Abstract
Introducing computational modeling into STEM classrooms can provide opportunities for the simultaneous learning of computational thinking (CT) and STEM. This paper describes the C2STEM modeling environment for learning physics, and the processes students can apply to their learning and modeling tasks. We use an unsupervised learning method to characterize student learning behaviors and how these behaviors relate to learning gains in STEM and CT.
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Acknowledgments
We thank Marian Rushdy, Naveed Mohammed, and our other collaborators at Vanderbilt University, Stanford University, Salem State University, SRI International, and ETS. This research is supported by NSF grant #1640199.
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Hutchins, N., Biswas, G., Grover, S., Basu, S., Snyder, C. (2019). A Systematic Approach for Analyzing Students’ Computational Modeling Processes in C2STEM. In: Isotani, S., Millán, E., Ogan, A., Hastings, P., McLaren, B., Luckin, R. (eds) Artificial Intelligence in Education. AIED 2019. Lecture Notes in Computer Science(), vol 11626. Springer, Cham. https://doi.org/10.1007/978-3-030-23207-8_22
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DOI: https://doi.org/10.1007/978-3-030-23207-8_22
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