university students in an online learning setting. Data were collected through student engagement questionnaires, learning outcome tests, and activity logs obtained from the Learning Management System (LMS). The data were analyzed using both descriptive and inferential statistical techniques. The findings indicate that the use of AI in personalized learning significantly improves student engagement, as reflected in increased active participation, learning time, and interaction with learning materials. Furthermore, a significant improvement in student learning outcomes was observed compared to conventional learning approaches. These results suggest that the integration of AI supported by learning analytics has strong potential as an innovative solution for promoting adaptive and sustainable learning in higher education. This study contributes to the development of technology-enhanced pedagogical models to support the achievement of the Sustainable Development Goals (SDGs) in education.
