Using Cognitive Traits for Improving the Detection of Learning Styles

Abstract

While providing online courses that fit students' learning styles has high potential to make learning easier for students, it requires knowing students' learning styles first. This paper demonstrates how the consideration of cognitive traits such as working memory capacity (WMC) can help in detecting learning styles. Previous studies have identified a relationship between learning styles and cognitive traits. In this paper, the practical application of this relationship is described and its potential to improve the detection of learning styles by additionally including data from cognitive traits in the calculation process is discussed. An extended approach and architecture for identifying learning styles which consider cognitive traits is also introduced. Furthermore, an experiment has been conducted that shows the positive effect of considering WMC in the detection process of learning styles for two out of three learning style dimensions, leading to higher precision of the results and therefore more accurate identification of learning styles which in turn lead to more accurate adaptivity for students.

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