ADAPT: A predictive cognitive model of user visual attention and action planning
We present a computational cognitive model of novice and expert aviation pilot action planning called ADAPT that models performance in a dynamically changing simulated flight environment. We perform rigorous tests of ADAPT's predictive validity by comparing the performance of individual human pilots to that of their respective models. Individual pilots were asked to execute a series of flight maneuvers using a flight simulator, and their eye fixations and control movements were recorded in a time-synched database. Computational models of each of the 25 individual pilots were constructed, and the individual models simulated execution of the same flight maneuvers performed by the human pilots. The time-synched eye fixations and control movements of individual pilots and their respective models were compared, and rigorous tests of ADAPT's predictive validity were performed. The model explains and predicts a significant portion of pilot visual attention and control movements during flight as a function of piloting expertise. Implications for adaptive training systems are discussed.
cognitive models action planning modeling expertise hybrid models