The Role of Predictive Analytics in Personalizing Education

Abstract

Predictive analytics is a crucial tool in changing teaching and learning practices in the ever-changing field of educational technology. This study examines the dynamic function of predictive analytics in customizing education, with a specific emphasis on its ability to adapt learning paths to improve individual student achievement. The study examines how predictive models might identify distinct learning patterns and demands by assessing many data sources, such as academic achievement, learning habits, and engagement indicators. It showcases the capabilities of these analytics in generating adaptive learning experiences, thereby providing a more focused approach to teaching. This article investigates how predictive analytics facilitates the early detection of educational hazards, allowing for timely interventions to support students who are at danger of academic underperformance or dropping out.