Hermann Astleitner and Detlev Leutner
Journal of Educational Computing
Research, Vol. 14(3), 1996, p. 285-303
Hypermedia systems may be considered as networks of interconnected fragments
of information. In the literature, several attempts have been made to describe
characteristics of nodes, links, and of the overall structure of such systems.
However, the utility of these attempts is only limited for educational purposes
because most of them are uneconomic in measuring and almost none of them
is explicitly concerned with learning. In this article, an analogy between
information networks and social networks is established. This analogy is
used to illustrate the application of standard network analysis procedures.
These procedures are 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 the graphical representation of a hypothetical hypermedia system can
be transformed into a matrix format which functions as the basis for computing
standard network indices for nodes, groups of nodes, and entire networks
(e.g., among other, centrality, cliques, or path distances). For each index,
its potential influence on learning processes or learning outcomes is discussed.
Implications of using standard network indices for research and practice
in the field of educational or instructional hypermedia systems are outlined.
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