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1. Workshops and Co-design Can Help Teachers Integrate Computational Thinking into Their K-12 STEM Classes

   Wu, S.; Peel, A.; Bain, C.; Anton, G.; Horn, M.; Wilensky, U. (April 2020, Proceedings of International Conference on Computational Thinking Education 2020)

   Kong, S.C. (Ed.)

   This work aims to help high school STEM teachers integrate computational thinking (CT) into their classrooms by engaging teachers as curriculum co-designers. K-12 teachers who are not trained in computer science may not see the value of CT in STEM classrooms and how to engage their students in computational practices that reflect the practices of STEM professionals. To this end, we developed a 4-week professional development workshop for eight science and mathematics high school teachers to co-design computationally enhanced curriculum with our team of researchers. The workshop first provided an introduction to computational practices and tools for STEM education. Then, teachers engaged in co-design to enhance their science and mathematics curricula with computational practices in STEM. Data from surveys and interviews showed that teachers learned about computational thinking, computational tools, coding, and the value of collaboration after the professional development. Further, they were able to integrate multiple computational tools that engage their students in CT-STEM practices. These findings suggest that teachers can learn to use computational practices and tools through workshops, and that teachers collaborating with researchers in co-design to develop computational enhanced STEM curriculum may be a powerful way to engage students and teachers with CT in K-12 classrooms. 

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2. 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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3. A Principled Approach to Designing Assessments That Integrate Science and Computational Thinking

   https://doi.org/10.22318/cscl2018.384  

   Basu, S.; McElhaney, K. W.; Grover, S.; Harris, C. J.; Biswas, G. (July 2018, 13th International Conference of the Learning Sciences (ICLS))

   There is increasing interest in broadening participation in computational thinking (CT) by integrating CT into pre-college STEM curricula and instruction. Science, in particular, is emerging as an important discipline to support integrated learning. This highlights the need for carefully designed assessments targeting the integration of science and CT to help teachers and researchers gauge students’ proficiency with integrating the disciplines. We describe a principled design process to develop assessment tasks and rubrics that integrate concepts and practices across science, CT, and computational modeling. We conducted a pilot study with 10 high school students who responded to integrative assessment tasks as part of a physics-based computational modeling unit. Our findings indicate that the tasks and rubrics successfully elicit both Physics and CT constructs while distinguishing important aspects of proficiency related to the two disciplines. This work illustrates the promise of using such assessments formatively in integrated STEM and computing learning contexts. 

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4. Developing Pedagogical Practices That Support Disciplinary Practices When Integrating Computer Science Into Elementary School Curriculum

   Sullivan, Florence; Enrique Suárez; Emrah Pektas; and Lian Duan. (June 2020, Proceedings of the 14th International Conference on the Learning Sciences)

   There is a growing movement seeking to promote Computer Science (CS) and Computational Thinking (CT) across K-8 education. While advantageous for supporting student learning through engaging in complex and interdisciplinary learning, integrating CS/CT into the elementary school curriculum can pose curricular and pedagogical challenges. For one, teachers themselves must understand the concepts and disciplinary practices associated with CS/CT and the other content areas being integrated, as well as develop a related pedagogical repertoire. This study addresses how two 3rd grade teachers made sense of the intersection of disciplinary practices and pedagogical practices to support student learning. We present preliminary findings from a Research-Practice Partnership that worked with elementary teachers to integrate aspects of CS/CT practice into existing content areas. We identified two main disciplinary activities that drove their curriculum design and pedagogical practices: (1) the importance of productive frustration and failure; and (2) the importance of precision 

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5. Studying the Interactions Between Science, Engineering, and Computational Thinking in a Learning-by-Modeling Environment.

   https://doi.org/10.1007/978-3-030-52237-7_48  

   Zhang, N.; Biswas, G.; McElhaney, K.; Basu, S.; McBride, E.; Chiu, J. (June 2020, In: Bittencourt I., Cukurova M., Muldner K., Luckin R., Millán E. (eds) Artificial Intelligence in Education. AIED 2020. Lecture Notes in Computer Science.)

   Computational Thinking (CT) can play a central role in fostering students' integrated learning of science and engineering. We adopt this framework to design and develop the Water Runoff Challenge (WRC) curriculum for lower middle school students in the USA. This paper presents (1) the WRC curriculum implemented in an integrated computational modeling and engineering design environment and (2) formative and summative assessments used to evaluate learner’s science, engineering, and CT skills as they progress through the curriculum. We derived a series of performance measures associated with student learning from system log data and the assessments. By applying Path Analysis we found significant relations between measures of science, engineering, and CT learning, indicating that they are mutually supportive of learning across these disciplines. 

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