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|Title:||Analyzing Students’ Synergistic Learning Processes in Physics and CT by Collaborative Discourse Analysis|
|Publisher:||International Society of the Learning Sciences (ISLS)|
|Citation:||Snyder, C., Hutchins, N., Biswas, G., Emara, M., Grover, S., & Conlin, L. (2019). Analyzing Students’ Synergistic Learning Processes in Physics and CT by Collaborative Discourse Analysis. 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 1 (pp. 360-367). Lyon, France: International Society of the Learning Sciences.|
|Abstract:||The introduction of computational modeling into science curricula has been shown to benefit students' learning, however the synergistic learning processes that contribute to these benefits are not fully understood. We study students' synergistic learning of physics and computational thinking (CT) through their actions and collaborative discourse as they develop computational models in a visual block-structured environment. We adopt a case study approach to analyze students synergistic learning processes related to stopping conditions, initialization, and debugging episodes. Our findings show a pattern of evolving sophistication in synergistic reasoning for model-building activities.|
|Appears in Collections:||CSCL 2019|
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