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dc.contributor.authorGunckel, Kristin, l.
dc.contributor.authorCovitt, Beth
dc.contributor.authorBerkowitz, Alan
dc.contributor.authorCaplan, Bess
dc.contributor.authorMoore, John
dc.date.accessioned2022-08-08T19:32:55Z
dc.date.available2022-08-08T19:32:55Z
dc.date.issued2022-09-20
dc.identifier.citationGunckel, K. L., Covitt, B. A., Berkowitz, A. R., Caplan, B., & Moore, J. C. (2022). Computational thinking for using models of water flow in environmental systems: Intertwining three dimensions in a learning progression. Journal of Research in Science Teaching(59), 1159-1203.en_US
dc.identifier.issn0022-4308
dc.identifier.doi10.1002/tea.21755
dc.identifier.urihttp://hdl.handle.net/10150/665561
dc.description.abstractNearly a decade ago, the Framework for K-12 Science Education argued for the need to intertwine science and engineering practices, disciplinary core ideas, and crosscutting concepts in performance expectations. However, there are few empirical examples for how intertwining three dimensions facilitates learning. In this study, we used a learning progressions approach to examine how student engagement in computational thinking (science and engineering practice) intertwines with learning about the flow of water through environmental systems (disciplinary core ideas) and understanding of systems and system models (crosscutting concept). We developed three secondary-level curriculum units situated in current groundwater contamination and urban flooding contexts. Units included specially designed NetLogo computational models. Post-assessments measured student performances in computational thinking processes and understanding of hydrologic systems. Using item response theory in our analysis, we identified distinct levels of performance on a learning progression. At the lower end, Literal Model Users interacted with models and manipulated model interfaces to achieve a specified goal. In the middle, Model Technicians used computational models to solve real-world problems. At the upper end, Principle-Based Model Users used computational thinking processes and principles related to systems modeling and hydrology to explain how the models worked to predict water flow. Differences between performances of Literal Model Users, Model Technicians, and Principle-based Model Users reflected shifts in how students made sense of the systems and system models crosscutting concept. These shifts in performances aligned with progress in computational thinking practices and finally with use of hydrology disciplinary core ideas. These findings contribute to understanding of how science and engineering practices, disciplinary core ideas, and crosscutting concepts intertwine during learning; how computational thinking practices develop; and how computational thinking about system models facilitates learning for environmental science literacy.en_US
dc.description.sponsorshipThis material is based upon work supported by the National Science Foundation DRL – 1543228 Comp Hydro: Integrating Data Computation and Visualization to Build Model-based Water Literacy. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.en_US
dc.language.isoenen_US
dc.publisherWileyen_US
dc.rights© 2022 National Association for Research in Science Teaching.en_US
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en_US
dc.subjectcomputational thinkingen_US
dc.subjectsystems and system modelsen_US
dc.subjectthree-dimensional learningen_US
dc.subjectlearning progressionsen_US
dc.subjectwater in environmental systemsen_US
dc.subjectenvironmental science literacyen_US
dc.titleComputational Thinking for Using Models of Water Flow in Environmental Systems: Intertwining Three Dimensions in a Learning Progressionen_US
dc.typeArticleen_US
dc.contributor.departmentDepartment of Teaching, Learning, & Sociocultural Studies, University of Arizonaen_US
dc.identifier.journalJournal of Research in Science Teachingen_US
dc.description.note12 month embargo; first published: 22 February 2022en_US
dc.description.collectioninformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.en_US
dc.eprint.versionFinal accepted manuscripten_US


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