Factors Affecting Student’s Academic Performance
Abstract
The educational system measures students’ performance using varied assessment methods such as quizzes, tests, examinations and assignments. Academic performance along with skill sets is strongly linked with positive outcomes upon completion of studies in the ever-demanding job market or pursuance of higher studies. Various factors can affect students’ academic performance such as mental issues, working status, time spent on gadgets and study duration. This research studies the role of various factors in order to understand their role in the student’s academic performance. Furthermore, various machine learning algorithms are implemented for the prediction process for a student’s performance range. The results present that various internal and external pressure on a student is a major contributor to the state of academic performance among other factors discussed in this paper. Light Gradient Boosting Machine performs the best compared to other algorithms in the multi-class classification problem with an overall accuracy and F1-score of 0.87 and 0.86, respectively.
