A Semi-Pareto Optimal Set based algorithm for grouping of students

• Published in: 4th International Conference on e-Learning and e-Teaching (ICELET 2013) pp. 10 - 13
• Main Authors: M. Mahdi, Barati Jozan, Fattaneh, Taghiyareh
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.02.2013
• Subjects: Clustering algorithms; collaborative learning; Electronic learning; Federated learning; grouping of student; heterogeneous and homogeneous group; Heuristic algorithms; NP-hard problem; pareto optimal set; Pareto optimization; Teamwork; Technological innovation; Training; Vectors
• ISSN: 2163-6982
• DOI: 10.1109/ICELET.2013.6681637

Collaborative learning in traditional and e-learning environments has a significant influence on the student learning process. Forming appropriate groups of students is one of the important factors in the collaborative learning, so lots of researches have been done in this area. In this paper, the new algorithm is proposed for grouping of students that uses modified Pareto Optimal Set concept that is called Semi-Pareto Optimal Set. The main advantages of this algorithm is that it does not limit number of student attributes in forming the groups and can uses for both heterogeneous and homogeneous groups. The results indicate that the proposed algorithm has high quality in formation groups and formed groups that are efficient in two below criteria 1) intra-group fitness that is the difference between students of groups and 2) inter- group fitness that is similarity between formed groups.