Matt Kasman Doctoral Candidate Graduate School of Education May 19th, 2014

1. School Selection, Student Assignment, and Enrollment in a School District with Open Enrollment and Mandatory Choice Policies Matt Kasman Doctoral Candidate Graduate School of Education May 19th, 2014 mkasman@stanford.edu

2. Motivation • Positive effects of racially diverse educational environment (Orfield et al., 2008) • Tolerance for different perspectives • Reduces prejudice • Stronger cooperative and critical-thinking skills • Benefits for individuals as well as communities and society

3. Motivation • School choice often discussed as a tool to improve diversity within schools • Provides families with the opportunity to make choices outside of a framework of traditional neighborhood schools • Predominantly single-race schools persist in open enrollment school districts • Under what, if any, policy conditions can open enrollment produce better results?

5. Dissertation Outline • 3 Papers that examine the open enrollment process: • School selection: when presented with school options, what choices do families make? • School enrollment: when assigned to schools, how do families respond? • Agent-based model simulations: given behaviors in previous two papers, how do policy interventions affect diversity?

6. Data • School application, assignment and enrollment data from a highly diverse, large urban school district • Focus on families choosing Kindergarten programs • Focus on families without observable siblings in schools • Student data • School program data

7. Simulations of Open Enrollment • School choice processes well suited for simulation • Individual decisions lead to system-wide change • Intention is for schools and districts to respond to changes in demand over time • Agent-based modeling is a good approach • Heterogeneity in schools and students • Dynamic process • Potential exit of students and schools • Equilibrium state is not focus of simulation

8. The Agent-based Model • Initialization: “plausible” cohort of prospective Kindergarten students sampled from actual 2009-2010 through 2012-2013 student data • School selection: race-specific participation probabilities; “choosers” submit ranked school selections that are based on findings from Paper 1 • Student assignment: simplified version of deferred acceptance algorithm used by district • Student enrollment: student enrollment based on findings from Paper 2 • Iteration: schools update characteristics based on enrollment, new cohort of students generated • Output: after 10 years, model stops and output by year is saved out

9. School Selection (Paper 1) • Conditional logit models predicting probability of a school program being selected as a family’s first choice: • Basic models include school/program characteristics • Additional models include interactions with student attributes

10. Predicting probability of school program selection with program characteristics and race interaction terms Coefficients are odds ratios; *** p<0.001, ** p<0.01, * p<0.05, + p<0.1

11. Achievement levels of options by distance

12. Student Assignment • Deferred acceptance student assignment • “Strategy-proof” • Hierarchical priority: • Low test-score zone residence • School attendance zone residence • Random lottery number • Unassigned student placement: • Attendance zone General Education program • Closest available General Education program

13. Enrollment (Paper 2) • Logit models predicting exit from public schools subsequent to assignment: • Models include family characteristics and assignment characteristics (either alone or relative to first choice characteristics) • Also, similar multinomial logit models predicting exit or reassignment:

14. Predicting probability of enrollment response with assignment relative to first choice Coefficients are odds ratios; *** p<0.001, ** p<0.01, * p<0.05, + p<0.1

15. Simulations (Paper 3) • Simulated scenarios • Baseline model: similar to current district policies • Full participation: upper bound on effect of interventions that increase engagement • Full participation, Black and Hispanic students • Better information: replace achievement levels with value-added as observed measure of quality • “simple” value-added • “more sophisticated” value-added • Increase capacity: investment in growing popular schools/programs • Change student assignment: similar to Dur et al. (2013); remove low test-score zone priorities

16. Results • Checking validity of simulations • Compare simulated 2011-2012 cohort to actual cohort • Enrollment trends in baseline simulation • Compare end-state school compositions across simulated scenarios

24. Discussion • Stability in enrollment trends in baseline simulation • Realistic, given longstanding choice policies in district • Simulated interventions have effect on enrollment patterns • Value-added information reduces racial gaps in enrolled school achievement levels • More participation in choice increases diversity within schools • Simulations of open enrollment are a tool that can be used to answer many questions

25. School Selection, Student Assignment, and Enrollment in a School District with Open Enrollment and Mandatory Choice Policies Matt Kasman Doctoral Candidate Graduate School of Education May 19th, 2014 mkasman@stanford.edu