A Review on the Academic performance analysis of higher Education Students using Data Mining Techniques

In today's world, various concerned bodies such as Students of higher educational systems, Parents, Government, Educational Policy Makers, Instructors and others seriously need to have relevant and timely information about higher Education's overall performance which is all about Students' academic activity in higher educations. As a result, analyzing the academic performance of higher Educational System/Institution students and predicting their Academic performance is considered to be highly important, necessary, and can also contribute to the development of a nation in general and to students, instructors, parents, governments, Education policy makers, higher education administrative bodies and higher educational Institutions in particular. However, analyzing student's activity in education circumstances and predicting their academic performance is very much challenging and difficult task for several reasons; availability of very huge volume of unstructured data in higher Education's is one among various reasons. This literature review is proposed with the aim to get insight about different knowledge Discovery in Data Base Methods used to analyze and forecast student's over all capacity in their Education and also to identify how the algorithms used for Prediction can also be used to find very important attributes.