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Title: Automated Tracking of Student Activities in a Makerspace Using Motion Sensor Data
Authors: Sung, Gahyun
Yoo, Tyler
Chng, Edwin
Yang, Stephanie
Schneider, Bertrand
Keywords: CSCL
Issue Date: Jun-2021
Publisher: International Society of the Learning Sciences
Citation: Sung, G., Yoo, T., Chng, E., Yang, S., & Schneider, B. (2021). Automated Tracking of Student Activities in a Makerspace Using Motion Sensor Data. In Hmelo-Silver, C. E., De Wever, B., & Oshima, J. (Eds.), Proceedings of the 14th International Conference on Computer-Supported Collaborative Learning - CSCL 2021 (pp. 185-188). Bochum, Germany: International Society of the Learning Sciences.
Abstract: Learning inside makerspaces can be difficult to track and support. Using Kinect data collected from students enrolled in a course for making, we explore ways to track student learning trajectories in an automated way. Namely, by transforming our data into a set of action sequences that span a semester, we are able to find that discouraged students display a statistically distinct type of activity pattern already in the first two weeks. Generating metrics on makerspace use, we also find that time spent alone and the number of transitions between stations are significant indicators for discouragement and motivation levels. We argue that high-frequency location data could provide an accessible, meaningful overview of student learning in a makerspace to all stakeholders, and conclude with limitations and future directions.
Appears in Collections:ISLS Annual Meeting 2021

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