October 2006 Volume 9 Number 4

Figure 4. Sample domain knowledge ontology (White arrow: isSubTopicOf, Black arrows: isPrerequisiteFor,
both relationships are transitive)
Designing an ontology is by no means trivial, nor are there commonly accepted standard methods for building
ontologies. We refer the reader to the work of Holsapple and Joshi (2002) on collaborative ontology design.
Figure 4 shows a very small part of an ontology for the domain ''data base systems'' that captures the topic of
normalization. The resulting ontology can then be implemented using one of the many ontology representation
languages such as RDF/RDFS, OWL, DAML, KIF, etc. The different representation languages provide different
levels of formality to capture different kinds of ontology characteristics and semantics. We found RDF to be
sufficient four our purpose.
We note that content analysis and content design have to be done just once for each knowledge domain. Ideally,
one could then defer the combination of ontology and didactic principles to the domain implementation phase.
Content didactics design
As pointed out earlier, content and didactics are interdependent so that one cannot simply transfer a component
into a different didactic environment without adapting its content. Indeed, we found it extremely difficult to
delay their combination past content didactics design. Instead we merge the ontology with the didactic
principles, i.e., the intended didactic usage of the content, into what we call learning atoms. Figure 5 gives a few
examples. Figure 5 also demonstrates that atom types may belong to terms on any level of the ontology.
Learning atoms that belong to the same term in the ontology are combined into a learning module. Hence, for
each term in the ontology there exists exactly one corresponding learning module with all learning atoms related
to that term. As we move upwards to higher levels of the ontology, more complex modules are constructed that
include modules from the lower levels. Consequently, the notion of learning module is recursively defined.
Figure 5 sketches an example.
Since there is a learning module for each term in the ontology, modules are already implicitly defined during the
creation of the ontology. By instantiating an atom from a certain atom type it automatically becomes part of the
appropriate module (and implicitly also of the higher-up modules through the isSubtopicOf relationship).
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