A Framework for Capturing Distinguishing User Interaction Behaviors in
By Samad Kardan, Department of Computer Science, UBC.
As novel interactive systems continue to be created, it is often difficult to understand a priori which ensemble of user interaction behaviors are conducive to good task performance. In this talk I'll describe our work on a user modeling framework that relies on interaction logs to identify both classes of user types, as well as the interaction behaviors characteristics of each type. This information is then used to automatically identify the type/behaviors of new users, with the long term goal of providing adaptive interaction support when needed. I will also provide the results of a user study on the CSP applet from the AIspace learning tools, demonstrating the effectiveness of this framework for detecting different behaviour patterns.
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