What Science and STEM Teachers Can Learn from COVID-19: Harnessing Data Science and Computer Science through the Convergence of Multiple STEM Subjects

Abstract

ABSTRACT The COVID-19 pandemic is a historic global event that has extended to all parts of society and shaken the core of what we know and how we live. During this pandemic, the work of STEM professionals has taken center stage. Through our close observations of how the events of the pandemic have been unfolding across the globe, we propose an instructional framework that emerged out of the real-time responses of STEM professionals to explain the pandemic and find solutions. This framework centers on data science, computer science, and multidisciplinary convergence as tools for engaging K-12 students in complex societal problems like the pandemic. In this theoretical position statement, we propose our framework that is grounded in three areas: (a) data science and computer science, (b) multidisciplinary convergence, and (c) orientation and support for science teachers specifically and STEM teachers broadly to prepare them for fundamentally different roles. Using data and computer models, students find phenomena and problems compelling, appreciate the power and potential of STEM subjects, and explain phenomena and design solutions to real-world problems. Then, through multidisciplinary convergence, individuals and societies integrate STEM disciplinary knowledge and practices to make informed decisions and take responsible actions. As STEM teachers engage students in explaining phenomena and solving complex societal problems with data science and computer science through the convergence of multiple STEM subjects, teachers take on roles that are fundamentally different from the roles they have traditionally played.