Training Expert Navigation
A more detailed description of the problem and our goals...
Using helicopter 
overland navigation as a representative task, our project investigates potential improvement to training simulation by monitoring pilots’ eye gaze direction as a measure of their cognitive states and as a cue for instructional intervention. Helicopter overland navigation is a cognitively complex and demanding task that requires years of training and continuous monitoring of system (e.g., ground speed, heading and altitude) and environment (e.g., terrain feature size, shape, slope and orientation) parameters. Given the intrinsically high cognitive workload of novice pilots, it is crucial to judge their performance during training and decide when to deliver instructional guidance. Currently, there are few cues available for the instructor to assess how the trainees monitor key parameters, perceive flight route, and implement navigation strategies. By examining visual scan differences between expert and novice pilots in out-the-window and map displays, we plan to understand cognitive processes by monitoring key parameters and perceiving flight routes in order to develop a real time training enhancement tool to aid navigation instruction.
Current status:
We've refined the experimental design, locked 
down the sytems and software architecture and are collecting data - experiment participants welcome! Data analysis presents an exciting and promising challenge. Although analysis is not complete, we've uncovered some promising future research and thesis topics.
More timely updates are over here...
Future work:
Data analysis continues. 
We are looking forward to working on visualization techniques, smart cockpit technology and instructional cues. Dwell distribution continues to look like a promising metric...
