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For nearly two decades, conversational agents have been used to structure group interactions in online chat-based environments. More recently, this form of dynamic support for collaborative learning has been extended to physical spaces using a combination of multimodal sensing technologies and instrumentation installed within a physical space. This demo extends the reach of dynamic support for collaboration still further through an application of what has recently been termed on-device machine learning, which enables a portable form of multimodal detection to trigger real-time responses. 

Socially shared regulation (SSRL) has been recognized as a contributing factor to successful collaborative learning. In this paper, we adopted a process-oriented approach to examine how students deliberate for SSRL through different regulatory triggers in a collaborative learning context. More specifically, this study examines the relationship between different types of regulatory and deliberative characteristics of interactions and then explores their sequential patterns through cognitive and emotional triggers. The study involved ten triads of secondary students (N=30) working on a collaborative learning task. The process mining results showed that following regulatory triggers, groups switched to more metacognitive and socio-emotional interactions as they adopted control strategies, such as defining problems, establishing strategies, and providing social support. This study not only contributes to a better understanding of SSRL by exploring learners’ deliberative negotiation but also presents a novel fine-grain video analysis approach to examine SSRL in collaborative learning. 

At its core, collaboration is about bringing diverse perspectives together to create something new. Diversity may arise along a multiplicity of dimensions, leading to some very similar challenges, and other dimension-specific challenges, each of which require discrete skills to address. Interdisciplinary collaboration, while understudied, has particular workplace relevance. This research seeks to understand what is specific to interdisciplinary collaboration as part of a broader agenda to operationalize key underlying skills that enable interdisciplinary collaboration and subsequently assess and support interdisciplinary collaboration, both in the classroom and in the workplace. The aim of this poster presentation is to engage the community in an intellectual exchange about underlying questions to inform work in progress. 

Understanding abstract concepts in mathematics has continuously presented as a challenge, but the use of directed and spontaneous gestures has shown to support learning and ground higher-order thought. Within embodied learning, gesture has been investigated as part of a multimodal assemblage with speech and movement, centering the body in interaction with the environment. We present a case study of one dyad’s undertaking of a robotic arm activity, targeting learning outcomes in matrix algebra, robotics, and spatial thinking. Through a body syntonicity lens and drawing on video and pre- and post- assessment data, we evaluate learning gains and investigate the multimodal processes contributing to them. We found gesture, speech, and body movement grounded understanding of vector and matrix operations, spatial reasoning, and robotics, as anchored by the physical robotic arm, with implications for the design of learning environments that employ directed gestures.