A Pairing Method in Collaborative Learning by using a Genetic Algorithm

K. Shin-ike and H. Iima (Japan)


Collaborative Learning, Learning Effect, Combination of Students, Pairing Method, Genetic Algorithm


In school education there are many kinds of learning styles, and it is well known that collaborative learning is more effective than conventional individual learning. In the collaborative learning it is very important how to determine the optimal combination of students in order to improve the learning effect. In this paper we propose a pairing method to improve the learning effect in collaborative learning. The problem of determining the optimal pairs is a kind of combinatorial optimization problem, and it is well known that it is difficult to solve the problem. Recently stochastic local search methods have been used for solving combinatorial optimization problems. Thus, we use a genetic algorithm which is one of the stochastic local search methods. This proposed method can determine the combination of pairs of students by a simple process in a short time. When teachers make teaching guidelines to improve the effect of learning, this research can be used effectively for an evaluation and an improvement of teaching.

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