• DocumentCode
    1312571
  • Title

    Does an Eye Tracker Tell the Truth about Visualizations?: Findings while Investigating Visualizations for Decision Making

  • Author

    Kim, Sung-Hee ; Dong, Zhihua ; Xian, Hanjun ; Upatising, Benjavan ; Yi, Ji Soo

  • Author_Institution
    Sch. ofIndustrial Eng., Purdue Univ., West Lafayette, IN, USA
  • Volume
    18
  • Issue
    12
  • fYear
    2012
  • Firstpage
    2421
  • Lastpage
    2430
  • Abstract
    For information visualization researchers, eye tracking has been a useful tool to investigate research participants´ underlying cognitive processes by tracking their eye movements while they interact with visual techniques. We used an eye tracker to better understand why participants with a variant of a tabular visualization called `SimulSort´ outperformed ones with a conventional table and typical one-column sorting feature (i.e., Typical Sorting). The collected eye-tracking data certainly shed light on the detailed cognitive processes of the participants; SimulSort helped with decision-making tasks by promoting efficient browsing behavior and compensatory decision-making strategies. However, more interestingly, we also found unexpected eye-tracking patterns with Simul- Sort. We investigated the cause of the unexpected patterns through a crowdsourcing-based study (i.e., Experiment 2), which elicited an important limitation of the eye tracking method: incapability of capturing peripheral vision. This particular result would be a caveat for other visualization researchers who plan to use an eye tracker in their studies. In addition, the method to use a testing stimulus (i.e., influential column) in Experiment 2 to verify the existence of such limitations would be useful for researchers who would like to verify their eye tracking results.
  • Keywords
    cognitive systems; data visualisation; decision making; eye; information retrieval; SimulSort; browsing behavior; cognitive process; decision making; eye movements; eye tracker; information visualization; peripheral vision; tabular visualization; Crowdsourcing; Data visualization; Decision making; Market research; Research and development; Tracking; Visualized decision making; crowdsourcing; eye tracking; limitations; peripheral vision; quantitative empirical study;
  • fLanguage
    English
  • Journal_Title
    Visualization and Computer Graphics, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1077-2626
  • Type

    jour

  • DOI
    10.1109/TVCG.2012.215
  • Filename
    6327247