Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for
deriving course offerings that are customized to the needs
of different learning communities or even individuals.
Several ways of organizing this course composition
process are discussed.
Course composition needs a clear understanding of the
dependencies between the learning objects. Therefore we
discuss the metadata for object relationships proposed in
different standardization projects and especially those
suggested in the Dublin Core Metadata Initiative.
Based on these metadata we construct adjacency
matrices and graphs. We show how Gozinto-type computations
can be used to determine direct and indirect
prerequisites for certain learning objects.
The metadata may also be used to define integer
programming models which can be applied to support the
instructor in formulating his specifications for selecting
objects or which allow a computer agent to automatically
select learning objects. Such decision models could also
be helpful for a learner navigating through a library of
learning objects. We also sketch a graph-based procedure
for manual or automatic sequencing of the learning
objects.