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Analytics for face-to-face learning

Despite the online revolution, many forms of learning require collocated, embodied expertise. CIC is at the forefront of techniques to provide automated feedback on collocated teamwork.

While the pandemic has driven a lot of teaching online, certain forms of learning are impossible to replicate virtually. Hopefully, as we gradually return to campus, students and teachers will once again enjoy the unique energy and experience of being together, working as a team, and using our bodies as well as our minds to work with people and physical material.  

While learning analytics started out as the analysis of data from “online activity” (discussions; watching videos; creating documents, etc.), today, increasingly cheap sensors mean that collocation ≠ digitally invisibleThere are several updates to share on our long term collaboration with the School of Nursing & Midwifery, which has been our vehicle for building and testing the new possibilities. 

Firstly, that we have a dynamic new video for a general audience, illustrating the progress we’ve made to date:  

Secondly, we’re delighted to say that the Australian Research Council has recognised our advances, awarding a joint Discovery Project to UTS (CIC and Doug Elliott, Professor of Nursing) and Monash. The Human-Centred Teamwork Analytics projectin collaboration with long-time colleagues Dragan Gasevic & Roberto Martinez-Maldonado (now moved from CIC to Monash), will extend two CIC PhDs by Vanessa Echeverria and Gloria Fernandez-Nieto. Here’s the quick summary: 

This project aims to develop methods to assist the assessment and improvement of collocated teamwork, by making multimodal activity traces visible and available for computational analysis. This project expects to bridge the gap between promising sensing technologies and the dearth of tools to automatically assess teamwork. Expected outcomes include co-design and modelling methodologies for human-centred analytics that map from low-level data to higher-order constructs to enable non-data science savvy users to get actionable insights into multimodal team traces. This research aims to provide significant benefits to Australia, with communication and teamwork being two of the topmost critical skills required by Australian employers. 

 Thirdly, this applied research is being disseminated in the leading international research venuesIn March we’ll be presenting at LAK’21: 

Fernandez-Nieto, G., Martinez-Maldonado, R., Kitto K. and Buckingham Shum, S. (2021). Modelling Spatial Behaviours in Clinical Team Simulations using Epistemic Network Analysis: Methodology and Teacher Evaluation. Proceedings of 11th International Conference on Learning Analytics & Knowledge, (Online, 12-16 April, 2021). ACM. [Preprint PDF

 and we scooped AIED 2020 Best Paper at the top international conference for AI in Education: 

Martinez-Maldonado, R., Echeverria, V., Schulte, J., Shibani, A., Mangaroska, K. and Buckingham Shum, S. (2020), Moodoo: Indoor Positioning Analytics for Characterising Classroom Teaching. In Proceedings of the 21st International Conference on Artificial Intelligence in Education (AIED2020), (Online, July 6–10, 2020). Springer, pp.360-373. [Preprint PDF