An Automatic Approach for Customization of Teaching Process Based on Learning Styles in Adaptive and Intelligent Learning Systems

Abstract

This paper presents a new approach for automatic personalization of the teaching process in intelligent and adaptive systems for distance education, taking into account students learning styles. Promising results have been obtained through experiments with a method that uses a learning styles model based on probability distributions instead of using fixed types, which resulted in a non-deterministic student modeling and teaching personalization processes, enabling treatment of the uncertainties inherent to learning styles modeling and content adaptation processes.