A hybrid PSO-GA method for composing heterogeneous groups in collaborative learning
Yaqian Zheng, Yunsong Liu, Weigang Lu, Chunrong Li · 2016
The importance and benefits of collaborative learning have been widely recognized. The initial stage of this instructional strategy is assigning students into groups, which is a key process in collaborative learning. One major approach of the group formation is to form heterogeneous groups based on student characteristics. In previous studies, several approaches have been presented to compose the heterogeneous groups. However, they only consider a limited number of particular student characteristics. To solve this problem, in this paper, a method based on a hybrid PSO-GA approach is proposed, which allows for considering an arbitrary number of student characteristics. With respect to the evaluation of the proposed method, we conduct a series of computational experiments, which are developed on eight data sets with different levels of complexity. The simulation results show that the proposed approach is effective and stable for composing heterogeneous groups.