APPLYING STANDARD NETWORK ANALYSIS TO HYPERMEDIA SYSTEMS - IMPLICATIONS FOR LEARNING

Hypermedia systems may be considered as networks of interconnected fra gments of information. In the literature, several attempts have been m ade to describe characteristics of nodes, links, and of the overall st ructure of such systems. However, the utility of these attempts is onl y limited for educational purposes because most of them are uneconomic in measuring and almost none of them is explicitly concerned with lea rning. In this article, an analogy between information networks and so cial networks is established. This analogy is used to illustrate the a pplication of standard network analysis procedures. These procedures a re available in widespread PC software (e.g., UCINET) and are used for calculating indices mapping structural aspects of hypermedia systems which are hypothesized to be relevant for learning. It is shown how th e graphical representation of a hypothetical hypermedia system can be transformed into a matrix format which functions as the basis for comp uting standard network indices for nodes, groups of nodes, and entire networks (e.g., among others, centrality, cliques, or path distances). For each index, its potential influence on learning processes or lear ning outcomes is discussed. Implications of using standard network ind ices for research and practice in the field of educational or instruct ional hypermedia systems are outlined.