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  1. Abstract

    Developing and using models to make sense of phenomena or to design solutions to problems is a key science and engineering practice. Classroom use of technology-based tools can promote the development of students’ modelling practice, systems thinking, and causal reasoning by providing opportunities to develop and use models to explore phenomena. In previous work, we presented four aspects of system modelling that emerged during our development and initial testing of an online system modelling tool. In this study, we provide an in-depth examination and detailed evidence of 10th grade students engaging in those four aspects during a classroom enactmentmore »of a system modelling unit. We look at the choices students made when constructing their models, whether they described evidence and reasoning for those choices, and whether they described the behavior of their models in connection with model usefulness in explaining and making predictions about the phenomena of interest. We conclude with a set of recommendations for designing curricular materials that leverage digital tools to facilitate the iterative constructing, using, evaluating, and revising of models.

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  2. 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 authenticmore »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. We face complex global issues such as climate change that challenge our ability as humans to manage them. Models have been used as a pivotal science and engineering tool to investigate, represent, explain, and predict phenomena or solve problems that involve multi-faceted systems across many fields. To fully explain complex phenomena or solve problems using models requires both systems thinking (ST) and computational thinking (CT). This study proposes a theoretical framework that uses modeling as a way to integrate ST and CT. We developed a framework to guide the complex process of developing curriculum, learning tools, support strategies, and assessmentsmore »for engaging learners in ST and CT in the context of modeling. The framework includes essential aspects of ST and CT based on selected literature, and illustrates how each modeling practice draws upon aspects of both ST and CT to support explaining phenomena and solving problems. We use computational models to show how these ST and CT aspects are manifested in modeling.« less
    Free, publicly-accessible full text available January 1, 2023
  4. Free, publicly-accessible full text available January 1, 2023
  5. Gresalfi, M. ; Horn, I. S. (Ed.)
    There is broad belief that preparing all students in preK-12 for a future in STEM involves integrating computing and computational thinking (CT) tools and practices. Through creating and examining rich “STEM+CT” learning environments that integrate STEM and CT, researchers are defining what CT means in STEM disciplinary settings. This interactive session brings together a diverse spectrum of leading STEM researchers to share how they operationalize CT, what integrated CT and STEM learning looks like in their curriculum, and how this learning is measured. It will serve as a rich opportunity for discussion to help advance the state of the fieldmore »of STEM and CT integration.« less
  6. Gresalfi, M. ; Horn, I. S. (Ed.)
    As human society advances, new scientific challenges are constantly emerging. The use of systems thinking (ST) and computational thinking (CT) can help elucidate these problems and bring us closer to a possible solution. The construction and use of models is one of the most widely used tools when trying to understand systems. In this paper, we examine four case studies of student pairs who were engaged in building and using system models in an NGSS-aligned project-based learning unit on chemical kinetics. Using a theoretical framework that describes how CT and ST practices are manifested in the modeling process we examinemore »the progression of students’ models during their model revisions and explore strategies they employ to overcome modeling challenges they face. We discuss some suggestions to scaffold students’ progression in constructing computational system models and prepare teachers to support their students in engaging in CT and ST practices.« less
  7. Gresalfi, M. ; Horn, I. S. (Ed.)
    Computational Thinking (CT) is increasingly being targeted as a pedagogical goal for science education. As such, researchers and teachers should collaborate to scaffold student engagement with CT alongside new technology and curricula. We interviewed two high school teachers who implemented a unit using dynamic modeling software to examine how they supported student engagement with CT through modeling practices. Based on their interviews, they believed that they supported student engagement in CT and modeling through preliminary activities, conducting classroom demonstrations of the phenomenon, and engaging students in model revisions through dialogue.