Enhancement of educational system using data mining techniques
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 4
Abstract
In this paper we will discuss about the problem that are faced by education institutions. One of the biggest challenges that 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 it will help to predict the electives of the students and predict the dropout rate. Also some time management needs more information about student like their overall result, interest in co-curricular and about the success ofnew 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.
Authors and Affiliations
Prof. Priya Thakarei, Ajinkya Kunjir, Poonam Pardeshi, Shrinik Dosh, Karan Naik
Keywords
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