Predicting student’s behavior in education using J48 algorithm analysis tools in WEKA environment

DOI: 10.5176/978-981-08-6308-1_51

Authors: Daya Gupta, Rajni Jindal, Vaibhav Verma, Dilpreet Singh Kohli, Shashi Kant Sharma

Abstract:

In the given case study we are proposing a scheme of student evaluation that can help the colleges (or other related organizations) to judge the candidate if he/she matches with the offered program .The student’s satisfaction level for that program can be estimated on the basis of his/her general attributes and program’s attributes. The proposal is to construct a decision tree on the bases of historical data through which the general attributes of the student and the particular program can be mapped to the satisfaction level. Construction and refinement of decision tree makes use of J48 Algorithm. Predictions regarding student dropout, transfer or persist can be made using the estimated satisfaction level.