Exploring Eye Tracking to Increase Bandwidth in User Modeling


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.

DOI: 10.1007/11527886_47

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@inproceedings{Conati2005ExploringET, title={Exploring Eye Tracking to Increase Bandwidth in User Modeling}, author={Cristina Conati and Christina Merten and Kasia Muldner and David Ternes}, booktitle={User Modeling}, year={2005} }