Evaluating Learning Style Personalization in Adaptive Systems: Quantitative Methods and Approaches

Brown, Elizabeth J.; Brailsford, Timothy J; Fisher, Tony; Moore, Adam

Abstract

It is a widely held assumption that learning style is a useful model for quantifying user characteristics for effective personalized learning. We set out to challenge this assumption by discussing the current state of the art in relation to quantitative evaluations of such systems and also the methodologies that should be employed in such evaluations. We present two case studies that provide rigorous and quantitative evaluations of learning-style-adapted e-learning environments. We believe that the null results of both these studies indicate a limited usefulness in terms of learning styles for user modeling and suggest that alternative characteristics or techniques might provide a more beneficial experience to users. © 2009, The Institute of Electrical and Electronics Engineers, Inc.

• Journal Article Type: Article
• Acceptance Date: Feb 8, 2009
• Online Publication Date: Feb 20, 2009
• Publication Date: Jan 1, 2009
• Deposit Date: Sep 20, 2018
• Journal: IEEE Transactions on Learning Technologies
• Print ISSN: 1939-1382
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 2
• Issue: 1
• Pages: 10-22
• DOI: https://doi.org/10.1109/TLT.2009.11
• Keywords: evaluation/methodology, adaptive hypermedia, user issues, computer-assisted instruction, human information processing
• Public URL: https://uwe-repository.worktribe.com/output/998722
• Publisher URL: http://dx.doi.org/10.1109/TLT.2009.11
• Contract Date: Sep 20, 2018