Prediction of students’ grades based on non-academic data

Abstract

This study examines the use of machine learning techniques to predict Math and Portuguese grades based on student demographics and survey data regarding their school experiences. Using a sample of 53 middle school students, an accuracy rate of 93% was achieved with a support vector machine model. This paper’s findings suggest that non-academic factors such as school climate and student engagement can have a significant impact on academic performance.