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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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Promoting Computational Thinking Through Science-Engineering Integration Using Computational Modeling
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.
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- Award ID(s):
- 1742195
- PAR ID:
- 10387198
- Date Published:
- Journal Name:
- Proceedings of the 16th International Conference of the Learning Sciences (ICLS)
- Page Range / eLocation ID:
- 743-750
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Rajala, a; Cortez, A; Hofmann, A; Jornet, A; Lotz-Sisitka, H; Markauskaite, M (Ed.)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.more » « less
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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.more » « less
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We articulate a framework for using computational modeling to coherently integrate the design of science and engineering curricular experiences. We describe how this framework informs the design of the Water Runoff Challenge (WRC), a multi-week curriculum unit and modeling environment that integrates Earth science, engineering, and computational modeling for upper elementary and lower middle school students. In the WRC, students develop conceptual and computational models of surface water runoff, then use simulations incorporating their models to develop, test, and optimize solutions to the runoff problem. We conducted a classroom pilot study where we collected students’ learning artifacts and data logged from their use of the computational environment. We illustrate opportunities students had to integrate science, engineering, and computational thinking during the unit in a pair of contrasting vignettes.more » « less
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This article describes a professional development (PD) model, the CT-Integration Cycle, that supports teachers in learning to integrate computational thinking (CT) and computer science principles into their middle school science and STEM instruction. The PD model outlined here includes collaborative design (codesign; Voogt et al., 2015) of curricular units aligned with the Next Generation Science Standards (NGSS) that use programmable sensors. Specifically, teachers can develop or modify curricular materials to ensure a focus on coherent, student-driven instruction through the investigation of scientific phenomena that are relevant to students and integrate CT and sensor technology. Teachers can implement these storylines and collaboratively reflect on their instructional practices and student learning. Throughout this process, teachers may develop expertise in CT-integrated science instruction as they plan and use instructional practices aligned with the NGSS and foreground CT. This paper describes an examination of a group of five middle school teachers’ experiences during one iteration of the CT-Integration Cycle, including their learning, planning, implementation, and reflection on a unit they codesigned. Throughout their participation in the PD, the teachers expanded their capacity to engage deeply with CT practices and thoughtfully facilitated a CT-integrated unit with their students.more » « less
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