Abstract
In addition to providing flexible access to instructional information and supporting convenient learning styles, educational hypermedia offers a nonsequential information presentation that markedly differs from conventional instructional systems. Many pedagogical issues are attributed to the nonlinear structures of educational hypermedia systems. Consequently, an ideal educational hypermedia system should provide navigation guidance, knowledge construction assistance and courseware analysis tools. By emphasizing courseware structure and navigational behavior in an educational hypermedia environment, this work presents several algorithmic analytical models of ideal educational hypermedia systems. Three graph algorithms are educational hypermedia analysis are used to identify courseware structures: minimum cut-set, strongly connected components and cut vertex. The algorithms allow one to construct a knowledge hierarchy, analyze a courseware network to determine whether it is well-structured and automatically generate a hierarchical guidance map to help users navigate in a hypermedia environment. This work also provides two quantitative measures, Hyper Degree and Hyper Distance, to describe further navigational behavior in hypermedia environments. After performing instructional experiments, the above methods were applied to the accumulated data.
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