Please use this identifier to cite or link to this item: https://repository.isls.org//handle/1/941
Title: Investigating Student Generated Computational Models of Science
Authors: Basu, Satabdi
Dukeman, Anton
Kinnebrew, John S.
Biswas, Gautam
Sengupta, Pratim
Issue Date: Jun-2014
Publisher: Boulder, CO: International Society of the Learning Sciences
Citation: Basu, S., Dukeman, A., Kinnebrew, J. S., Biswas, G., & Sengupta, P. (2014). Investigating Student Generated Computational Models of Science. In Joseph L. Polman, Eleni A. Kyza, D. Kevin O'Neill, Iris Tabak, William R. Penuel, A. Susan Jurow, Kevin O'Connor, Tiffany Lee, and Laura D'Amico (Eds.). Learning and Becoming in Practice: The International Conference of the Learning Sciences (ICLS) 2014. Volume 2. Colorado, CO: International Society of the Learning Sciences, pp. 1097-1101.
Abstract: Computational Thinking (CT) is now considered a core competency in problem formulation and problem solving. In spite of the known synergies between CT and science ed- ucation, integrating CT in K-12 science classrooms is challenging. This paper reports a teach- er-led, multi-domain classroom study conducted with 6th graders using CTSiM a learning environment for CT and middle school science. Pre-post comparisons show that students made significant gains, both in terms of computational thinking and the relevant science con- cepts. Furthermore, we developed measures for analyzing students' computational models, and our results show that as challenges faced decreased, model accuracy not only increased in general, but also became a good predictor of individual learning gains.
URI: https://doi.dx.org/10.22318/icls2014.1097
https://repository.isls.org//handle/1/941
Appears in Collections:ICLS2014

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