About the Event
The monthly QE Webinar Series showcases emerging research and exciting new developments in Quantitative Ethnography. These one-hour events begin with a 30-minute presentation by a scholar from the QE community, followed by 30 minutes of moderated discussion. You can attend live via video-conferencing software!, and you will also be able to access recordings of the presentations shortly after they occur. Attendance is free and open to the public, but registration is required to receive each event’s link. Any enquiries regarding these webinars please email email@example.com.
Making Sense of Collocated Teamwork Activity: The Multimodal Matrix as a Quantitative Ethnography Methodology
3 December 2020 – 3:00 PM (CST), 9:00 PM (GMT), 8:00 AM +1 day (AEDT)
Collocated, face-to-face teamwork remains a pervasive mode of working and learning, which is hard to replicate online. In team-based situations, learners’ embodied, multimodal interaction with each other and with digital and material resources has been studied by researchers, but due to its complexity, has remained opaque to automated analysis. The ready availability of sensors makes it increasingly affordable to instrument work spaces to automatically capture activity traces to study teamwork and groupwork. Yet, a key challenge is the enrichment of these multiple and intertwined quantitative data streams with the qualitative insights needed to make sense of them. In this seminar, we will discuss our inroads into giving meaning to multimodal group data. We have followed a human-centred approach to design meaningful end-user interfaces that convert multimodal data into data stories. Based on Quantitative Ethnography principles, we developed a modelling technique, termed the Multimodal Matrix, to grounding quantitative data in the semantics derived from a qualitative interpretation of the context from which it arises. We will present practical examples in the context of high-fidelity clinical simulations in which multimodal data (physiological, positioning, and logged actions) have been transformed into learning analytics interfaces that support teachers’ and learners’ reflection.