  Scheduling university courses is extra challenging when classroom capacities
are reduced because of social distancing requirements that are implemented in
response to a pandemic such as COVID-19. In this work, we propose an expanded
taxonomy of course delivery modes, present an integer program, and develop a
course scheduling algorithm to enable all course sections -- even the largest
-- to have a significant classroom learning component during a pandemic. Our
approach is fair by ensuring that a certain fraction of the instruction in
every course section occurs in the classroom. Unlike previous studies, we do
not allow rotating attendance and instead require simultaneous attendance in
which all students in a section meet in 1-5 rooms at the same time but less
often than in a normal semester. These mass meetings, which create
opportunities for in-person midterm exams and group activities, are scheduled
at high precision across all days of the semester rather than a single,
repeating week. A fast heuristic algorithm makes the schedule in an hour.
Results: We consider the 1834 in-person course sections, 172 classrooms, and 96
days in the fall 2022 semester at [UniversityXYZ]. If average classroom
capacity is reduced by 75% due to a pandemic, our approach still allows at
least 25% of the instruction in every section, and more than 49% of all
instruction across the entire campus, to be in the classroom. Our method also
produces excellent results for regular classroom assignment. Managerial
implications: An algorithm based on the principles of fairness and simultaneous
attendance can significantly improve university course schedules during a
pandemic and in normal times. High-precision schedules that prepare a campus
for various pandemic possibilities can be created with minimal administrative
effort and activated at a moment's notice before or during a semester if an
outbreak occurs.
