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1. Using computational thinking and modeling to build water and watershed literacy

   Caplan, B.; Covitt, B.; Love, G.; Berkowitz, A.R.; Gunckel, K.L.; McClure, C.; Moore, J.C. (January 2021, Connected science learning)

   null (Ed.)

   Engaging students in science learning that integrates disciplinary knowledge and practices such as computational thinking (CT) is a challenge that may represent unfamiliar territory for many teachers. CompHydro Baltimore is a collaborative partnership aimed at enacting Next Generation Science Standards (NGSS)–aligned instruction to support students in developing knowledge and practice reflective of the goals laid out in A Framework for K–12 Science Education (National Research Council 2012) “... that by the end of 12th grade, all students possess sufficient knowledge of science and engineering to engage in public discussion on related issues … and are careful consumers of scientific and technological information related to their everyday lives.” This article presents the results of a partnership that generated a new high school level curriculum and teacher professional development program that tackled the challenge of integrating hydrologic learning with computational thinking as applied to a real-world issue of flooding. CompHydro Baltimore produced Baltimore Floods, a six-lesson high school unit that builds students’ water literacy by engaging them in computational thinking (CT) and modeling practices as they learn about water system processes involved in urban flooding (See Computational Thinking and Associated Science Practices). CompHydro demonstrates that broad partnerships can address these challenges, bringing together the diverse expertise necessary to develop innovative CT-infused science curriculum materials and the teacher supports needed for successful implementation. 

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2. Promoting Computational Thinking through Project-Based Learning

   https://doi.org/doi.org/10.1186/s43031-021-00033-y  

   Shin, N.; Bowers, J.; Krajcik, J.; Damelin, D. (August 2021, Disciplinary and Interdisciplinary Science Education Research)

   null (Ed.)

   This paper introduces project-based learning (PBL) features for developing technological, curricular, and pedagogical supports to engage students in computational thinking (CT) through modeling. CT is recognized as the collection of approaches that involve people in computational problem solving. CT supports students in deconstructing and reformulating a phenomenon such that it can be resolved using an information-processing agent (human or machine) to reach a scientifically appropriate explanation of a phenomenon. PBL allows students to learn by doing, to apply ideas, figure out how phenomena occur and solve challenging, compelling and complex problems. In doing so, students take part in authentic science practices similar to those of professionals in science or engineering, such as computational thinking. This paper includes 1) CT and its associated aspects, 2) The foundation of PBL, 3) PBL design features to support CT through modeling, and 4) a curriculum example and associated student models to illustrate how particular design features can be used for developing high school physical science materials, such as an evaporative cooling unit to promote the teaching and learning of CT. 

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3. Promoting computational thinking through project-based learning

   https://doi.org/10.1186/s43031-021-00033-y  

   Shin, Namsoo; Bowers, Jonathan; Krajcik, Joseph; Damelin, Daniel (August 2021, Disciplinary and Interdisciplinary Science Education Research)

   Abstract This paper introduces project-based learning (PBL) features for developing technological, curricular, and pedagogical supports to engage students in computational thinking (CT) through modeling. CT is recognized as the collection of approaches that  involve people in computational problem solving. CT supports students in deconstructing and reformulating a phenomenon such that it can be resolved using an information-processing agent (human or machine) to reach a scientifically appropriate explanation of a phenomenon. PBL allows students to learn by doing, to apply ideas, figure out how phenomena occur and solve challenging, compelling and complex problems. In doing so, students  take part in authentic science practices similar to those of professionals in science or engineering, such as computational thinking. This paper includes 1) CT and its associated aspects, 2) The foundation of PBL, 3) PBL design features to support CT through modeling, and 4) a curriculum example and associated student models to illustrate how particular design features can be used for developing high school physical science materials, such as an evaporative cooling unit to promote the teaching and learning of CT. 

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4. Science Thinking for Tomorrow Today

   Hsi, S. (October 2017, @Concord)

   This article introduces the Integrated Science Practices Enhanced by Computational Thinking (InSPECT project). We live in an era in which connectivity reigns supreme, and the “Internet of Things,” from self-driving cars to “smart homes,” has become part of our increasingly technological world. Solving big problems like growing sufficient food and developing complex medical treatments requires more than memorizing facts. Knowing how to leverage technology and program computers, formulate and solve problems, generate and interpret various kinds of data, as well as carry out hands-on experiments have become part of an essential skill set. Yet these skills—necessary for solving today’s dynamic, multidisciplinary problems—are rarely taught in a collaborative and integrated way in current K-12 classrooms.We’re investigating ways to teach students how to learn science by doing science, like real scientists—by undertaking authentically complex experiments that rely heavily on digital technology, and often have unexpected outcomes. 

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5. Promoting Computational Thinking Through Science-Engineering Integration Using Computational Modeling

   Basu, Satabdi; McElhaney, Kevin W.; Rachmatullah, Arif; Hutchins, Nicole; Biswas, Gautam; Chiu, Jennie (January 2022, Proceedings of the 16th International Conference of the Learning Sciences (ICLS))

   Careers in science, technology, engineering, and mathematics (STEM) increasingly rely on computational thinking (CT) to explore scientific processes and apply scientific knowledge to the solution of real-world problems. Integrating CT with science and engineering also helps broaden participation in computing for students who otherwise would not have access to CT learning. Using a set of emergent design guidelines for scaffolding integrated STEM and CT curricular experiences, we designed the Water Runoff Challenge (WRC) - a three-week unit that integrates Earth science, engineering, and CT. We implemented the WRC with 99 sixth grade students and analyzed students’ learning artifacts and pre/post assessments to characterize students’ learning process in the WRC. We use a vignette to illustrate how anchoring CT tasks to STEM contexts supported CT learning for a student with low prior CT proficiency. 

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