Model for Prediction of Dropout Student Using ID3 Decision Tree Algorithm

The objectives of this research work is to identify relevant attribute from socio-demographic, academic and institutional data of first year students from undergraduate at the University and design a prototype machine learning tool which can automatically recognize whether the student continue their study or drop their study using classification technique based on decision tree. For powerful decision making tool different parameter are need to be considered such as socio-demographic data, parental attitude and institutional factors. The generated knowledge will be quite useful for tutor and management of university to develop policies and strategies related to increase the enrolment rate in University and to take precautionary and advisory measures and thereby reduce student dropout. It can also use to find the reasons and relevant factors that affect the dropout students.