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INFORMATICS IN EDUCATION, 2012, Vol. 11, No. 2, 191-212
© Institute of Mathematics and Informatics,

ISSN 1648-5831

A Stochastic Approach for Automatic and Dynamic Modeling of Students' Learning Styles in Adaptive Educational Systems

Fabiano Azevedo DORÇA, Luciano Vieira LIMA, Márcia Aparecida FERNANDES, Carlos Roberto LOPES

Faculty of Computer Science, Federal University of Uberlândia (UFU) Campus Santa Mônica - Bloco 1B - Sala 1B148 Av. João Naves de Ávila, 2.121 - Bairro Santa Mônica, CEP 38400-902 - Uberlândia/MG, Brazil Faculty of Electrical Engineering, UFU E-mail: {fabiano, marcia,},


Considering learning and how to improve students' performances, an adaptive educational system must know how an individual learns best. In this context, this work presents an innovative approach for student modeling through probabilistic learning styles combination. Experiments have shown that our approach is able to automatically detect and precisely adjust students' learning styles, based on the non-deterministic and non-stationary aspects of learning styles. Because of the probabilistic and dynamic aspects enclosed in automatic detection of learning styles, our approach gradually and constantly adjusts the student model, taking into account students' performances, obtaining a fine-tuned student model. Promising results were obtained from experiments, and some of them are discussed in this paper.


dynamic student modeling, learning styles, probabilistic student model, adaptive educational systems, e-learning

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