Title

Data Visualization Approaches in Eye Tracking to Support the Learning of Air Traffic Control Operations

Presenter Email

zihokang@ou.edu

Location

Jim W. Henderson Administration & Welcome Center (Bldg. #602)

Start Date

14-8-2017 1:15 PM

End Date

14-8-2017 2:45 PM

Submission Type

Paper

Topic Area

Human factors

Keywords

Eye tracking, Data visualization, Air traffic control, Learning, Visual scanning pattern

Abstract

Due to the high cost of training new air traffic control specialists (ATCSs) and the expected increase of new hires in the near future, we need less costly methods to effectively train them. One of the approaches is to utilize expert ATCSs’ visual scanning patterns as a learning method; however, there are many issues that need to addressed when we try to visualize and/or aggregate the complex raw eye tracking data composed of eye fixations, durations, and saccades into meaningful patterns. In this paper, we introduce existing data visualization methods, especially those related to visualizing the eye tracking data, along with our preliminary research findings such as applying the concept of visual groupings, adapting the directed network approach, or mapping the visual scanning patterns with verbal protocols so that we can explore more effective ways to characterize large amounts of raw eye tracking data into useful visual scanning patterns for teaching purposes.

Presenter Biography

Dr. Kang is an Assistant Professor in Industrial & Systems Engineering and is the Director of the Human Factors and Simulation Laboratory at The University of Oklahoma. Dr. Kang’s background is in human-integrated systems modeling, and his specialty is in eye tracking data analysis methodologies. Dr. Kang’s research objective is to characterize, model, and analyze human decision making processes in order to understand human behavior and to inform the design of complex systems. He previously worked at Samsung and has performed research for National Aeronautics and Space Administration (NASA) and Collaborative Adaptive Sensing of the Atmosphere (CASA). Dr. Kang is currently corroborating with Federal Aviation Administration (FAA) and National Oceanic and Atmosphere Administration (NOAA).

RESEARCH INTERESTS

  • Human-integrated systems engineering
  • Human factors
  • Eye tracking data analysis methodologies
  • Air traffic management system
  • Weather system
  • Healthcare system

EDUCATION

Ph.D., Industrial Engineering, Purdue University

M.S., Industrial Engineering, Purdue University

B.S., Industrial Engineering, Korea University

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Aug 14th, 1:15 PM Aug 14th, 2:45 PM

Data Visualization Approaches in Eye Tracking to Support the Learning of Air Traffic Control Operations

Jim W. Henderson Administration & Welcome Center (Bldg. #602)

Due to the high cost of training new air traffic control specialists (ATCSs) and the expected increase of new hires in the near future, we need less costly methods to effectively train them. One of the approaches is to utilize expert ATCSs’ visual scanning patterns as a learning method; however, there are many issues that need to addressed when we try to visualize and/or aggregate the complex raw eye tracking data composed of eye fixations, durations, and saccades into meaningful patterns. In this paper, we introduce existing data visualization methods, especially those related to visualizing the eye tracking data, along with our preliminary research findings such as applying the concept of visual groupings, adapting the directed network approach, or mapping the visual scanning patterns with verbal protocols so that we can explore more effective ways to characterize large amounts of raw eye tracking data into useful visual scanning patterns for teaching purposes.