Ontologies and the Semantic Web for E-learning - Educational ...

a common denominator, is extremely important, so that the semantics can be preserved between different
systems. It is at this level where the actual acceptance of standards by the different parties (authors, researchers,
developers, end-users) becomes important, even if the standards might not fulfil all of their respective needs.
Before we proceed, we have to analyse these needs in more detail.
The remainder of this document is structured as follows. First we look at Adaptive Hypermedia and the Semantic
Web from the point of view of E-learning, to see if and how E-learning can benefit from them. The next section
treats the adoption process of Semantic Web techniques and technologies by Adaptive Hypermedia. We then
shortly sketch LAOS, an Adaptive Hypermedia (authoring) framework, along with its goals and connection to
the Semantic Web. Then we consider LAOS from the point of view of Semantic Web languages, and attempt to
express it in XML Schema paired with an example XML application. Next we describe MOT, an authoring
system built based on LAOS. We look at some Semantic Web features of MOT, and we then express MOT in
the Semantic Web language, RDF. Finally, we draw some conclusions.
E-Learning, Adaptive Hypermedia and the Semantic Web
Do the Semantic Web and Adaptive Hypermedia actually provide viable solutions for e-learning? Fensel
&Musen (2001) call the Semantic Web a “bigger and more powerful” Web – but what can the Semantic Web do
for e-learning? According to Brusilovsky (2001) “Adaptive Hypermedia is an alternative for the ‘one-size-fitsall’
approach in the development of hypermedia systems”. How does this benefit e-learning? As both Adaptive
Hypermedia and Semantic Web have higher production costs than regular, linear hypermedia for e-learning, the
benefits have to be evaluated carefully.
What are these benefits? Before embarking on one or the other solution, an educator or provider of "learning"
(e.g., as a commodity) should consider the following questions:
1. Do I only deal with learners of a given type (as opposed to a variety of learners and learner
characteristics)?
2. Do I need to change (parts of) the content frequently or do I expect to perform changes in time to the given
material (as opposed to not at all)?
3. Do I expect everything to be created by the same person, an expert who can deal with all aspects of a
course (from contents to the adaptive behaviour, from notification type to other communication aspects,
etc.), as opposed to having different experts and roles for different parts of the authoring / creation
process?
4. Do I need to export (move data) between different learning systems, as opposed to using only one system
during the whole authoring and exploitation (learning material delivery) process?
Let’s look at the possible answers and treat the needs resulting from them one by one.
Learners of a given type
If the answer to the first question is yes, then adaptivity is most probably not the answer, and a one-size-fits-all
approach is appropriate. There are some special cases in which learners of a given type still vary (for instance, in
time) with respect to their needs, preferences, etc., but here we are considering a setting similar to that of
educational TV broadcasting, without any type of personalization.
If the answer is no, and there are several types of learners, then Adaptive Educational Hypermedia is necessary,
to cater for the different needs for each type of learner (for instance, for each stereotype, such as beginner,
intermediate, advanced; or for each learning style expected, such as field-dependent and field-independent). The
semantic web responds with user ontologies, but their actual applications still lie in the future.
Frequent content change
If the answer to the second question is yes, then the content has to be sufficiently malleable to be reused in
different settings, so that each change can focus on the new issues and refine the old. Therefore, a layered
approach with appropriate semantic labelling is necessary, at least with respect to the semantics inherent to the elearning
system used. The layers should reflect a higher level semantics, such as domain model, user
characteristics, machine characteristics, etc. At a lower level, the semantics have to be applied all the way to the
41