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learning activities, and presentation styles, etc).
In this paper, we have proposed a framework for
smart learning management system. The framework
is designed to provide learning materials that is
suitable for the user level for the topic and most
relevant to the user’s interest. To improve the
accuracy, we have separated user profile into two
parts – static and dynamic, which is an extension of
IMS LIP definition. Dynamic profiler maintains up
to date information for user profile so the learning
object fetcher and the user level assessor can
reference them to provide more accurate result to the
learner. Learning objects are organized by
constructing ontology. Based on RDF description,
semantic search for the learning objects can be
conducted. The final results are filtered by using
relevancy ranking and the filtered result is delivered
to the learner as recommended learning objects.
ACKNOWLEDGEMENTS
This research work is funded by Korea Association
of Industry, Academy, and Research Institute
(KAIRI).
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