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Mining: Student Database


 

Data mining is the process of analyzing data from different perspectives and summarizing it into useful information. Educational data mining is an emerging discipline concern with developing methods for exploring the unique type of data that come from educational setting and using those methods to better understand the student’s performance. Mining in educational environment is called educational data mining. For mining educational DB the concepts named clustering, classification and association are used. It is concerned with developing new methods to discover knowledge from educational database. Educational data mining provides a set of techniques, which can help the educational system to overcome the performance issues. This paper presents the concepts needed to reduced drop-out ratio to a significant level and to improve the performance of students by discovering knowledge for prediction regarding enrolment of students in a particular course, alienation of traditional classroom teaching model, detection of unfair means used in online examination, detection of abnormal values in the result sheets of the students, prediction about students’ performance and so on.


Keywords

Educational Data Mining (EDM), Classification, Knowledge Discovery in Database (KDD), k-means Algorithm
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  • Mining: Student Database

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Abstract


Data mining is the process of analyzing data from different perspectives and summarizing it into useful information. Educational data mining is an emerging discipline concern with developing methods for exploring the unique type of data that come from educational setting and using those methods to better understand the student’s performance. Mining in educational environment is called educational data mining. For mining educational DB the concepts named clustering, classification and association are used. It is concerned with developing new methods to discover knowledge from educational database. Educational data mining provides a set of techniques, which can help the educational system to overcome the performance issues. This paper presents the concepts needed to reduced drop-out ratio to a significant level and to improve the performance of students by discovering knowledge for prediction regarding enrolment of students in a particular course, alienation of traditional classroom teaching model, detection of unfair means used in online examination, detection of abnormal values in the result sheets of the students, prediction about students’ performance and so on.


Keywords


Educational Data Mining (EDM), Classification, Knowledge Discovery in Database (KDD), k-means Algorithm