A. Burattin, M. Kaiser, M. Neurauter and B. Weber
In: Proc. TAProViz '16 (accepted), 2016.
Abstract. Research on the process of process modeling (PPM) studies how process models are created. It typically uses the logs of the interactions with the modeling tool to assess the modeler's behavior. In this paper we suggest to introduce an additional stream of data (i.e., eye tracking) to improve the analysis of the PPM. We show that, by exploiting this additional source of information, we can refine the detection of comprehension phases (introducing activities such as "semantic validation" or "problem understanding") as well as provide more exploratory visualizations (e.g., combined modeling phase diagram, heat maps, fixations distributions) both static and dynamic (i.e., movies with the evolution of the model and eye tracking data on top).
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