Predicting Students Attrition using Data Mining
Journal Title: International Journal of Computer Science & Engineering Technology - Year 2013, Vol 4, Issue 10
Abstract
Student attrition has become one of the most important measures of success for higher education institutions. It is an important issue for all institutions due to the potential negative impact on the image of the university and the institution and is great hindrance on the career path of the dropouts. A system to identify students that have high risk of attrition using Decision tree is being described in this paper. The paper also focuses on reasons on attrition of students and steps need to be taken to improve student’s retention. The result of analysis will assist the institutions in predicting the set of students who can leave the institution after confirming admission and steps that need to be taken to improve student’s retention.
Authors and Affiliations
Rakesh Kumar Arora , Dr. Dharmendra Badal
Keywords
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