Recommendation of Data Mining Technique in Higher Education Prof. Priya Thakare Guide

In this paper we will discuss about the problem that are faced by higher education institutions. One of the biggest challenges that higher education faces today is predicting the right path of students. Institutions would like to know, which students will enroll in which course, and which students will need more assistance in particular subject and what efforts should be taken for weak students. Also some time management needs more information about student like their overall result, interest in co-curricular and extra-curricular activities and about the success of new offered courses. One way to effectively address the challenges for improving the quality of students and education is to provide new knowledge related to the educational processes and entities to the system. This knowledge can be extracted from historical data that reside in the educational organization's databases using the techniques of data mining technology. If data mining techniques such as clustering, decision tree, association, classification and prediction can be applied to higher education processes, it can definitely help improve students' overall performance, their life cycle management, selection of course and predict their dropout rate.