Abstract
The accuracy of a user model usually depends on the amount and quality of information available on the user’s states of interest. An eye-tracker provides data detailing where a user is looking during interaction with the system. In this paper we present a study to explore how this information can improve the performance of a model designed to assess the user’s tendency to engage in a meta-cognitive behavior known as self-explanation.
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Conati, C., Merten, C., Muldner, K., Ternes, D. (2005). Exploring Eye Tracking to Increase Bandwidth in User Modeling. In: Ardissono, L., Brna, P., Mitrovic, A. (eds) User Modeling 2005. UM 2005. Lecture Notes in Computer Science(), vol 3538. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527886_47
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DOI: https://doi.org/10.1007/11527886_47
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