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Student Mobility Patterns and Achievement in Wisconsin. Prepared for the Wisconsin Department of Public Instruction Selina Eadie Ryan Eisner Bryan Miller Leni Wolf Monday, May 13, 2013. Overview of Presentation. ● Overview of Previous Findings ● Methodology of Analysis
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Student Mobility Patterns and Achievement in Wisconsin Prepared for the Wisconsin Department of Public Instruction Selina Eadie Ryan Eisner Bryan Miller Leni Wolf Monday, May 13, 2013
Overview of Presentation • ● Overview of Previous Findings • ● Methodology of Analysis • ● Description of Mobility in Wisconsin • ● Association Between Mobility and Achievement • ● Policy Implications and Ideas for Future Research
Research Questions ● What is the state of student mobility in WI? ● What is mobility’s association with achievement?
Previous Findings ● Moves associated with lower academic performance ● Different mobility rates for different groups of students ●Timing matters (both time of year and time of academic career) ●Inter- versus intra-district moves
Methodology • ● First research using Wisconsin Student Number Locator System (WSLS) • ●Created a cohort of students for analysis • ●Start: September 15, 2006 • ●End: May 1, 2011 • ●Students in Cohort: 319,230
Mobility Rates by Ethnicity (2006-07 through 2010-11) Number of moves
Moves in the Five Largest Districts (2006-07 through 2010-11)
Top Receiving Districts of Milwaukee Public Schools Students
Regression Confirmation ● Ran an OLS regression to test these relationships ● Controlled for: ● Race, Economic Status, Homelessness,District,Ever received English Language Learner (ELL) services Includes fixed effects for district ● Findings ● Coefficients on moves consistently negative and significant at .01 level ● Coefficients on other variables consistently of greater magnitude
Summary of Findings ● Black and Hispanic students appear to move much more frequently than their White and Asian-American peers ●Students who qualify for free or reduced-priced lunch move more than full-price students ●Students in largest districts are more likely to move than the state average ● Especially Milwaukee ●Consistent relationship between mobility and achievement
Future Research Considerations ● Detect residential moves ● Moves by time in academic career ●Type of destination school ● Prior year test score controls
Policy Implications ● Information and record-keeping systems ● Funding mechanisms and sources ● Implications for school choice policies
Acknowledgements ● Jared Knowles, Wisconsin Department of Public Instruction ● Russell Dimond, University of Wisconsin-Madison ● Jed Richardson, Wisconsin Center for Education Research ● Professor Andrew Reschovsky, University of Wisconsin- Madison
Thank you! Questions?