A REVIEW OF DM APPROACHES FOR PREDICTING STUDENT’S PERFORMANCE
Ankita Singh Tomar
Research scholar, MITS, Gwalior, India , IN
Rajendra Kumar Gupta
Research scholar, MITS, Gwalior, India , IN
Khushboo Agarwal
Research scholar, MITS, Gwalior, India , IN
Keywords: Data mining, EDM, performance prediction, data mining techniques.
Abstract
To judge the performance of students in advanced education has now become a great challenge not only in academic but in curriculum activities as well. In this manner, it is important to adequately analyze the data which is utilized for educating and learning processes. Mining data from educational dataset helps to extract useful information for enhancing the teaching and learning abilities. This survey presents the overview of various Data Mining Techniques in terms of advanced education as a new research domain known as educational data mining (EDM) for foreseeing the execution behavior of the students and to find out the reasons behind their failures. The intended review of literature is assessed to briefly evaluate the work done in educational field. Through this task, we extract those factors that describe student's attainments and discover those ones who require special concern by introducing various data mining methods which assimilate classification, clustering, regression, prediction and so forth.
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