ABSTRACT
This chapter examines the role of comprehension-based cognitive processes in the acquisition of skills in real-time dynamic task environments. A theoretically-based model of pilot instrument flight (ADAPT) is used as the student model component of an intelligent tool for training real-time complex task performance. ADAPT’s learning mechanisms are used to model instrument flight skill acquisition and to select instructions intended to optimize pilot performance. The flight simulator and oculometer data are time-synched, passed to the ADAPT model for analysis, and then ADAPT selects instructions that optimize pilot comprehension of their task environment. Of particular interest for cognitive science is how ADAPT uses performance data to make inferences about individual pilot knowledge, skill, and focus of attention, and the ability of the model to run simulations in real-time to predict future pilot actions and to select instructions that optimize future performance.
