The effects of cognitive-affective states on performance, workload, and knowledge acquisition in synthetic military training environments

This research investigated the effects of automated feedback system manipulations to influence cognitive-affective states and increase effectiveness teams in complex technological environments. Participants functioned as team members operating unmanned aerial systems to conduct Close Air Support missions in a simulation training environment. This research used a true experimental design and multivariate quantitative analyses of Multiple Analysis of Variance (MANOVA) and Multiple Analysis of Covariance (MANCOVA). Civilians were utilized as participants and they underwent training and had elements of controlling unmanned aerial systems automated for them throughout missions. Independent variable feedback manipulations in this study utilize attributes of engagement and flow as an optimal cognitive-affective states in order to assess resulting state and effectiveness differences. Dependent variables measures included assessment of valence, arousal, workload, performance, and knowledge acquisition. Understanding the complicated nature of these effects could enable aspects of future system designs that might be adapted for augmenting cognitive functioning and optimization of future approaches in training of teams in complex technological environments.