Extraction Rules from Educational Data using FP Growth Algorithm with Correlation

Educational data mining is discoveringknowledge from data that come from educationalenvironment. This paper presents finding interestingpatterns from educational database. Learning howstudent behaviors relate to academic results, couldimprove the teaching system. Association rule miningis used to find the interesting patterns, from whichstudent behaviors can be learned. Correlation value,measured by lift ratio is used to measure theinterestingness. The statistical index of the degree towhich two variables are associated is the correlationcoefficient. The lift value of greater than 1 indicatesa positive correlation between antecedent andconsequent. FP Growth algorithm is used toimplement the association rule