The implementation of a multimedia learning environment for graduate civil engineers

Abstract

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.