Physical learning analytics: A multimodal perspective

Publication Type:
Conference Proceeding
ACM International Conference Proceeding Series, 2018, pp. 375 - 379
Issue Date:
Filename Description Size
Martinez-Maldonado-2018-Physical-learning-analytics.pdfPublished version1.62 MB
Adobe PDF
Full metadata record
© 2018 Association for Computing Machinery. The increasing progress in ubiquitous technology makes it easier and cheaper to track students’ physical actions unobtrusively, making it possible to consider such data for supporting research, educator interventions, and provision of feedback to students. In this paper, we reflect on the underexplored, yet important area of learning analytics applied to physical/motor learning tasks and to the physicality aspects of ‘traditional’ intellectual tasks that often occur in physical learning spaces. Based on Distributed Cognition theory, the concept of Internet of Things and multimodal learning analytics, this paper introduces a theoretical perspective for bringing learning analytics into physical spaces. We present three prototypes that serve to illustrate the potential of physical analytics for teaching and learning. These studies illustrate advances in proximity, motion and location analytics in collaborative learning, dance education and healthcare training.
Please use this identifier to cite or link to this item: