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
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;
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
DOI :
10.1109/TVCG.2012.215