A memetic algorithm for collaborative learning team formation in the context of software engineering courses

Authors:
Virginia Yannibelli;Analía Amandi
Affiliations:
ISISTAN Research Institute, UNCPBA, Tandil, Buenos Aires, Argentina, CONICET, Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina;ISISTAN Research Institute, UNCPBA, Tandil, Buenos Aires, Argentina, CONICET, Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina
Venue:
ADNTIIC'11 Proceedings of the Second international conference on Advances in New Technologies, Interactive Interfaces and Communicability
Year:
2011

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Abstract

In this paper, we propose a memetic algorithm with the aim of assisting professors when forming collaborative learning teams in the context of software engineering courses. This algorithm designs different alternatives to divide a given number of students into teams and evaluates each alternative as regards one of the grouping criteria most analyzed and appropriate in the context of software engineering courses. This criterion is based on taking into account the team roles of the students and on forming well-balanced teams according to the team roles of their members. To analyze the performance of the proposed algorithm, we report the computational experiments developed on eight different data sets. In this respect, the algorithm has obtained high-quality solutions for each one of the utilized data sets.