Performance Based Grouping of Neighbors Students in Progressive Education Datasets

Abstract

Now a day’s the educational organizations are facing the biggest challenges, of the massive growth of educational data. Further they do not have a good policy and to use this data for improving the quality of their managerial decisions in today’s scenario. The main goal of higher education institutions is to provide quality of education for their students.

In general the educational database contains the important information for predicting a student’s performance, and this Prediction of student’s performance in educational environments is of utmost importance. The knowledge mining techniques has provided a decision making tool which can facilitate better resource utilization in terms of students performance. The knowledge mining techniques are more helpful in classifying educational database. In this paper the clustering task is used to assess student’s performance from education databases. By using this task we extract the knowledge that can describes students’ performance in end semester examination.

Keywords – Educational datasets, knowledge mining, Decision Making, Data Classification, Performance Prediction.