AERA Open (Jan 2022)

Using Longitudinal Student Mobility to Identify At-Risk Students

  • Dan Goldhaber,
  • Cory Koedel,
  • Umut Özek,
  • Eric Parsons

DOI
https://doi.org/10.1177/23328584211071090
Journal volume & issue
Vol. 8

Abstract

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We use administrative data from three states to document the relationships between geographic mobility and student outcomes during K–12 schooling. We focus specifically on nonstructural mobility events—which we define as school changes that do not occur as the result of normal transitions between schools—and on longitudinal measures that capture these events cumulatively for students. We show that the number of nonstructural moves experienced by a student is a powerful indicator of low-test performance and graduation rates. Longitudinal information on student mobility is unlikely to be readily available to local practitioners—that is, individual districts, schools, or teachers. However, due to recent investments in longitudinal data systems in most states, this information can be made available at low cost by state education agencies.