Making the Transition to Remote Science Teaching and Learning
Elementary, middle, and high school teachers in remote and hybrid instructional settings are engaged in professional learning to support students in three-dimensional learning through a modeling tool that scaffolds systems and computational thinking.
Across the nation, teachers have shifted to delivering instruction remotely due to COVID-19. This transition to remote instruction has presented challenges for secondary science teachers who previously engaged their students in hands-on learning through empirical tests and observations of real-world phenomena, but whose students might not now have the equipment or materials in their homes to enable hands-on investigations. In this project, Concord Consortium will develop and test a remote professional development program that is designed to support secondary science teachers in making the transition from face-to-face to remote instruction, while still providing their students with engaging opportunities to learn from empirical data. Through this professional development program, science teachers will gain practice in using an open-source tool that teaches data-based modeling in the context of complex systems. For example, this tool will enable students to use data related to the pandemic to develop models that can predict relevant outcomes. As students develop skills related to modeling, they will be better prepared for the STEM (science, technology, engineering, and mathematics) workforce of the future, which increasingly requires the ability to interpret and use large-scale data. Research will identify the features of professional development that support teachers in providing remote instruction that is aligned with the Next Generation Science Standards (NGSS) related to modeling and systems thinking. Concord Consortium will provide remote professional development to ten secondary science teachers on modeling using complex systems via open-source software. They will collect surveys, interviews, and teacher-generated curricular materials to ascertain how the teachers develop pedagogical strategies for remote instruction, which are designed to support the development of their students' modeling skills and practices. Additionally, they will collect data from student work, including log files from the software, to determine how the students demonstrate modeling practices and knowledge of systems in the context of this remote instruction. The results from inductive descriptive analyses of these data will be submitted to empirical journals. Other dissemination materials will outline the design principles that support teachers in modifying NGSS-aligned curricular materials for remote delivery. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.