Composing High-Heterogeneous and High-Interaction Groups in Collaborative Learning with Particle Swarm Optimization
Computer Science and Information Engineering, World Congress on (2009)
Los Angeles, California USA
Mar. 31, 2009 to Apr. 2, 2009
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CSIE.2009.876
Computer supported collaborative learning (CSCL) which helps to increase the social interactions among learners without the constraint of time and space as it would be in real classrooms has prevailed among e-learning technologies. However,the studies of group formation that involve with diverse characteristics such as learning style of students or concern with interactions among students have rarely been conducted. Due to the fact that allocating students into groups is an NP-hard problem, we propose a particle swarm optimization (PSO) algorithm to cope with the problem of constructing high-heterogeneous and high interaction groups for students in classrooms to enhance the effect of CSCL. A real case with 61 students in a classroom was illustrated for our PSO grouping algorithm. The results indicate that students could be allocated into groups with higher degrees of heterogeneity among groups and interactions among members in a rational execution time.
Collaborative work, Particle swarm optimization, Computer science, Space technology, NP-hard problem, Time factors, Electronic learning, Collaboration, Surges, Assembly, Particle Swarm Optimization, Meta-Heuristic Algorithm, Group Composing, Learning Style
"Composing High-Heterogeneous and High-Interaction Groups in Collaborative Learning with Particle Swarm Optimization", Computer Science and Information Engineering, World Congress on, vol. 04, no. , pp. 607-611, 2009, doi:10.1109/CSIE.2009.876