Transforming Education With Predictive Analytics: A Data-Driven Approach to Student Achievement

Abstract

In this fast-changing educational landscape of today, data science and predictive analytics are tools critical to creating student success and transforming educational systems. This chapter will further explore how predictive analytics can be utilized to anticipate and improve student outcomes. It also includes methodologies in collecting and analyzing student data, algorithms predicting their academic performance, and insights for early interventions and adapted support by educators and administrators. The predictive model, based on historical and real-time data, can predict the at-risk or chance of succeeding in student and develop learning paths for each one. The chapter also tackles data privacy issues, ethical implications, and the AI technology integration processes in schools. This chapter explains how predictive analytics the power can have to offer a better personalized, fair, and effective learning environment that would ensure improved student success and retention.