A Machine Learning Approach To Predict the Chances of Drooping out Students Due to COVID-19 in University Perspective Bangladesh

Abstract

The difficulties of COVID 19 have exposed humanity to some terrible truths. The pandemic's grip has severely harmed a number of industries, including education. Numerous days of school, college, and university closures caused the students to be disengaged from their academics. The amount of students who leave university for practical or financial reasons has become a major source of concern. We successfully investigate the university student dropout rate in our research. We look for the underlying causes of their dropout and work to provide a workable solution. We have gathered information from more than 400 undergraduate Bangladeshi students via an online survey. The most effective techniques for predicting dropout among Bangladeshi students were found after training and testing the dataset with a number of well-known algorithms, including SVM, Logistic Regression, Random Forest, Decision Tree, etc.