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Teamwork and collaboration form the cornerstones of organizational performance and success. It is important to understand how the attention allocation of team members is linked to performance. One approach to studying attention allocation in a team context is to compare the scanpath similarity of two people working in teams and to explore the link between scanpath similarity and team performance. In this study, participants were recruited to work in pairs on an unmanned aerial vehicle (UAV) task that included low and high workload conditions. An eye tracker was used to collect the eye movements of both participants in each team. The scanpaths of two teammates were compared in low and high workload conditions using MultiMatch, an established scanpath comparison algorithm. The obtained scanpath similarity values were correlated with performance measures of response time and accuracy. Several MultiMatch measures showed significant strong correlations across multiple dimensions, providing insight into team behavior and attention allocation. The results suggested that the more similar each team member’s scanpath is, the better their performance. Additional research and consideration of experimental variables will be necessary to further understand how best to use MultiMatch for scanpath similarity assessment in complex domains. 

Complex and dynamic environments including military operations, healthcare, aviation, and driving require operators to transition seamlessly between levels of mental workload. However, little is known about how the rate of an increase in workload impacts multitasking performance, especially in the context of real-world tasks. We evaluated both gradual and sudden workload increases in the dynamic multitasking environment of an Unmanned Aerial Vehicle (UAV) command and control testbed and compared them to constant workload. Workload transitions were found to improve response time and accuracy compared to when workload was held constant at low or high. These results suggest that workload transitions may allow operators to better regulate mental resources. These findings can also inform the design of operations and technology to assist operators’ management of cognitive resources, which include negating the adverse effects of vigilance decrements during low workload periods and data overload during high workload periods. Background: High workload and workload transitions can affect performance; however, it is not clear how the rate of transition from low to high workload influences performance in a multitasking setting. Purpose: We investigated the effect of workload transition rate on performance in a multitasking environment that is akin to the expectations of operators in complex, data-rich work domains. Method: An Unmanned Aerial Vehicle (UAV) command and control testbed was used to vary workload between low, high, gradually transitioning from low to high, and suddenly transitioning from low to high. Performance measures consisted of the response time and accuracy of one primary task and three secondary tasks. Analyses compared: (a) performance differences between gradual and sudden increases in workload; (b) performance during the low workload phases of the workload transitions; and (c) performance during the high workload phases of the workload transitions. Results: Overall, there were limited performance differences between gradual and sudden workload transitions. However, both types of transitions led to better performance than constant workload, lending some support for the effort regulation explanation which suggests that participants actively evaluated the amount of mental resources necessary to successfully complete a task after a workload transition. Conclusions: Gradual and sudden workload transitions benefit primary and secondary task performance, suggesting that the applicability of existing theoretical explanations depend on the context. For example, varying task demands can be a means to assist operators in the appropriate regulation of mental resources in domains with interdependent tasks. These findings can inform occupation and technology design to support task management.