Evaluating learning style personalization in adaptive systems: quantitative methods and approaches

Brown, E. J.; Brailsford, T. J.; Fisher, T. and Moore, A. (2009). Evaluating learning style personalization in adaptive systems: quantitative methods and approaches. IEEE Transactions on Learning Technologies, 2(1) pp. 10–22.

DOI (Digital Object Identifier) Link:	https://doi.org/10.1109/TLT.2009.11
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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.

Item Type:	Journal Item
Copyright Holders:	2009 IEEE
ISSN:	1939-1382
Extra Information:	Special Issue on Personalization
Keywords:	evaluation/methodology; adaptive hypermedia; user issues; computer-assisted instruction; human information processing
Academic Unit/School:	Learning and Teaching Innovation (LTI) > Institute of Educational Technology (IET) Learning and Teaching Innovation (LTI)
Research Group:	Centre for Research in Education and Educational Technology (CREET)
Related URLs:	http://www.computer.org/csdl/trans/lt/20...(Other)
Item ID:	30224
Depositing User:	Elizabeth FitzGerald
Date Deposited:	25 Nov 2011 09:21
Last Modified:	15 Dec 2018 08:59
URI:	http://oro.open.ac.uk/id/eprint/30224
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• Personalization in adaptive systems: quantitative methods and approaches. (deposited 10 Nov 2011 09:05)
  • Evaluating learning style personalization in adaptive systems: quantitative methods and approaches. (deposited 25 Nov 2011 09:21) [Currently Displayed]

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