Computational Urban Science (May 2022)
GIS-based classroom management system to support COVID-19 social distance planning
Abstract
Abstract Schools across the United States and around the world canceled in-person classes beginning in March 2020 to contain the spread of the COVID-19 virus, a public health emergency. Many empirical pieces of research have demonstrated that educational institutions aid students’ overall growth and studies have stressed the importance of prioritizing in-person learning to cultivate social values through education. Two years into the COVID-19 pandemic, policymakers and school administrators have been making plans to reopen schools. However, few scientific studies had been done to support planning classroom seating while complying with the social distancing policy. To ensure a safe return to campus, we designed a ‘community-safe’ method for classroom management that incorporates social distancing and computes seating capacity. In this paper, we present custom GIS tools developed for two types of classroom settings – classrooms with fixed seating and classrooms with movable seating. The fixed model tool is based on an optimized backtracking algorithm. Our flexible model tool can consider various classroom dimensions, fixtures, and a safe social distance. The tool is built on a python script that can be executed to calculate revised seating capacity to maintain a safe social distance for any defined space. We present a real-world implementation of the system at Eastern Michigan University, United States, where it was used to support campus reopening planning in 2020. Our proposed GIS-based technique could be applicable for seating planning in other indoor and outdoor settings.
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