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The intelligence of an interactive system is exhibited through the evolution of its intelligent behaviors, namely, its effectiveness in performing tasks and its adaptiveness to both variations of task conditions and different users. Having a good user modeling component in any intelligent interactive system becomes crucial to the performance of that system. We have developed a computational approach to building intelligent tutoring systems (ITS) in conjunction with our framework for ITS . This computational approach employs two exploratory AI techniques-a hybrid knowledge representation model as an implementation mechanism of ITS and a rough set  approximation approach to user modeling. In this article, we focus on discussing the rough set approach to user modeling of the system in detail.