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ERIC Number: EJ1097513
Record Type: Journal
Publication Date: 2016
Abstractor: As Provided
An Automatic and Dynamic Approach for Personalized Recommendation of Learning Objects Considering Students Learning Styles: An Experimental Analysis
Dorça, Fabiano A.; Araújo, Rafael D.; de Carvalho, Vitor C.; Resende, Daniel T.; Cattelan, Renan G.
Informatics in Education, v15 n1 p45-62 2016
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.
Descriptors: Resource Units, Cognitive Style, Automation, Individualized Instruction, Artificial Intelligence, Classification, Students
Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: email@example.com; Web site: http://www.mii.lt/informatics_in_education/
Publication Type: Journal Articles; Reports - Evaluative
Education Level: N/A
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