Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/7312
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dc.contributor.authorSung, Gahyun
dc.contributor.authorYoo, Tyler
dc.contributor.authorChng, Edwin
dc.contributor.authorYang, Stephanie
dc.contributor.authorSchneider, Bertrand
dc.coverage.spatialBochum, Germanyen_US
dc.date.accessioned2021-10-09T15:44:06Z
dc.date.accessioned2021-10-09T19:46:28Z-
dc.date.available2021-10-09T15:44:06Z
dc.date.available2021-10-09T19:46:28Z-
dc.date.issued2021-06
dc.identifier.citationSung, 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.en_US
dc.identifier.urihttps://doi.dx.org/10.22318/cscl2021.185
dc.identifier.urihttps://repository.isls.org//handle/1/7312-
dc.description.abstractLearning 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.en_US
dc.format.extentpp. 185-188
dc.language.isoen_US
dc.publisherInternational Society of the Learning Sciencesen_US
dc.relation.ispartofProceedings of the 14th International Conference on Computer-Supported Collaborative Learning - CSCL 2021en_US
dc.subjectCSCLen_US
dc.titleAutomated Tracking of Student Activities in a Makerspace Using Motion Sensor Dataen_US
dc.typeConference Paperen_US
dc.typeShort Paperen_US
Appears in Collections:ISLS Annual Meeting 2021

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