Abstract
Educational organizations are one of the important parts of our society and playing a vital role for growth and development of any nation. With the help of Data Mining, which is an emerging technique, one can efficiently learn from historical data and use that obtained knowledge for predicting future behaviour of concern areas. Growth of current education system is surely enhanced if Data Mining has been adopted as a futuristic strategic management tool. The Data Mining tool is able to facilitate better resource utilization in terms of student performance, course development and finally the development of nation's education related standards. This paper focuses on capabilities of data mining in context of education, Also it compare three of the most common data mining techniques (ID3, C4.5 and REPTree).
Highlights
During past few years, there is explosive growth in the educational data which contains valuable information [2]
The knowledge discovered by data mining techniques would enable the higher education systems in making better decisions, having more advanced planning [1]
Size of the data is 1038 records are given in Table 2 where Excellent (EX), Very Good (VG), Good (G), Acceptable (ACC) and Fail (FL), Average (AV), Poor (P), Yes (Y), No (N), Female (F), Male (M)
Summary
There is explosive growth in the educational data which contains valuable information [2]. Organizations generate data about student, staff, faculty, which contains information of management system, employees, lecturers, organizational personal and so on. These strategic resources are helpful for improving quality of higher educational institutes. Educational data mining uses many techniques such as decision tree, rule induction, neural networks, k-nearest neighbour, naïve Bayesian and many others. By using these techniques, many kinds of knowledge can be discovered such as association rules, classifications and clustering [4] [5]
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