Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/1651
Title: See the Collaboration Through the Code: Using Data Mining and CORDTRA Graphs to Analyze Blocks-Based Programming
Authors: Tissenbaum, Mike
Kumar, Vishesh
Issue Date: Jun-2019
Publisher: International Society of the Learning Sciences (ISLS)
Citation: Tissenbaum, 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., Gweon, C. H., & 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.
Abstract: This 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.
URI: https://doi.dx.org/10.22318/cscl2019.680
https://repository.isls.org//handle/1/1651
Appears in Collections:CSCL 2019

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