Prediction of Student Attrition Using Machine Learning

Abstract

Student attrition is one of the most important problems for any school, being it private or public. In public education, a high attrition rate reflects poorly in the school, as it is wasting public taxes on students that do not finish their majors. In private education, it means the school revenue decreases considerably. Much work has been done on predicting churn rates in the Telecommunication industry, in this work we use similar techniques to predict churn rates in education. We explore the data extensively and see the possible correlations between attrition and variables like entrance examination, place where the students are from and grades up to the point of abandonment of the major.