Computing has become an integral part of everyday practice within modern fields of science, technology, engineering, and mathematics. 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 addresses that mission by developing and testing computing-based science investigations for an Advanced Placement (AP) Computer Science Principles course, and for additional learning modules for use by teachers and students in middle school and high school not engaged in AP courses. The project will be implemented through a state-wide network of schools in Rhode Island having diverse student populations, and will provide professional development experiences for teachers in participating schools. The learning modules to be developed will integrate use of data and observations with computing to create conceptual models that simulate or predict natural phenomena, such as earthquakes, coastal resiliency, trends in the spread of infectious diseases, bioaccumulation of toxins in fish, the incidence of radon in homes, or other phenomena associated with emerging societal issues.

This design and development project will develop at least six proof-of-concept computing-based scientific investigations for use in science or computing classes. The investigations will each be grounded in the core science fields (life sciences, physical sciences, or Earth and space sciences), but the content and implications of the learning modules will span a broad range of interdisciplinary topics that focus on societal issues or potential hazards that require behavioral or engineering solutions. Each topic will require students to access data from science or engineering publications, or from national data archives maintained by agencies such as NASA, NIH, NOAA, or USGS, and incorporate these data into the development or testing of their conceptual or computer models of natural phenomena. The investigations will be aligned with performance expectations advocated by the Next Generation Science Standards for disciplinary core ideas, crosscutting concepts, and science and engineering practices. Research questions for the project will focus on student and teacher skills in using computational thinking to understand, learn, or teach; the influence of computational thinking on attitudes toward science, engineering, and computing; and factors influencing the learning and teaching of computational thinking. The learning modules to be developed will first be piloted within AP courses having diverse student populations at three Career and Technical Centers, with subsequent implementations in schools throughout the collaboration network. Data for project research and evaluation activities will be gathered from higher education partners, assessments embedded within the investigation activities themselves, and classroom surveys and assessments.