Patterns in Authoring of Adaptive Educational Hypermedia: A Taxonomy of Learning Styles.

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Bibliographic Details
Title:	Patterns in Authoring of Adaptive Educational Hypermedia: A Taxonomy of Learning Styles.
Authors:	Brown, Elizabeth¹ ejb@cs.nott.ac.uk, Cristea, Alexandra¹ cds@cs.nott.ac.uk, Stewart, Craig² a.i.cristea@tue.nl, Brailsford, Tim¹ tjb@cs.nott.ac.uk
Source:	Educational Technology & Society. Jul2005, Vol. 8 Issue 3, p77-90. 14p.
Subject Terms:	Computer assisted instruction authoring software, Computer managed instruction, Computer software, Interactive multimedia, Learning, Instructional systems
Abstract:	This paper describes the use of adaptation patterns in the task of formulating standards for adaptive educational hypermedia (AEH) systems that is currently under investigation by the EU ADAPT project. Within this project, design dimensions for high granularity patterns have been established. In this paper we focus on detailing lower granularity adaptive patterns based upon learning styles. Several patterns from existing AEH system case studies are identified and classified according to an extended learning style "onion" model. This model forms the basis of a learning style taxonomy, introduced here, whose components determine adaptation patterns for AEH. These patterns are of importance both for authoring, as well as for interfacing between adaptive hypermedia systems. From an authoring point of view, these patterns may be used to establish a fine-grain approach to instructional strategies that can be implemented in AEH systems, as a response to a particular learning style. The implementation of this adaptation pattern taxonomy is discussed, both generally and in detail. [ABSTRACT FROM AUTHOR]
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Database:	Education Research Complete

Description
Abstract:	This paper describes the use of adaptation patterns in the task of formulating standards for adaptive educational hypermedia (AEH) systems that is currently under investigation by the EU ADAPT project. Within this project, design dimensions for high granularity patterns have been established. In this paper we focus on detailing lower granularity adaptive patterns based upon learning styles. Several patterns from existing AEH system case studies are identified and classified according to an extended learning style "onion" model. This model forms the basis of a learning style taxonomy, introduced here, whose components determine adaptation patterns for AEH. These patterns are of importance both for authoring, as well as for interfacing between adaptive hypermedia systems. From an authoring point of view, these patterns may be used to establish a fine-grain approach to instructional strategies that can be implemented in AEH systems, as a response to a particular learning style. The implementation of this adaptation pattern taxonomy is discussed, both generally and in detail. [ABSTRACT FROM AUTHOR]
ISSN:	11763647