Date of Publication :23rd August 2018

Abstract: Educational Decision Support System has become one of the fundamental needs for any learning centers. Data mining techniques have found to be capable of providing the Decision Support System (DSS) in education domain. Conventional Data mining algorithms needs to be adapted and modified for applying the educational data. The accuracy of any data mining algorithm is also considered to be affected by the attributes selected. This study focuses on different algorithms and attributes used in developing DSS. It is found that most of the studies aimed on improving the performance academic accomplishment of the students and less research has been conducted in providing a decision support system for organizing and maintaining educational infrastructure, areas of interest of students and courses demanded. It is also found that demographic features and students’ past academic details are mainly used as attributes in this area of study. Student’s psychology, its intelligence and the way student learn have not been found to be used as attributes while considering the DSS in education domain

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