Digests, snapshots, events, or cumulative gaze - what is most informative of success and failure? A study of the foretelling signs of user performance during interaction with ontology visualization

Tracking #: 3271-4485

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Bo Fu

Responsible editor: 
Cogan Shimizu

Submission type: 
Full Paper
The current research landscape in ontology visualization has largely focused on tool development yielding an extensive array of visualization tools. Although many existing solutions provide multiple ontology visualization layouts, there is limited research in adapting to an individual user’s performance, despite successful applications of adaptive technologies in related fields including information visualization. In an effort to innovate beyond traditional one-size-fits-all ontology visualizations, this paper contributes one step towards realizing user adaptive ontology visualization in the future by recognizing timely moments where users may potentially need intervention, as real-time adaptation can only occur if it is possible to correctly predict user success and failure during an interaction in the first place. Building on a wealth of research in eye tracking, this paper compares four approaches to predictive gaze analytics through a series of experiments that utilizes scheduled gaze digests, irregular gaze events, last known gaze status, as well as all gaze captured for a user at a given moment in time. Experimental results suggest that irregular gaze events are most informative of early predictions, while increased gaze is most often associated with peak accuracies. Furthermore, cognitive workload appears to be most indicative of overall user performance, while task type may impact predictive outcome irrespective of the gaze analysis approach in use.
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