Analysis & Survey of Different Data Mining Techniques for Predicting Student’s Performance

Abstract

Data Mining has wide applicability due to wide
ease of use of large amount of data and requirement of
storage as per the need. Data mining techniques are widely
useful in educational data mining for analysis of student data.
In educational area data mining different data mining
techniques like classification, clustering, association rule
mining, decision tree method have been used to analyze
student’s learning manners, their mindset, forecasting their
result, group them, and for finding out different patterns.
Educational data mining helps for improving student’s
performance, for managing the student database and for
managing the institute. This paper focuses on different data
mining techniques that are useful for predicting student
performance.