Student Performance Assessment and Prediction based on Machine Learning

Abstract

Student Performance Analysis System is an emerging field and is very crucial to schools and universities in helping their students and professors. Most of the pre-existing methods are based only on past academic performance of students. This paper is aimed at developing prototypes for prediction of students performance on the basis of assessing the amount of grades scored from their psychographic and standard of living attributes. It uses various deep learning and machine learning techniques to predict the performance of students, and basic exploratory data analysis to derive various correlations of students performance with psychographic attributes.