#673: Embodied Geometry Fingerprint: An Example of How to Make Implicit Explicit in Multimodality Research on Embodied Learning

Multimodal analysis of embodied learning through video data can be overwhelming for both researchers and practitioners. It requires attending to the spatial and temporal components of verbal and non-verbal interactions simultaneously, while also identifying moments that reveal learning as an embodied phenomenon. For practitioners, it is often unclear how the researchers arrive at these conclusions and whether those conclusions are optimal for the practitioners’ context. This paper presents the development of an embodied geometry fingerprint (EGF), which is an interactive visualization of embodied learning interactions. The EGF enhances the exploration of embodied learning, making the process of identifying salient moments of interaction more explicit. This has the potential to broaden research-practice partnerships, offering educators and other stakeholders a tool to more effectively express and brainstorm ideas, refine and expand data exploration trajectories, as well as foster clarity and transparency of communication and decision-making across the partnership team.