Mining video data
Tracking learners for orchestration and design
DOI:
https://doi.org/10.14742/apubs.2016.836Keywords:
learning analytics, learning spaces, learner trackingAbstract
Learning spaces influence how we act, however there is a lack of systemic research addressing the impact of environments on teaching and learning. In this paper, we introduce a hybrid tracking technique in which a colour model is combined with algorithms to identify human positions, and applied to video data. The aim of identifying patterns of movement that could be used to indicate successful collaboration in open plan learning spaces. We apply the method to a previously analyzed dataset, to demonstrate how multiple analytic techniques can be used to build a complex understanding of learner movement in relation to collaboration and learning. We conclude with suggestions of the ways in which the results could be used by instructors to inform orchestration of complex learning environments, as well as directions for future research.
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Copyright (c) 2024 Kate Thompson, Sarah Howard, Jie Yang, Jun Ma
This work is licensed under a Creative Commons Attribution 4.0 International License.