In general, clustering and prediction are two of the most remarkable features of data mining techniques. Unlike
traditional analytical methods, data mining could offer more individual-oriented results. The application of data mining
techniques in the education field enables numerous possibilities such as comprehensively analyzing the
characteristics of each students, predicting success in classes, pinpointing the gifted students and their learning paths [13] etc. In the higher education field, data mining applications have been highly suggested by many researchers such as C Romero and S Ventura in [14] and Luan in [15] to modify or design the curriculum to meet the different needs of students in terms of the learning abilities and knowledge construction.