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1. Coherence across conceptual and computational representations of students’ scientific models

   Hutchins, N.M. ; Basu, S. ; McElhaney, K. ; Chiu, J. ; Fick, S. ; Zhang, N. ; Biswas, G. ( January 2021 , 15th International Conference of the Learning Sciences)

   null (Ed.)

   We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT. 

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2. Coherence across conceptual and computational representations of students’ scientific models

   Hutchins, N.M. ; Basu, S. ; McElhaney, K. ; Chiu, J. ; Fick, S. ; Zhang, N. ; Biswas, G. ( June 2021 , Computersupported collaborative learning)

   de Vries, E. (Ed.)

   We articulate a framework for characterizing student learning trajectories as they progress through a scientific modeling curriculum. By maintaining coherence between modeling representations and leveraging key design principles including evidence-centered design, we develop mechanisms to evaluate student science and computational thinking (CT) proficiency as they transition from conceptual to computational modeling representations. We have analyzed pre-post assessments and learning artifacts from 99 6th grade students and present three contrasting vignettes to illustrate students’ learning trajectories as they work on their modeling tasks. Our analysis indicates pathways that support the transition and identify domain-specific support needs. Our findings will inform refinements to our curriculum and scaffolding of students to further support the integrated learning of science and CT. 

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3. 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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4. 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)

   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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5. Designing biomimetic robots: iterative development of an integrated technology design curriculum

   https://doi.org/10.1007/s11423-021-10061-0  

   Bernstein, Debra ; Puttick, Gillian ; Wendell, Kristen ; Shaw, Fayette ; Danahy, Ethan ; Cassidy, Michael ( November 2021 , Educational technology research and development)

   In most middle schools, learning is segregated by discipline. Yet interdisciplinary approaches have been shown to cultivate creative thinking, support problem solving, and develop interest while supporting knowledge gains (NAE & NRC in STEM Integration in K-12 Education: Status, Prospects, and an Agenda for Research. National Academies Press, Washington, 2014). The Designing Biomimetic Robots project emphasizes problem-based learning to integrate engineering, science, and computational thinking (CT). During a 3 to 4-week unit, students study the natural world to learn how animals accomplish different tasks, then design a robot inspired by what they learned. The project engages students in science, engineering, and CT practices. Over the course of a 3-year project, we used a design-based research approach to: (1) identify and describe strategies and challenges that emerge from integrated curriculum design, (2) explicate how a balance of integrated disciplines can provide opportunities for student participation in science, engineering, and CT practices, and (3) explore how a technology design task can support students’ participation in integrated learning. Data from three focal groups (one from each year of the project) suggest that a focused design task, supported by explicit and targeted supports for science, CT, and engineering practices, led to a student technology design process that was driven by disciplinary understanding. This work highlights the importance of drawing out and prioritizing alignments between disciplines (Barber in Educ Des, 2(8), 2015), to enable integrated learning. Additionally, this work demonstrates how a technology design task can support student learning across disciplines, and how engaging in CT practices can further help students draw these connections.

    

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