1. The WSA Program: Pathways from Application to College Charles Hirschman and Nikolas Pharris-Ciurej University of Washington UW-Beyond High School Project Workshop October 19, 2007

2. 2 Next Steps in WSA Evaluation Extend beyond Tacoma Extend beyond Tacoma Disaggregate WSA effect Disaggregate WSA effect Shift in opportunity structure, but may interact with individual characteristicsShift in opportunity structure, but may interact with individual characteristics Program Mechanics Program Mechanics Application– need to define eligibilityApplication– need to define eligibility Selection of WSA ScholarsSelection of WSA Scholars Continuation to CollegeContinuation to College Especially to 4 year college Especially to 4 year college

3. 3 Potential Limitations of BHS Data Only 5 of 16 WSA high schools in BHS Only 5 of 16 WSA high schools in BHS Non WSA high schools allow comparisonNon WSA high schools allow comparison Eligibility (low income) not measured Eligibility (low income) not measured Survey Non response Survey Non response 70-80% of seniors in baseline survey70-80% of seniors in baseline survey 90% of interviewed seniors in one year follow up survey90% of interviewed seniors in one year follow up survey

4. Supplementary Data Sources OSPI data on school characteristics OSPI data on school characteristics Useful to measure selectivity of WSA program and BHS sample of schoolsUseful to measure selectivity of WSA program and BHS sample of schools Administrative Data from one district Administrative Data from one district Low income measure: proxy for eligibilityLow income measure: proxy for eligibility Potential to estimate low income in BHS dataPotential to estimate low income in BHS data College Success Foundation: College Success Foundation: Administrative records of Applicants, WSA Scholars, and College AttendanceAdministrative records of Applicants, WSA Scholars, and College Attendance Can be used to evaluate BHS estimates of transition ratesCan be used to evaluate BHS estimates of transition rates

5. Advantages/Disadvantages of Each Data Set Administrative Data: Administrative Data: Essentially complete; Proxy for eligibilityEssentially complete; Proxy for eligibility Lacks independent variablesLacks independent variables UWBHS UWBHS Not all students responded to surveyNot all students responded to survey No income data, but can be estimatedNo income data, but can be estimated WSA and non WSA schoolsWSA and non WSA schools Loads of independent variablesLoads of independent variables

6. 6 Selectivity of WSA Schools and the BHS Sample of WSA Schools Does the BHS sample fairly represent all schools and WSA schools, in particular?

7. Percent low-income students in all Washington state high schools, BHS public schools (9), WSA public high schools (16), and BHS WSA schools (5). OSPI: 2004-05 N= 276 N= 16 N= 9 N= 5

8. Percent passing 10 th Grade Math WASL in Washington state high schools, BHS public schools (9), WSA public high schools (16), and BHS WSA schools (5). OSPI: 2004- 05 N= 276 N= 16 N= 9 N= 5

9. Next Steps Measure System Dynamics Measure System Dynamics Eligibility, Application, Selection, College AttendanceEligibility, Application, Selection, College Attendance Estimation: Low income eligibilityEstimation: Low income eligibility Compare BHS sample with Admin Data Compare BHS sample with Admin Data Are system dynamics comparableAre system dynamics comparable Can we estimate low income students: proxy for eligibilityCan we estimate low income students: proxy for eligibility

10. 10 Measuring WSA Eligibility Lowest 1/3 of Washington St. families Lowest 1/3 of Washington St. families Approx $49,000 for family of 4Approx $49,000 for family of 4 Admin variable identifies students below 185% of poverty level Admin variable identifies students below 185% of poverty level Majority of students in WSA schoolsMajority of students in WSA schools 80-90% of WSA applicants80-90% of WSA applicants Poverty prediction equation using BHS measures of home ownership, parental SES, and other factors Poverty prediction equation using BHS measures of home ownership, parental SES, and other factors Correctly predicts ¾ of low income studentsCorrectly predicts ¾ of low income students Allows research to extend beyond district 1Allows research to extend beyond district 1

11. 11 Estimation of WSA Eligibility and Program Transition Rates Among High School Seniors in 3 WSA High Schools, 2002-05* All High School Students Low Income Students Applicants WSA Scholars Enrolled in Any College Enrolled in a 4 yr College *Based on district administrative data and CSF records Eligibility ~ 63% Application Rate ~ 38% Selection Rate ~ 65% Attending Any College ~ 92% Attending a 4 yr College ~ 73%

12. Comparison of Application, Selection & College Attendance Rates Between Administrative and BHS Survey Data for 3 WSA High Schools: 2002-05

13. Findings: UW-BHS schools representative sample UW-BHS schools representative sample Low income is a proxy for eligibility Low income is a proxy for eligibility Prediction of low income status (from BHS data) is reasonably accurate Prediction of low income status (from BHS data) is reasonably accurate Models using fitted income values similar to those with actual income data Models using fitted income values similar to those with actual income data UW-BHS data provide good estimates of WSA application and selection rates UW-BHS data provide good estimates of WSA application and selection rates

14. 14 Predicting WSA Application, Selection and College Attendance? Demographic variables: Demographic variables: Gender, Race/Ethnicity, Immigrant GenerationGender, Race/Ethnicity, Immigrant Generation Family SES & Structure Family SES & Structure Home Ownership, Parental Education, Intact FamilyHome Ownership, Parental Education, Intact Family Parenting and Encouragement Parenting and Encouragement Good Behavior, Locus of Control, Self Esteem, GPA Good Behavior, Locus of Control, Self Esteem, GPA

15. 15 Predicting Application and Selection APPLICATION ENCOURAGEMENT Females (via GPA) Asians (Vietnamese) Non-intact family Parents know friends Hrs of Homework High self efficacy High GPASELECTION HIGH SELF EFFICACY AND GPA Non-intact family Parental education Parents know friends Hrs of Homework

16. 16 Predicting Attending College Any College Encouragement & GPA Vietnamese (via encouragement) 1 st Gen (via encouragement & GPA) Non Intact family Parental Educ & Comm. (via GPA) 4 Year College Encouragement & GPA African Amer., East Asian 1 st and 2 nd Gen (via encouragement & GPA) Non Intact family Parental Educ (via GPA)

17. Predictors among low income students Demographic and SES largely unimportant, except non-intact families Demographic and SES largely unimportant, except non-intact families Encouragement/High expectations Encouragement/High expectations Homework and GPA Homework and GPA Self Efficacy/ Locus of Control Self Efficacy/ Locus of Control

18. Further Evaluation of WSA Program Compare low income students in non-WSA schools with WSA schools Compare low income students in non-WSA schools with WSA schools Is gap in college attendance between low and high income students less in WSA schools? Is gap in college attendance between low and high income students less in WSA schools? Are rejected applicants more likely to attend college than non applicants? Are rejected applicants more likely to attend college than non applicants?