MINING EDUCATIONAL DATA TO CATEGORIZE STUDENT’S PERFORMANCE USING R TOOLS

Abstract

Educational Data Mining (EDM) plays a most important role in educational institution. This paper mainly aims to motivate the students in all areas other than the Academic area. There are many categorize involved in educational institutions. This proposed research aims to categorize student’s activity in three ways: 1. Academic Activity 2. Personal Activity 3. Extra Activity. The needed and useful information mined from Training Data Set using data mining techniques. Most of the Educational Institutions motivate the students which includes Academic Activity like Internal Marks, Seminar and End Semester Marks. Similarly, most of the researchers done their works in limited areas, but these three activities are limited. Therefore in this paper we have analyzed Classification Decision Trees (DT) to categorize the student activities into three groups. We have based on the final results of categorization points to provide the Excellency Certificates to all these areas and to Overall Excellency Certificate to one or more students when they get more points in all activities. We have also described and produced how the points are evaluated and how the outputs are achieved in easy manner using R tools. R is an excellent and alternative tool to many of the existing data mining tools. This proposed system could be very helpful in predicting student's activity in different ways and also useful for most of the Educational institutions.
Key Words: Educational Data Mining (EDM), Classification, Decision Trees (DT), Activity, Certificate