A New Approach to Discover Students Learning Styles in Adaptive Educational Systems

Resumo

Personalization according to specific requirements of an individual student is one of the most important features in adaptive educational systems. Considering learning and how to improve a student’s performance, these systems must know the way in which an individual student learns best. In this context, the current work outlines a new approach to discover students learning styles, which is mainly based on the non-deterministic and non-stationary aspects of learning styles, taking into account that learning styles may change during the learning process in an unexpected and unpredictable way. Taking into consideration the stochastic and dynamic aspects enclosed on learning process, our approach gradually and constantly updates the student model using a set of rules that infer which learning styles should be adjusted at a specific moment. Therefore, the student model stochastically evolves towards the real student’s learning style, considering its fine-tuned strengths. Our approach has been being tested through computer simulation of students and promising results have been obtained. Some of them are presented in this paper.