Bayesian Modeling for Adaptive Hypermedia Systems
In this paper we show how Bayesian models can be used advantageously
for various adaptation tasks in open WWW-based hypermedia systems. We
discuss how to model user knowledge about different topics and
learning dependencies between these topics, how to make inferences for
calculating the system's belief on a user's knowledge based on
observations from exercises/observations. We illustrate this
discussion by examples from an educational hypermedia system we
developed for our course "Introduction to Java Programming".
Keywords: User and discourse modeling and user adapted interaction.
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