Aspectos emocionais e cognitivos de estudantes em ambientes virtuais de aprendizagem.

Abstract

In distance learning courses, communication between teacher and student occurs via a Virtual Learning Environment (VLE). In this context, several authors in the area claim the existence of a strong relationship between emotion and cognition, and to establish a relationship of affection between teacher and learner may reflect positively on learning. Therefore, knowing and making use of the student's emotions, it may improve the interaction and contribute to the pupils’ motivation. Students have different cognitive styles, in other words, different ways to purchase or process the information. Each cognitive style has features and preferences for learning strategies that should be respected and addressed by the teacher at the time of preparation of teaching materials. To make a customizable VLE, adapting according to cognitive style and emotion of the student, different teaching materials (teaching tactics) were prepared. This is justified because to present the same educational materials for all students may not have the same result of learning for everyone, because of the different cognitive characteristics that each student possesses. Seeking the overall goal of the work is to adapt the VLE according to these aspects, some steps were necessary, such as, to infer emotion and cognitive style of the student, to study the characteristics of cognitive styles to elaborate pedagogical tactics and teaching materials; to define the interaction rules of pedagogical agents, considering aspects inferred during their interaction with the environment. And finally, to make the validation of this study, two groups of high school and graduation students, subsidized the results analyzed by the Clinical Method of Piaget and Data Mining techniques. As a result of the relationship between emotion and cognition in VLEs, it may highlight the importance of improving the quality of interaction and inferring the emotion of the student to support this improvement.