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There has been significant progress in increasing the access to computing education for many K-12 students, including states adopting computer science (CS) standards and/or requiring CS courses. This includes the creation of block-based programming languages to make programming more accessible to younger students. Despite this progress, a new challenge has emerged: Students often struggle to transfer conceptual knowledge when transitioning to a new programming language (e.g., transitioning to a text-based programming after learning a block-based programming language). This poster presents the results of teacher interviews regarding the examples of knowledge transfer they observe in their classrooms. These interviews are part of an overarching project that aims to address the challenge of knowledge transfer between programming languages by developing a framework to support such transfer and deliver curricular supports that can be used to aid students’ productive knowledge transfer between programming languages. 

With the increased demand for introducing computational thinking (CT) in K-12 classrooms, educational researchers are developing integrated lesson plans that can teach CT fundamentals in non- computing specific classrooms. Although these lessons reach more students through the core curriculum, proper evaluation methods are needed to ensure the quality of the design and integration. As part of a research practice partnership, we work to infuse research- backed curricula into science courses. We find a three-pronged approach of evaluation can help us make better decisions on how to improve experimental curricula for active classrooms. This CEO model uses three data sources (student code traces, exit ticket responses, and field observations) as a triangulated approach that can be used to identify programming behavior among novice developers, preferred task ordering for the assignment, and scaffolding recommendations to teachers. This approach allows us to evaluate the practical implementations of our initiative and create a focused approach for designing more effective lessons. 

Computational Thinking (CT) is being infused into curricula in a variety of core K-12 STEM courses. As these topics are being introduced to students without prior programming experience and are potentially taught by instructors unfamiliar with programming and CT, appropriate lesson design might help support both students and teachers. “Use-Modify-Create" (UMC), a CT lesson progression, has students ease into CT topics by first “Using" a given artifact, “Modifying" an existing one, and then eventually “Creating" new ones. While studies have presented lessons adopting and adapting this progression and advocating for its use, few have focused on evaluating UMC’s pedagogical effectiveness and claims. We present a comparison study between two CT lesson progressions for middle school science classes. Students participated in a 4-day activity focused on developing an agent-based simulation in a block-based programming environment. While some classrooms had students develop code on days 2-4, others used a scaffolded lesson plan modeled after the UMC framework. Through analyzing student’s exit tickets, classroom observations, and teacher interviews, we illustrate differences in perception of assignment difficulty from both the students and teachers, as well as student perception of artifact “ownership" between conditions.