Modeling and Predicting Student Academic Performance in Higher Education Using Data Mining Techniques

Abstract

The primary goal of upper education foundations is to offer quality instruction to its understudies. One approach to accomplish most elevated level of import during advanced education framework is by finding learning for forecast with reference to enrollment of understudies in a specific course, estrangement of typical study hall showing model, discovery of out of line means that used in on-line assessment, identification of surprising qualities within the outcome sheets of the understudies, expectation concerning understudies' exhibition, etc. the educational is tucked away among the instructive infoal index and it's removable through information mining ways. This paper is intended to let the limits of data mining methodologies in setting of cutting edge training by giving a data mining model to higher education framework inside institute. During this exploration, the classification and prediction tasks are employed to assess understudy’s presentation and as there are various methodologies that are utilized; decision tree, clustering and neural network techniques are used here.