INVESTIGADORES
YANNIBELLI Virginia Daniela
artículos
Título:
A Memetic Algorithm for Collaborative Learning Team Formation in the Context of Software Engineering Courses
Autor/es:
VIRGINIA YANNIBELLI; ANALÍA AMANDI
Revista:
LECTURE NOTES IN COMPUTER SCIENCE
Editorial:
Springer
Referencias:
Lugar: Heidelberg; Año: 2012 vol. 7547 p. 92 - 103
ISSN:
0302-9743
Resumen:
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.