Investigating the Utility of Eye-Tracking Information on Affect and Reasoning for User Modeling

We investigate the utility of an eye tracker for providing information on users' affect and reasoning. To do so, we conducted a user study, results from which show that users' pupillary responses differ significantly between positive and negative affective states. As far as reasoning is concerned, while our analysis shows that larger pupil size is associated with more constructive reasoning events, it also suggests that to disambiguate between different kinds of reasoning, additional information may be needed. Our results show that pupillary response is a promising non-invasive avenue for increasing user model bandwidth.

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