Forming heterogeneous group in cooperative learning process using partitioning around medoids (PAM) and equitable distribution

Selection of methods will greatly impact in learning process. One of the methods commonly applied are Cooperative learning. Cooperative learning is one of many learning techniques to improve the performance of students in the academic literature. Moreover, the heterogeneity in study group's academics can improve performance, but only partially implementing cooperative learning in a group of heterogeneous formations. The problem faced in this type is the process of forming group of students into a heterogeneous group and inter-group quality is relatively equal or balanced. In this study, the authors aimed to provide intelligent solutions in the distribution group based on the value (The value of achievement on related subjects) and personality traits of each student in the determination of the performance of students are using the algorithm clustering Partitioning Around Medoids (PAM) in consideration of the value of measurement Euclidean Distance (ED) and the equitable distribution to form heterogeneous groups based on their level of heterogeneity in Measured with Goodness of Heterogeneity in Group (GH) and the rate of coefficient variation (CV) in same group or between groups with groups and equitable distributions on college campuses.