A Predictive Model for Calculating Student GPA Using Machine Learning Algorithms

This study focuses on analyzing students' educational performance and their behavior in relation to their grade point average (GPA), using a dataset that includes socio-behavioral and educational attributes. Machine learning techniques were applied to predict GPA and to develop a predictive model. Exploratory data analysis identified key correlations, and various algorithms were used for GPA prediction. The aim of this study is to assist policymakers in designing strategies to enhance educational outcomes and support student development. It highlights the importance for universities to identify students at risk of low GPA and to improve future predictions to help boost student performance.