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1. How Teachers Support Student Computational Thinking Practices

   https://doi.org/10.22318/icls2020.2343  

   Bowers, J.; Shin, N.; Krajcik, J. (June 2020, How Teachers Support Student Computational Thinking Practices)

   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. 

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2. How Teachers Support Student Computational Thinking Practices

   https://doi.org/https://doi.dx.org/10.22318/icls2020.2343 https://repository.isls.org//handle/1/6551  

   Bowers, J.; Shin, N.; Krajcik, J. (June 2020, The Interdisciplinarity of the Learning Sciences, 14th International Conference of the Learning Sciences (ICLS) 2020)

   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. 

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3. Back to Computational Transparency: Co-designing with Teachers to Integrate Computational Thinking in Science Classrooms

   Bain, Connor; Anton, Gabriella; Horn, Michael; Wilensky, Uri (June 2020, International Conference of the Learning Sciences)

   Integrating computational thinking (CT) in the science classroom presents the opportunity to simultaneously broaden participation in computing, enhance science content learning, and engage students in authentic scientific practice. However, there is a lot more to learn on how teachers might integrate CT activities within their existing curricula. In this work, we describe a process of co-design with researchers and teachers to develop CT-infused science curricula. Specifically, we present a case study of one veteran physics teacher whose conception of CT during a professional development institute changed over time. We use this case study to explore how CT is perceived in physics instruction, a field that has a long history of computational learning opportunities. We also discuss how a co-design process led to the development of a lens through which to identify fruitful opportunities to integrate CT activities in physics curricula which we term computational transparency–purposefully revealing the inner workings of computational tools that students already use in the classroom. 

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4. Vectors of CT-ification: Integrating Computational Activities in STEM Classrooms.

   https://doi.org/10.1145/3328778.3372674  

   Bain, C. & (April 2020, Proceedings of tThe 51st ACM Technical Symposium on Computer Science Education)

   null (Ed.)

   While the Next Generation Science Standards set an expectation for developing computer science and computational thinking (CT) practices in the context of science subjects, it is an open question as to how to create curriculum and assessments that develop and measure these practices. In this poster, we show one possible solution to this problem: to introduce students to computer science through infusing computational thinking practices ("CT-ifying") science classrooms. To address this gap, our group has worked to explicitly characterize core CT-STEM practices as specific learning objectives and we use these to guide our development of science curriculum and assessments. However, having these learning objectives in mind is not enough to actually create activities that engage students in CT practices. We have developed along with science teachers, a strategy of examining a teacher’s existing curricula and identifying potential activities and concepts to “CT-ify”, rather than creating entirely new curricula from scratch by using the concept of scale as an “attack vector” to design science units that integrate computational thinking practices into traditional science curricula. We demonstrate how we conceptualize four different versions of scale in science, 1. Time, 2. Size, 3. Number, and 4. Repeatability. We also present examples of these concepts in traditional high school science curricula that hundreds of students in a large urban US school district have used. 

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5. Computational Classrooms: A Research-Based Approach to Designing a Computer Science Course for Elementary and Middle School Teachers

   Rivera, J; Radoff, J (March 2025, National Association for Research in Science Teaching)

   To address the complex threats to Earth's life-sustaining systems, students need to learn core concepts and practices from various disciplines, including mathematics, civics, science, and, increasingly, computer science (NRC, 2012; United Nations, 2021). Schools must therefore equip students to navigate and integrate these disciplines to tackle real-world problems. Over the past two decades, STEM educators have advocated for an interdisciplinary approach, challenging traditional barriers between subjects and emphasizing contextualized real-world issues (Hoachlander & Yanofsky, 2011; Vasquez et al., 2013; Ortiz-Revilla et al., 2020; Honey et al., 2014; Takeuchi et al., 2020). Despite extensive evidence supporting integrated approaches to STEM education, subject boundaries remain, with disciplines often taught separately and computer science and computational thinking (CS & CT) not consistently included in elementary and middle school curricula. In today's digital age, CS and CT are crucial for a well-rounded education and for addressing sustainability challenges (ESSA, 2015; NGSS Lead States, 2013; NRC, 2012). While there's consensus on the importance of introducing computational concepts and practices to elementary and middle school students, integrating them into existing curricula poses significant challenges, including how to effectively support teachers to deliver inquiry instruction confidently and competently (Ryoo, 2019). Existing frameworks and tools for teaching CS and CT often focus on maintaining fidelity to canonical concepts and formalized taxonomies rather than on practical applications (Grover & Pea, 2013; Kafai et al., 2020; Wilkerson et al., 2020). This focus can lead teachers to learn terminology without fully understanding its relevance or application in different contexts. In response, some researchers suggest using a learning sciences perspective to consider “how the complexity of everyday spaces of learning shapes what counts, and what should be counted, as ‘computational thinking’” (Wilkerson et al., 2020, p. 265). These scholars emphasize the importance of drawing on learners’ everyday experiences and problems to make computational practices more meaningful and contextually relevant for both teachers and their students. Thus, this paper aims to address the following question: How can we design learning experiences for in-service teachers that support (1) their authentic engagement with computational concepts, practices, and tools and (2) more effective integration within classroom contexts? In the limited space of this proposal, we primarily address part 1. 

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