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Computational modeling of scientific systems is a powerful approach for fostering science and computational thinking (CT) proficiencies. However, the role of programming activities for this synergistic learning remains unclear. This paper examines alternative ways to engage with computational models (CM) beyond programming. Students participated in an integrated Science, Engineering, and Computational Modeling unit through one of three distinct instructional versions: Construct a CM, Interpret-and-Evaluate a CM, and Explore-and-Evaluate a simulation. Analyzing 188 student responses to a science+CT embedded assessment task, we investigate how science proficiency and instructional versions related to pseudocode interpretation and debugging performances. We found that students in the Explore-and-Evaluate a simulation outperformed students in the programming-based versions on the CT assessment items. Additionally, science proficiency strongly predicted students’ CT performance, unlike prior programming experience. These results highlight the promise of diverse approaches for fostering CT practices with implications for STEM+C instruction and assessment design. 

Computational models (CMs) offer pre-college students opportunities to integrate STEM disciplines with computational thinking in ways that reflect authentic STEM practice. However, not all STEM teachers and students are prepared to teach or learn programming skills required to construct CMs. To broaden participation in computing, we propose instructional approaches that integrate STEM with CMs without requiring students to program, thereby alleviating challenges associated with learning how to program. 

Careers in science, technology, engineering, and mathematics (STEM) increasingly rely on computational thinking (CT) to explore scientific processes and apply scientific knowledge to the solution of real-world problems. Integrating CT with science and engineering also helps broaden participation in computing for students who otherwise would not have access to CT learning. Using a set of emergent design guidelines for scaffolding integrated STEM and CT curricular experiences, we designed the Water Runoff Challenge (WRC) - a three-week unit that integrates Earth science, engineering, and CT. We implemented the WRC with 99 sixth grade students and analyzed students’ learning artifacts and pre/post assessments to characterize students’ learning process in the WRC. We use a vignette to illustrate how anchoring CT tasks to STEM contexts supported CT learning for a student with low prior CT proficiency. 

Recent science education reforms, as described in the Framework for K-12 Science Education (NRC, 2012), call for three-dimensional learning that engages students in scientific practices and the use of scientific lenses to learn science content. However, relatively little research at any grade level has focused on how students develop this kind of three-dimensional knowledge that includes crosscutting concepts. This paper aims to contribute to a growing knowledge base that describes how to engage students in three-dimensional learning by exploring to what extent elementary students represent the crosscutting concept systems and system models when engaged in the practice developing and using models as part of an NGSS-aligned curriculum unit. This paper answers the questions: How do students represent elements of crosscutting concepts in conceptual models of water systems? How do students’ representations of crosscutting concepts change related to different task-based scaffolds? To analyze students’ models, we developed and applied a descriptive coding scheme to describe how the students illustrated the flow of water. The results show important differences in how students represented system elements across models. Findings provide insight for the kinds of support that students might need in order to move towards the development of three-dimensional understandings of science content.