DIANA: A computer-supported heterogeneous grouping system for teachers to conduct successful small learning groups

Abstract

Teachers interested in small-group learning can benefit from using psychological factors to create heterogeneous groups. In this paper we describe a computer-supported grouping system named DIANA that uses genetic algorithms to achieve fairness, equity, flexibility, and easy implementation. Grouping was performed so as to avoid the creation of exceptionally weak groups. We tested DIANA with 66 undergraduate computer science students assigned to groups of three either randomly (10 groups) or using an algorithm reflecting [Sternberg, R. J. (1994). Thinking styles: theory and assessment at the interface between intelligence and personality. In R. J. Sterberg, & P. Ruzgis (Eds.), Personality and Intelligence (pp. 169-187). New York: Cambridge University Press.] three thinking styles (12 groups). The results indicate that: (a) the algorithm-determined groups were more capable of completing whatever they were "required to do" at a statistically significant level, (b) both groups were equally capable of solving approximately 80% of what they "chose to do," and (c) the algorithm-determined groups had smaller inter-group variation in performance. Levels of satisfaction with fellow group member attitudes, the cooperative process, and group outcomes were also higher among members of the algorithm-determined groups. Suggestions for applying computer-supported group composition systems are offered. (c) 2006 Elsevier Ltd. All rights reserved.