Investigating the Effectiveness of an Advanced Adaptive Mechanism for Considering Learning Styles in Learning Management Systems

Abstract

Blended and online learning becomes more and more popular and learning management systems (LMSs) are used by many educational institutions to host such blended or online courses. However, such LMS typically do not adapt to students' individual characteristics and provide each student with the same content and presentation. Such one-size-fits-all approach does not fit most students particularly well and can lead to low student performance and satisfaction. In this paper, we present a study to evaluate an advanced adaptive mechanism that extends LMSs with adaptive functionality to automatically provide students with courses that fit their learning styles. The results of this study showed two significant benefits of the adaptive mechanism for students: receiving higher grades on adaptive lessons than on non-adaptive ones while spending a similar amount of time on both, and spending less time on adaptive lessons than on non-adaptive ones while receiving on average the same grades. Based on these results, the proposed adaptive mechanism can be seen as an effective extension to LMSs in order to support students in learning.