The implementation of a multimedia learning environment for graduate civil engineers

Underlying our approach to the development of a Multimedia Learning Environment (MLE) is the proposition that conventional learning needs analysis, for Computer-Based Learning does not address the richness of delivery possible with MLEs. We propose that knowledge-engineering techniques (from the fie...

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Main Authors: Peter Jagodzinski, Chris Smith
Format: Article
Language:English
Published: Association for Learning Technology 1995-12-01
Series:Research in Learning Technology
Online Access:http://www.researchinlearningtechnology.net/index.php/rlt/article/view/9589
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spelling doaj-a570b7f1f50549e8931c8cd774faf5c92020-11-24T22:37:29ZengAssociation for Learning Technology Research in Learning Technology2156-70692156-70771995-12-013110.3402/rlt.v3i1.9589The implementation of a multimedia learning environment for graduate civil engineersPeter JagodzinskiChris SmithUnderlying our approach to the development of a Multimedia Learning Environment (MLE) is the proposition that conventional learning needs analysis, for Computer-Based Learning does not address the richness of delivery possible with MLEs. We propose that knowledge-engineering techniques (from the field of Artificial Intelligence) can provide a richer understanding of the domain, thus enabling a better MLE to be produced. The knowledge-engineering approach we have used, outlined in this paper, involved acquiring knowledge from a range of sources, then analysing this knowledge so that individual knowledge items could be categorized according to identified underlying knowledge-representation paradigms which each imply their own, most suitable, presentation style. This knowledge engineering analysis was then used to select an instructional model capable of conveying all the acquired types of knowledge in their paradigmatic styles, and detailed and adaptable enough to be implemented on a computer. The chosen model, the Cognitive Apprenticeship Model (CAM), was explicitly used as the basis for the architecture of the MLE.http://www.researchinlearningtechnology.net/index.php/rlt/article/view/9589
collection DOAJ
language English
format Article
sources DOAJ
author Peter Jagodzinski
Chris Smith
spellingShingle Peter Jagodzinski
Chris Smith
The implementation of a multimedia learning environment for graduate civil engineers
Research in Learning Technology
author_facet Peter Jagodzinski
Chris Smith
author_sort Peter Jagodzinski
title The implementation of a multimedia learning environment for graduate civil engineers
title_short The implementation of a multimedia learning environment for graduate civil engineers
title_full The implementation of a multimedia learning environment for graduate civil engineers
title_fullStr The implementation of a multimedia learning environment for graduate civil engineers
title_full_unstemmed The implementation of a multimedia learning environment for graduate civil engineers
title_sort implementation of a multimedia learning environment for graduate civil engineers
publisher Association for Learning Technology
series Research in Learning Technology
issn 2156-7069
2156-7077
publishDate 1995-12-01
description Underlying our approach to the development of a Multimedia Learning Environment (MLE) is the proposition that conventional learning needs analysis, for Computer-Based Learning does not address the richness of delivery possible with MLEs. We propose that knowledge-engineering techniques (from the field of Artificial Intelligence) can provide a richer understanding of the domain, thus enabling a better MLE to be produced. The knowledge-engineering approach we have used, outlined in this paper, involved acquiring knowledge from a range of sources, then analysing this knowledge so that individual knowledge items could be categorized according to identified underlying knowledge-representation paradigms which each imply their own, most suitable, presentation style. This knowledge engineering analysis was then used to select an instructional model capable of conveying all the acquired types of knowledge in their paradigmatic styles, and detailed and adaptable enough to be implemented on a computer. The chosen model, the Cognitive Apprenticeship Model (CAM), was explicitly used as the basis for the architecture of the MLE.
url http://www.researchinlearningtechnology.net/index.php/rlt/article/view/9589
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