Assessing neurophysiologic markers for training and simulation to develop expertise in complex cognitive tasks

Abstract

This work explores the theoretic basis and provides empirical support for using neurophysiologic markers to provide information on a trainee's cognition to guide instruction. This serves as the basis for improving the design of simulation responsive to individual traits for training continuous complex cognitive tasks. Individualized instruction has been empirically proven to be vastly superior to other forms of instruction. However, current methods to design simulation that is responsive to the user have relied primarily on raw performance metrics. These metrics are often misleading and provide very little diagnostic value. For complex tasks, understanding cognitive processes is critical. Neurophysiologic markers can potentially inform instructional systems on trainees' cognition but have yet to be validated. This research developed a sample process to identify neurophysiologic markers for informing individualized instruction. Applying the process to helicopter overland navigation, a theoretic model of eye scan behavior was developed. The process and theoretic model were validated by analyzing novices and expert navigators. Predicted eye scan metrics reliably distinguished between expert and novice behavior, providing insight not available using raw performance metrics. Also, a visualization tool was developed to explore expert scan strategies. In addition to confirming expected strategies and novice expert differences, we discovered novel, unexpected strategies of expert navigators.