Considering social-affective factors for group formation in collaborative learning environments with computer support using genetic algorithms

Abstract

In collaborative learning, affective-partner factors such as cooperation, motivation, cognitive-partner affinities, pro-activity, interaction, among others, play an important role of stimulation to collaboration, as well as they act in the construction of relations of human being of a cultural-partner perspective. According to researchers, in collaborative activities of learning, affective-partner individual abilities of one person need to be conjugated with other ones in order to get greater success in the collaborative work. Although pedagogues and other researchers turned towards education recognize the importance to consider affective-partner factors in learning collaborative activities, only a few collaborative educational environments are making considerations into this matter. It is from this challenge that this work searches to advance in the state of the art, as well as to present actions of inferences of the affective-partner factors: Capacity of Cooperation, Personality, Leadership and Social Affinity, in order that they be used as criteria in the formation of groups of students to work collaboratively through the modeling of a Genetic Algorithm.

Keywords: emotions, genetic algorithms, collaborative learning.