Evolution and prediction of radical multi-dimensional e-learning system with cluster based data mining techniques

摘要

In most of the educational institutions, the main concern is with the student performance. If the student performance can be evaluated or predictable miracles can be done in education scenario. But unfortunately there are no system is utilised for student performance evaluation. In the present education system performance evaluation is a big task, because of its multi-dimensional data base. Large data sets may consume time and produce less accurate results. To assess large databases an efficient datamining techniques are required to assess a student academic perfectly. There are various data mining techniques available to search appropriate record and data from large data. In the present paper a new method is proposed to evaluate student performance to analyse student achievement and future performance track. A clustering data mining technique is used to analyse large student data set. A clustering technique will boost the searching process speed and analysis. In the present work the existing techniques are discussed and presented the flaws in various contemporary techniques. Evaluating student performance would enhance the student skills, and help the educators and institutions to adopt new learning methods or modifications in the present techniques.