Detecção automática e dinâmica de Estilos de Aprendizagem para Sistemas Adaptativos Inteligentes para a Educação utilizando a meta-heurística Vitis Vinífera

Abstract

The present work adresses the problem to detect students' cognitive traits in order to customize Virtual Learning Enviroments. In this sense, it applies the Vits Vinifera meta-heuristic to detect the student's Learning Style for the selection of learning objects in order to improve the teaching and learning processes. The proposed approach is evaluated in relation to the state of the art that uses a Genetic Algorithm for the identification of the Learning Style. Experimental results indicate that the proposed approach is superior in relation to the Genetic Algorithm considering the detections erros.