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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. 

Abstract The Institute for Student‐AI Teaming (iSAT) addresses the foundational question:how to promote deep conceptual learning via rich socio‐collaborative learning experiences for all students?—a question that is ripe for AI‐based facilitation and has the potential to transform classrooms. We advance research in speech, computer vision, human‐agent teaming, computer‐supported collaborative learning, expansive co‐design, and the science of broadening participation to design and study next generation AI technologies (called AI Partners) embedded in student collaborative learning teams in coordination with teachers. Our institute ascribes to theoretical perspectives that aim to create a normative environment of widespread engagement through responsible design of technology, curriculum, and pedagogy in partnership with K–12 educators, racially diverse students, parents, and other community members.