Operations research methods have been used to identify and evaluate solutions to the reconfiguration of public school attendance area boundaries for over fifty years. In broad terms, the school redistricting problem seeks to find capacity-feasible assignments of students in a school district to local schools. This talk will present analysis of the use of operations research for school districting. The talk will feature a review of the literature, exploring connections between evolving issues in public education and advances in optimization, computing and geographic information systems. Much of the early work was motivated by Supreme Court decisions to desegregate schools (Brown v. Board of Education, Brown II, Green v. New Kent, Swann v. Charlotte-Mecklenburg). Around that time, papers appeared in the operations research literature proposing analytical approaches to school desegregation that made use of advances in linear programming. The talk will examine ways in which these papers modeled the trade-offs between achieving racial balance and minimizing travel distance for students, and the extent to which the resulting analysis impacted policy and court cases. We will also discuss how the limitations of early models and solution approaches hindered their applicability. The years since have seen new directions in research to address additional challenges related to the design of school attendance boundaries and leverage emerging advances in optimization, computing, and geographic information systems technology. The talk will end with a reflection on current issues facing public school districts, including school busing and return-to-school plans amid the COVID-19 pandemic, and the ways in which operations research can be part of these discussions.