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Collaborative problem solving (CPS) is an important skill in the modern workforce, and due to its interactive nature, is challenging to assess. The present study builds on work in team sciences to provide initial validation for a metric that quantifies CPS influence—the extent to which each individual contributes toward the team’s CPS processes—using average mutual information (AMI). The measure is investigated in teams collaborating in a computer programming task, where one teammate was assigned to a controller role (i.e., the only person who engaged with the task interface directly). Results suggest the controller had more influence over the team’s CPS processes than the other participants in the triad, providing initial validation for the influence metric. Future work will investigate the measure in classrooms and multiple modalities, and extend the metric in real-time to understand how influence fluctuates over the course of collaboration. 

ObjectiveThis study examines low-, medium-, and high-performing Human-Autonomy Teams’ (HATs’) communication strategies during various technological failures that impact routine communication strategies to adapt to the task environment. BackgroundTeams must adapt their communication strategies during dynamic tasks, where more successful teams make more substantial adaptations. Adaptations in communication strategies may explain how successful HATs overcome technological failures. Further, technological failures of variable severity may alter communication strategies of HATs at different performance levels in their attempts to overcome each failure. MethodHATs in a Remotely Piloted Aircraft System-Synthetic Task Environment (RPAS-STE), involving three team members, were tasked with photographing targets. Each triad had two randomly assigned participants in navigator and photographer roles, teaming with an experimenter who simulated an AI pilot in a Wizard of Oz paradigm. Teams encountered two different technological failures, automation and autonomy, where autonomy failures were more challenging to overcome. ResultsHigh-performing HATs calibrated their communication strategy to the complexity of the different failures better than medium- and low-performing teams. Further, HATs adjusted their communication strategies over time. Finally, only the most severe failures required teams to increase the efficiency of their communication. ConclusionHAT effectiveness under degraded conditions depends on the type of communication strategies enacted by the team. Previous findings from studies of all-human teams apply here; however, novel results suggest information requests are particularly important to HAT success during failures. ApplicationUnderstanding the communication strategies of HATs under degraded conditions can inform training protocols to help HATs overcome failures.