The use of learning styles in adaptive hypermedia

Brown, Elizabeth (2007) The use of learning styles in adaptive hypermedia. PhD thesis, University of Nottingham.

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Abstract

Computer-based learning has become a common phenomenon in the modern age. Many distance-learning systems distribute educational resources on the Internet and indeed entire study programmes are now widely available online. Such a large amount of content and information can be intimidating to learners, who may exhibit different individual characteristics, such as variation in goals, interests, motivation and/or learning preferences. This suggests that a uniform approach taken by learning environments to deliver materials and resources to students is not appropriate and that personalisation of such materials/resources should address users' differences to provide a customised learning experience, thus enhancing its effectiveness, lowering drop-out rates and maintaining high student motivation.

This thesis addresses the latter issue of learning preferences, specifically investigating learning styles as an adaptation mechanism for personalised computer-based learning. A number of previous studies indicated the positive effect that this kind of adaptation provides, but under closer examination these were not conducted in a scientifically rigorous manner and thus their findings are somewhat limited.

This research utilises a quantitative and highly objective approach to investigate visual/verbal and sequential/global learning styles in different user groups. Three user trials were carried out to discover whether there were any benefits to using these learning styles for studying in an adapted environment.

Overall, no statistically significant benefits were found and these findings now shed doubt as to whether learning styles are indeed an effective mechanism for personalised learning.

Item Type:Thesis (PhD)
Supervisors:Brailsford, T.J.
Fisher, A.M.
Uncontrolled Keywords:Learning styles, cognitive styles, adaptive hypermedia, learning, education, personalisation, evaluation.
Faculties/Schools:UK Campuses > Faculty of Science > School of Computer Science
ID Code:577
Deposited By:Elizabeth Brown
Deposited On:09 Oct 2008
Last Modified:17 Feb 2009 16:54

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