Computing and computational thinking (CT) are an integral part of everyday practice within modern fields of science, technology, engineering, and math (STEM). As a result, the STEM+Computing Partnerships (STEM+C) program seeks to advance new multidisciplinary approaches to, and evidence-based understanding of, the integration of computing in STEM teaching and learning, and discipline-specific efforts in computing designed to build an evidence base for teaching and learning of computer science in K-12, including within diverse populations. Integrating CT into core science instruction addresses practical constraints in K-12 education, in that there is no room in the curriculum to teach it directly to everyone. But, more importantly, integrating CT into core science provides a synergistic opportunity to deepen instruction in both. This project investigates the synergistic learning of physics and CT concepts and practices through students' construction of and interaction with computational models that visually represent physical systems.
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Computing and computational thinking (CT) are an integral part of everyday practice within modern fields of science, technology, engineering, and math (STEM). As a result, the STEM+Computing Partnerships (STEM+C) program seeks to advance new multidisciplinary approaches to, and evidence-based understanding of, the integration of computing in STEM teaching and learning, and discipline-specific efforts in computing designed to build an evidence base for teaching and learning of computer science in K-12, including within diverse populations. Integrating CT into core science instruction addresses practical constraints in K-12 education, in that there is no room in the curriculum to teach it directly to everyone. But, more importantly, integrating CT into core science provides a synergistic opportunity to deepen instruction in both. This project investigates the synergistic learning of physics and CT concepts and practices through students' construction of and interaction with computational models that visually represent physical systems. Led by investigators at Vanderbilt University, the project team includes computer scientists, physicists, education developers, and learning scientists SRI International, Stanford, and Salem State University. The project will develop, implement, and study an innovative programming environment, a multi-week computational physics curriculum, and new assessments that are focused on physics concepts of force and motion and CT practices involved in computational modeling. Guided by the programming environment and the curriculum, learners construct models that represent physical systems, analyze and explain model behaviors, and then use models for solving problems. These processes support their abilities to think and act like a scientist as they explore and learn about both the computational and physical systems and phenomena. Assessments will be developed to measure CT-infused physics learning that is targeted in the curriculum, but also what CT learners apply to new physics topics and problem-solving situations they encounter. The educational program will address specific needs of high school students and teachers with regard to relevant disciplinary content, practices, and computation as specified in Next Generation Science Standards, the AP Computer Science Principles, and recent consensus frameworks for computational thinking in STEM. Approximately 450 students will be involved with and benefit from the project in four diverse high school settings. The diverse nature of the participating schools will both engage a demographically diverse student population in STEM and help the project achieve significant broader impacts, by assuring that the findings and products developed reflect the needs of a broad diversity of people and places. The project will develop new educational technologies, curriculum materials, and assessments for integrating physics and computation that will be broadly usable in high school physics and computer science courses.
This project will investigate a method of broadening access to CT through the integration of computational modeling and problem solving in secondary physics courses. Through constructing computational models that represent complex physical systems, students will learn key concepts of Newtonian physics and CT practices of problem representation, abstraction, decomposition, composition, and verification. The project will produce a new programming environment that is optimized for modeling physics systems and phenomena, that facilitates collaborative modeling and problem solving, and that diagnoses and responds to users' learning activity with adaptive scaffolds. Three standards-aligned, problem-oriented computational physics units will be developed and used in conjunction with the programming environment. Evidence-centered design will be used to develop and validate assessments that measure CT-infused physics learning that is targeted in the units. A unique set of assessments will be developed independent of the modeling environment to measure whether and what CT students spontaneously transfer to new physics problems and learning situations. The curriculum and assessments with be co-developed by researchers and four teachers from diverse high school settings in Tennessee and California. Quantitative and qualitative analyses of student assessments, surveys, work products, computer-use logs, and videotaped tasks will be used to determine the effectiveness and broad utility of the approach - and its component parts - for integrating physics and computing. By tackling the challenge to align offline and online measures of students' learning and behaviors, the project will generate deeper understanding of how students learn, the difficulties they face, and the promise of adaptive scaffolds for improving learning. The research will also elucidate the potential of explicit CT frameworks for preparing students' for future physics learning and problem solving. The project will provide the field with a strong foundation for designing learning technologies that integrate science and computational modeling. The research findings will be shared with the project team members' respective communities in computer science, technology education, cyberlearning, physics education, science education, and teacher education through papers in peer-reviewed journals and conference presentations. Efforts will be made to disseminate to teachers through practitioners workshops, conferences, and journals. A post-doctoral fellow and three graduate students will be trained through this project.
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