The small-world phenomenon: an algorithmic perspective
STOC '00 Proceedings of the thirty-second annual ACM symposium on Theory of computing
Proceedings of the 2008 symposium on Eye tracking research & applications
Who is the expert? analyzing gaze data to predict expertise level in collaborative applications
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
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In this paper we describe preliminary applications of network analysis techniques to eye-tracking data. In a previous study, the first author conducted a collaborative learning experiment in which subjects had access (or not) to a gaze-awareness tool: their task was to learn from neuroscience diagrams in a remote collaboration. In the treatment group, they could see the gaze of their partner displayed on the screen in real-time. In the control group, they could not. Dyads in the treatment group achieved a higher quality of collaboration and a higher learning gain. In this paper, we describe how network analysis techniques can further illuminate these results, and contribute to the development of 'collaboration sensing'. More specifically, we describe two contributions: first, one can use networks to visualize and explore eye-tracking data. Second, network metrics can be computed to interpret the properties of the graph. We conclude with comments on implementing this approach for formal learning environments.