Computing and computational thinking 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. This project will develop, implement, and study an innovative multi-week middle school curriculum unit in computational weather forecasting that integrates students' learning and use of meteorology, mathematics, and computational thinking concepts and practices. Led by investigators at Concord Consortium, the project team includes weather scientists, computer scientists, education developers, and learning scientists from Argonne National Laboratory, Millersville University, and the University of Illinois at Chicago. The curriculum consists of instructional materials and technologies that transform classrooms into dynamic weather simulations and then scaffold students' learning and use of science, mathematics, and computational thinking as they (a) collect and analyze data from the simulated weather events; (b) develop and refine computational models from these data; (c) and use computational models to make and evaluate weather predictions. Live webcasts with meteorologists enable students to learn about how they made predictions from same data sets students examined. Approximately 430 students will be involved with and benefit from the project. 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 curriculum developed reflect the needs of a broad diversity of people and places.
This project will address a daunting challenge to developing STEM literacy in students: integrating teaching and learning of key ideas and practices of science and mathematics with computational thinking in authentic, innovative and effective ways. The project will exploit young people's universal interest in weather and the computationally intensive practice of modern meteorology to develop an inquiry-based curriculum in which students play the role of scientific experts that apply computational thinking as they explore, explain, and predict weather phenomena. The curriculum consists of a) four standards-aligned instructional sequences; b) a suite of technologies, software systems, and weather data sets; and c) professional development workshops and materials to support teachers' curriculum implementation. The intervention will address specific needs of middle school students and teachers with regard to relevant disciplinary content, practices, and computation as specified in Next Generation Science Standards, Common Core State Standards for mathematics, and recent consensus frameworks for computational thinking in STEM. Over three years the project will engage eight teachers and their 430 students who will work with the project team members to test the curriculum in distinctive middle school settings in Illinois, Massachusetts, and Alaska. The mixed methods design-based research will use a rich set of student tests, reflections, narrated computer models (called screencasts), and video recordings of students during classroom activities as sources of evidence. The research seeks to understand how students use computational thinking practices to generate explanations and predictions of weather events, and how these explanations and predictions evolve with the sequence and complexity of computational thinking practices. The research further seeks to understand how a set of core design elements of the curriculum facilitate students' computational thinking and reasoning about weather events. The research and external evaluation will explore replicability and scale by elucidating how findings and design elements generalize to unique populations, such as Alaskan Inuit students, and the contexts in which they learn. The project will produce an evidence-based trajectory of learning that describes how students become more sophisticated in their understanding of weather science and in their scientific explanations and predictions of weather events in conjunction with their use of key computational practices of collecting, interpreting, and representing data; evaluating and predicting with computational models. The project will also produce a set of evidence-based design principles for broader dissemination. The research findings will be shared with Concord Consortium's extensive network of more than 25,000 teachers, researchers, and policymakers, and by more traditional means, such as papers in peer-reviewed journals and conference presentations. The curriculum will be licensed via open source and open content licenses and freely distributed to other teachers, curriculum designers, and researchers through Concord Consortium's website.