ABSTRACT
This chapter explains an academic institute to improve the quality of education by analyzing the data and discover the factors that affect the academic results. It focuses on the implementation of data mining techniques and methods for acquiring new knowledge from student database. Educational data mining (EDM) research focused with developing new methods to find out knowledge from educational database. Clustering is applied to group the records in classes that are similar, and dissimilar records to other classes. Clustering aimed at finding high-quality clusters such that the inter-cluster distances are maximized and the intra-cluster distances are minimized. Classification is one of the most frequently studied problems by data mining and machine-learning researchers. A couple of EDM methods and algorithms are adopted in this research to discover hidden patterns and relationships. In each of these tasks, research has presented the extracted knowledge and described its importance in educational domain.
