Title

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

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

Abstract - Paper/Presentation Only

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.

This document is currently not available here.

Share

COinS
 
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.