Detecção Automática e Dinâmica de Estilos de Aprendizagem em Sistemas Adaptativos e Inteligentes utilizando Dynamic Scripting

Abstract

Adaptive and Intelligent Educational Systems (AIES) aim to provide a personalized assistance to the student by detecting their Learning Style (LS). One of the most popular techniques used for this detection is Reinforcement Le- arning (RL). However, RL presents slow convergence rate in some cases. This work proposes the improvement of an AIES by using an adaptation of the Dy- namic Scripting technique, considered faster than the RL. Experimental results showed that the proposed technique reduced the number of the learning pro- blems by ≈ 54%, and ≈ 35%, respectively, to Static and Dynamic LS, while reduced the number of interactions by ≈ 5.7% in relation to the literature.