Healion, D; Russell, S; Cukurova, M; Spikol, D; (2017) Tracing physical movement during practice-based learning through Multimodal Learning Analytics. In: Wise, A and Winne, PH and Lynch, G and Ochoa, X and Molenaar, I and Dawson, S and Hatala, M, (eds.) LAK '17: Proceedings of the Seventh International Learning Analytics & Knowledge Conference. (pp. pp. 588-589). Association for Computing Machinery (ACM): New York, NY, USA.

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Abstract

In this paper, we pose the question, can the tracking and analysis of the physical movements of students and teachers within a Practice-Based Learning (PBL) environment reveal information about the learning process that is relevant and informative to Learning Analytics (LA) implementations? Using the example of trials conducted in the design of a LA system, we aim to show how the analysis of physical movement from a macro level can help to enrich our understanding of what is happening in the classroom. The results suggest that Multimodal Learning Analytics (MMLA) could be used to generate valuable information about the human factors of the collaborative learning process and we propose how this information could assist in the provision of relevant supports for small group work. More research is needed to confirm the initial findings with larger sample sizes and refine the data capture and analysis methodology to allow automation.

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