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

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

Author(s): Fabiano Azevedo Dorca, Rafael D. Araujo, Vitor C. de CARVALHO, Daniel T. RESENDE, Renan G. CATTELAN
Subject(s): Essay|Book Review |Scientific Life
Published by: Vilniaus Universiteto Leidykla
Keywords: personalized content recommendation; learning styles; learning objects; expert systems; adaptive educational systems

Summary/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.

  • Issue Year: 15/2016
  • Issue No: 1
  • Page Range: 45-62
  • Page Count: 18
  • Language: English