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Teachers in K-12 science classrooms play a key role in helping their students engage in computational thinking (CT) activities that reflect authentic science practices. However, we know less about how to support teachers in integrating CT into their classrooms. This paper presents a case of one science teacher over three years as she participated in a Design Based Implementation Research project focused on integrating CT into science curriculum. We analyze her professional growth as a designer and instructor as she created and implemented three computationally-enriched science units with the support of our research team. Results suggest that she became more confident in her understanding of and ability, leading to greater integration of CT in the science units. Relationships with the research team and co-design experiences mediated this growth. Findings yield implications for how best to support teachers in collaborative curriculum design. 

Teaching science inquiry practices, especially the more contemporary ones, such as computational thinking practices, requires designing newer learning environments and appropriate pedagogical scaffolds. Using such learning environments, when students construct knowledge about disciplinary ideas using inquiry practices, it is important that they make connections between the two. We call such connections epistemic connections, which are about constructing knowledge using science inquiry practices. In this paper, we discuss the design of a computational thinking integrated biology unit as an Emergent Systems Microworlds (ESM) based curriculum. Using Epistemic Network Analysis, we investigate how the design of unit support students’ learning through making epistemic connections. We also analyze the teacher’s pedagogical moves to scaffold making such connections. This work implies that to support students’ epistemic connections between science inquiry practices and disciplinary ideas, it is critical to design restructured learning environments like ESMs, aligned curricular activities and provide appropriate pedagogical scaffolds. 

Code-first learning entails the use of computer code to learn a concept, and creating computational models is one such effective method for learning about scientific phenomena. Many code-first learning approaches employ the visual block-based programming paradigm in order to be accessible to school children with no prior programming experience, providing them with high- level domain-specific code-blocks that encapsulate the underlying complex programming logic. However, even with the aid of visual clues and the benefit of simpler primitives like “forward” and “repeat,” many phenomena studied in classrooms such as the behavior of gas particles in Kinetic Molecular Theory (KMT) are challenging to describe in code. We hypothesized that code blocks designed from a phenomenological perspective to model the behavior of familiar objects and events would both promote students’ authoring of computational models and their ability to encode and test their beliefs within their models. We created these phenomenological blocks within a code-first gas particle sandbox and integrated it into a KMT lesson plan. Two high school teachers taught this curriculum to 121 students, from which we gathered and analyzed video footage from lesson activities and student focus groups. We found that the phenomenological blocks gave students the ability to start programming right away and to express their intuitive understanding of KMT through computational models. This exploratory study demonstrates the potential for phenomenological programming to broaden the application and accessibility of code-first computational modeling for learning scientific phenomena. 

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.