Using Longitudinal Student Mobility to Identify At-Risk Students

Principal Investigator(s):  View help for Principal Investigator(s) Dan Goldhaber, American Institutes for Research; Cory Koedel, University of Missouri; Umut Ozek, American Institutes for Research; Eric Parsons, University of Missouri

Version:  View help for Version V1

Name File Type Size Last Modified
MO - Tables 1 to 4 charter.do text/plain 7.2 KB 12/08/2021 11:33:AM
MO - Tables 1 to 4 dist move.do text/plain 5.2 KB 12/07/2021 08:50:AM
MO - Tables 1 to 4 grades 3-5.do text/plain 7.3 KB 12/08/2021 08:13:AM
MO - Tables 1 to 4 grades 3-8.do text/plain 7.3 KB 12/08/2021 08:13:AM
MO - Tables 1 to 4 urban rural.do text/plain 7.3 KB 12/08/2021 08:13:AM
MO - Tables 1 to 4.do text/plain 5.2 KB 12/08/2021 08:13:AM
Proprietary Data Access.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document 13.5 KB 12/08/2021 08:13:AM
Read Me.docx application/vnd.openxmlformats-officedocument.wordprocessingml.document 16.2 KB 12/08/2021 08:23:AM
tables_figures_MA_WA.do text/plain 66.7 KB 12/08/2021 08:19:AM

Project Citation: 

Goldhaber, Dan, Koedel, Cory, Ozek, Umut, and Parsons, Eric. Using Longitudinal Student Mobility to Identify  At-Risk Students. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2021-12-08. https://doi.org/10.3886/E156641V1

Project Description

Summary:  View help for Summary 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—i.e., 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.



Related Publications

Download this project

Published Versions

V1 [2021-12-08]

Export Metadata

Dublin Core

DDI 2.5

Report a Problem

Found a serious problem with the data, such as disclosure risk or copyrighted content? Let us know.

This material is distributed exactly as it arrived from the data depositor. ICPSR has not checked or processed this material. Users should consult the investigator(s) if further information is desired.