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INFORMATICS IN EDUCATION
Journal of Eastern and Central Europe

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INFORMATICS IN EDUCATION

ISSN 1648-5831

© Vilnius University Institute of Mathematics and Informatics

2016, Vol. 15, No. 1
pp. 45-62

DOI: http://dx.doi.org/10.15388/infedu.2016.03

An Automatic and Dynamic Approach for Personalized Recommendation of Learning Objects Considering Students Learning Styles: An Experimental Analysis

Fabiano A. DORÇA, Rafael D. ARAÚJO, Vitor C. de CARVALHO,
Daniel T. RESENDE, Renan G. CATTELAN

Faculty of Computer Science (FACOM) - Federal University of Uberlandia (UFU)
Campus Santa Monica - Bloco 1B - Sala 1B148
Av. Joao Naves de Avila, 2.121 - Bairro Santa Monica - CEP 38400-902
Uberlandia/MG, Brazil. Phone Number: +55 (34) 3239-4218

Abstract

Content personalization in educational systems is an increasing research area. Studies show that students tend to have better performances when the content is customized according to his/her preferences. One important aspect of students particularities is how they prefer to learn. In this context, students learning styles should be considered, due to the importance of this feature to the adaptivity process in such systems. Thus, this work presents an efficient approach for personalization of the teaching process based on learning styles. Our approach is based on an expert system that implements a set of rules which classifies learning objects according to their teaching style, and then automatically filters learning objects according to students' learning styles. The best adapted learning objects are ranked and recommended to the student. Preliminary experiments suggest promising results.

Keywords:

personalized content recommendation; learning styles; learning objects; expert systems; adaptive educational systems.




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