Oscar Revelo Sánchez, César Collazos Ordóñez, Miguel Redondo Duque
pp. 29 – 45, download
(https://doi.org/10.55612/s-5002-049-002)
Abstract
Considering that group formation is one of the key processes when developing activities in collaborative learning contexts, this paper aims to propose a technique based on an approach of genetic algorithms to achieve homogeneous groups, considering the students’ personality traits as grouping criteria. For its validation, an experiment was designed with 132 first semesters engineering students, quantifying their personality traits through the “Big Five Inventory”, forming workgroups and developing a collaborative activity in initial Programming courses. The experiment made it possible to compare the results obtained by the students applying the proposed approach to those obtained through other group formation strategies. It was demonstrated through the experiment that the homogeneous groups generated by the proposed technique produce better academic results compared to thegrouping techniqueby students’ preference, traditionally used by the teachers when developing a collaborative activity.
Keywords: Collaborative learning, Empirical study, Genetic algorithms, Group formation, Personality traits.