Automatic Identification of Learning Styles: A Systematic Literature Review

• Edilaine Santiago de Oliveira IFCE
• Gilvandenys Leites Sales IFCE
• Pryscilla de Sousa Pereira IFCE
• Ramires do Nascimento Moreira IFCE

DOI: https://doi.org/10.5753/wei.2018.3488

Abstract

The spread and evolution of technology have revolutionized the way education is approached. The classification of learning styles within Virtual Learning Environments (VLE’s) can help in the use of new teaching strategies based on the student profile, besides contributing to the personalization of these virtual environments. This research consists of a Systematic Review of Literature (SRL) of relevant works in the last four years that adopt automatic approaches, such as data mining and machine learning, in order to classify student’s learning styles. In all, 12 papers were selected, considered significant for this research, for a more careful analysis. The results show that different techniques are applied, as well as different models of learning styles available in the literature.

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