Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/4487
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dc.contributor.authorTissenbaum, Mike
dc.contributor.authorKumar, Vishesh
dc.date.accessioned2020-06-10T13:52:05Z
dc.date.accessioned2020-06-10T20:03:38Z-
dc.date.available2020-06-10T13:52:05Z
dc.date.available2020-06-10T20:03:38Z-
dc.date.issued2019-06
dc.identifier.citationTissenbaum, M. & Kumar, V. (2019). See the Collaboration Through the Code: Using Data Mining and CORDTRA Graphs to Analyze Blocks-Based Programming. In Lund, K., Niccolai, G. P., Lavoué, E., Hmelo-Silver, C., Gweon, G., & Baker, M. (Eds.), A Wide Lens: Combining Embodied, Enactive, Extended, and Embedded Learning in Collaborative Settings, 13th International Conference on Computer Supported Collaborative Learning (CSCL) 2019, Volume 2 (pp. 680-683). Lyon, France: International Society of the Learning Sciences.en_US
dc.identifier.urihttps://doi.dx.org/10.22318/cscl2019.680
dc.identifier.urihttps://repository.isls.org//handle/1/4487-
dc.description.abstractThis paper describes an exploratory study that leveraged data mining, qualitative analysis, and Chronologically-Ordered Representations of Discourse and Tool-Related Activity (CORDTRA) diagrams to identify and analyze key moments in students' collaborative app building during a 12-week computing curriculum. Our analysis showed that two key practices emerged: 1) Students leveraged their past work and tutorials to support their app development, both on their own and with peers; and 2) Students largely developed their own parts of group apps without feedback from peers or referencing prior work. We discuss how patterns revealed in this mixed-methods approach affected how students constructed code, with an eventual goal of identifying how these patterns shaped students' final projects.en_US
dc.language.isoenen_US
dc.publisherInternational Society of the Learning Sciences (ISLS)en_US
dc.titleSee the Collaboration Through the Code: Using Data Mining and CORDTRA Graphs to Analyze Blocks-Based Programmingen_US
dc.typeShort Papersen_US
Appears in Collections:CSCL 2019

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