Investigating the effectiveness of an advanced adaptive mechanism for considering learning styles in learning management systems

Sabine Graf, Ting Wen Chang, Anne Kersebaum, Thomas Rath, Jeffrey Kurcz

Research output: Chapter in Book/Report/Conference proceedingPublished Conference contributionpeer-review

3 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014
EditorsDemetrios G. Sampson, Michael J. Spector, Nian-Shing Chen, Ronghuai Huang, Kinshuk
Pages112-116
Number of pages5
ISBN (Electronic)9781479940387
DOIs
Publication statusPublished - 17 Sep. 2014
Event14th IEEE International Conference on Advanced Learning Technologies, ICALT 2014 - Athens, Greece
Duration: 7 Jul. 20149 Jul. 2014

Publication series

NameProceedings - IEEE 14th International Conference on Advanced Learning Technologies, ICALT 2014

Conference

Conference14th IEEE International Conference on Advanced Learning Technologies, ICALT 2014
Country/TerritoryGreece
CityAthens
Period7/07/149/07/14

Keywords

  • Learning management systems
  • adaptivity
  • learning styles

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