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Socially assistive robots have the potential to improve group dynamics when interacting with groups of people in social settings. This work contributes to the understanding of those dynamics through a user study of trust dynamics in the novel context of a robot mediated support group. For this study, a novel framework for robot mediation of a support group was developed and validated. To evaluate interpersonal trust in the multi-party setting, a dyadic trust scale was implemented and found to be uni-factorial, validating it as an appropriate measure of general trust. The results of this study demonstrate a significant increase in average interpersonal trust after the group interaction session, and qualitative post-session interview data report that participants found the interaction helpful and successfully supported and learned from one other. The results of the study validate that a robot-mediated support group can improve trust among strangers and allow them to share and receive support for their academic stress.

This study examined the utility of continuous operator state monitoring in predicting air traffic control officer (ATCO) workload and fatigue. Participants (N=8) were observed in live operational air traffic control environments for 60-minute periods. ATCO state was assessed using a real-time, computer vision-based system which tracked operator gaze and pupil diameter. Workload and fatigue were also assessed via the adapted Bedford Workload Scale and Samn-Perelli Fatigue Scale, respectively. Standard deviation of gaze was a significant predictor of both max and mean workload, showing a strong negative relationship with both subjective measures. Pupil diameter showed a significant positive relationship with operator fatigue. Our findings demonstrate the utility of continuous ocular metrics of workload and fatigue in operational environments.