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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. Next Steps in WSA Evaluation. Extend beyond Tacoma Disaggregate WSA effect
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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
Next Steps in WSA Evaluation • Extend beyond Tacoma • Disaggregate WSA effect • Shift in opportunity structure, but may interact with individual characteristics • Program Mechanics • Application– need to define eligibility • Selection of WSA Scholars • Continuation to College • Especially to 4 year college
Potential Limitations of BHS Data • Only 5 of 16 WSA high schools in BHS • Non WSA high schools allow comparison • Eligibility (low income) not measured • Survey Non response • 70-80% of seniors in baseline survey • 90% of interviewed seniors in one year follow up survey
Supplementary Data Sources • OSPI data on school characteristics • Useful to measure selectivity of WSA program and BHS sample of schools • Administrative Data from one district • Low income measure: proxy for eligibility • Potential to estimate low income in BHS data • College Success Foundation: • Administrative records of Applicants, WSA Scholars, and College Attendance • Can be used to evaluate BHS estimates of transition rates
Advantages/Disadvantages of Each Data Set • Administrative Data: • Essentially complete; Proxy for eligibility • Lacks independent variables • UWBHS • Not all students responded to survey • No income data, but can be estimated • WSA and non WSA schools • Loads of independent variables
Selectivity of WSA Schoolsand the BHS Sample of WSA Schools Does the BHS sample fairly represent all schools and WSA schools, in particular?
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=16 N=276 N=9 N=5
Percent passing 10th 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=9 N=16 N=5
Next Steps • Measure System Dynamics • Eligibility, Application, Selection, College Attendance • Estimation: Low income eligibility • Compare BHS sample with Admin Data • Are system dynamics comparable • Can we estimate low income students: proxy for eligibility
Measuring WSA Eligibility • Lowest 1/3 of Washington St. families • Approx $49,000 for family of 4 • Admin variable identifies students below 185% of poverty level • Majority of students in WSA schools • 80-90% of WSA applicants • Poverty prediction equation using BHS measures of home ownership, parental SES, and other factors • Correctly predicts ¾ of low income students • Allows research to extend beyond district 1
Estimation of WSA Eligibility and Program Transition Rates Among High School Seniors in 3 WSA High Schools, 2002-05* All High School Students Eligibility ~ 63% Low Income Students Application Rate ~ 38% Applicants Selection Rate ~ 65% WSA Scholars Attending Any College ~ 92% Enrolled in Any College Attending a 4 yr College ~ 73% Enrolled in a 4 yr College *Based on district administrative data and CSF records
Comparison of Application, Selection & College Attendance Rates Between Administrative and BHS Survey Data for 3 WSA High Schools: 2002-05
Findings: • UW-BHS schools representative sample • Low income is a proxy for eligibility • Prediction of low income status (from BHS data) is reasonably accurate • Models using fitted income values similar to those with actual income data • UW-BHS data provide good estimates of WSA application and selection rates
Predicting WSA Application, Selection and College Attendance? • Demographic variables: • Gender, Race/Ethnicity, Immigrant Generation • Family SES & Structure • Home Ownership, Parental Education, Intact Family • Parenting and Encouragement • Good Behavior, Locus of Control, Self Esteem, GPA
APPLICATION ENCOURAGEMENT Females (via GPA) Asians (Vietnamese) Non-intact family Parents know friends Hrs of Homework High self efficacy High GPA SELECTION HIGH SELF EFFICACY AND GPA Non-intact family Parental education Parents know friends Hrs of Homework Predicting Application and Selection
Any College Encouragement & GPA Vietnamese (via encouragement) 1st Gen (via encouragement & GPA) Non Intact family Parental Educ & Comm. (via GPA) 4 Year College Encouragement & GPA African Amer., East Asian 1st and 2nd Gen(via encouragement & GPA) Non Intact family Parental Educ (via GPA) Predicting Attending College
Predictors among low income students • Demographic and SES largely unimportant, except non-intact families • Encouragement/High expectations • Homework and GPA • Self Efficacy/ Locus of Control
Further Evaluation of WSA Program • 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? • Are rejected applicants more likely to attend college than non applicants?