Behavioral Patterns for Automatic Detection of Learning Styles in Learning Management Systems: a Case Study

Abstract

In this paper we present advances of a case study designed to determine which student behaviors are more informative when classifying LMS's users according to their learning style. This case study represents the first step towards developing a mechanism for automatic detection of learning styles in LMS, which takes into account behavioral, affective and performance patterns. The contribution of this paper will benefit researchers and practitioners in the field of educational technology with interest in generating personalized learning environments based in LMS.