Evaluating training with cognitive state sensing technology

Abstract

Five different training techniques (classroom, video, game-based, computer-based, and simulator) were compared using neurophysiological measurements. The best performance was displayed by individuals in the classroom and video conditions. These participants also displayed the lowest levels of cognitive workload and the highest levels of engagement. The poorest performance on the training was exhibited by individuals in the computer-based and game conditions. These participants also displayed the highest levels of cognitive workload, the lowest levels of engagement, and computer-based had the highest levels of drowsiness. As expected, the testing phases of the training had the highest levels of workload. In general, engagement dropped and distraction increased during the training phase when the material was first presented to participants. However, participants who could keep engagement high during this period performed better. This suggests that mental state monitoring during training could help provide a mechanism for alleviating distraction and inattention and boost training efficacy. © 2009 Springer.