Augmented Cognition and Training in the Laboratory: DVTE System Validation

Abstract

As the modern workplace becomes more complex, the training community needs to develop new strategies to continute to create a competent workforce. The emerging field of augmented cognition may be able to contribute greatly to increasing training capability through the use of neurophysiological measures that support real-time performance and can be used to satisfy some of the requirements of an automated intelligent tutoring system. The first step to building this system is to design and validate a testbed that can be used with future efforts to target effective mitigation strategies with learning efficiency. In this study, participants watched a computerized instructional presentation and then engaged in a practice CFF scenario in the simulator. When finished, each participant was assigned to either a low or high task load test scenario. In both, the goal was to destroy five enemy tanks. Some participants were also asked to simultaneously execute a secondary radar monitoring task. Both the National Aeronautics and Space Administration's Task Load Index (NASA-TLX) and the MRQ were used to assess the validity of the testbed. Results from both measures indicate that a significant difference exists between the two levels of workload and further, we can distinguish between the subscales within each measurement tool. Thus, the overarching goal of this study was achieved. High and low workload scenarios were created and validated. Ultimatly, they will be used as a testbed of scenarios to address the questions surrounding the use of neurophysiological equipment to impact individual learning patterns.