Prediction of Academic Performance During Adolescence Based on Socioeconomic, Psychological and Academic Factors

Abstract

Educational effectivity is paramount towards enhancing modernization. In our study we have taken into account various socioeconomic, psychological and academic factors to properly understand a student’s life during adolescence and their effect on academic performance. In order to build a predictive model, we have pre-processed the data using dimensionality reduction, data balancing, discretization, and normalization and then classified the data using different machine learning techniques like Artificial Neural Net, K-Nearest Neighbors and Support Vector Machine. Lastly we have discovered patterns throughout the dataset in relation with academic performance.