Prediction of Student’s Academic Performance using Clustering

-------------------------------------------------------------------ABSTRACT------------------------------------------------------------One of the significant facts in higher learning institution is the explosive growth of educational data. These data are increasing rapidly without any benefit to the management. The main objective of any higher educational institution is to improve the quality of managerial decisions and to impart quality education. Predicting successful and unsuccessful students at an early stage of the degree program help academia not only to concentrate more on the bright students but also to apply more efforts in developing remedial programs for the weaker ones in order to improve their progress while attempting to avoid student dropouts. The aim of this study is to apply the k-means clustering technique to analyze the relationships between students’s behavioral and their success.