In March 2016, the Russell Sage Foundation and William T. Grant Foundation established the Educational Opportunity Monitoring Project, a collaboration designed to support innovative research that uses newly released data on academic achievement from the Stanford Education Data Archive (SEDA) to address educational opportunity and success in the United States. SEDA is a large-scale administrative database assembled by former RSF visiting scholar Sean Reardon(Stanford University) and colleagues that contains information on the results of over 200 million standardized achievement tests taken by roughly 40 million public school students from 2009 to 2013.
RSF and the W.T. Grant Foundation launched the first of two small grants competitions in May 2016. The competition aims to encourage junior faculty and graduate students to use the SEDA and other datasets to investigate issues and policies relevant to educational inequalities. Seven projects were funded in 2016. The following nine projects have recently been funded in the second round of the competition:
Selective Enrollment and (In)equality in U.S. Public Schooling
Véronique Irwin (University of California, Berkeley) – $7,000
Irwin will study the extent to which academically selective public schools improve education for all students. She will combine an original and comprehensive database of Selective Enrollment Public Schools (SEPS) with existing school and district data from SEDA to investigate whether selective schools tend to expand opportunities for more “traditional” urban public-school students or instead serve as educational subsidies for the well-off.
Effect of Medicaid and CHIP Eligibility on Academic Achievement and Achievement Gaps
Matthew F. Larsen (Lafayette College) – $15,496
Larsen will investigate how changes in Medicaid and Children’s Health Insurance Program (CHIP) coverage have affected short-term educational outcomes for low-income students. He will utilize test scores from SEDA at the country and state level in conjunction with data on Medicaid and CHIP eligibility to examine how contemporaneous changes in eligibility for these programs affected academic achievement gaps by state.
Outsized and Overlooked: The Role of PTA Resources in the Widening Achievement Gap
Brittany Murray and James Carter III (University of North Carolina, Chapel Hill) – $13,933
Murray and Carter will examine the role of parent-teacher associations (PTAs) in exacerbating educational inequality. They will pair data from the IRS on PTA expenditures nationwide with data on district-level achievement from SEDA to analyze the extent to which PTA expenditures affect district-wide achievement gaps. They will also study whether racial and class disparities in students’ exposure to PTA resources drives racial achievement gaps.
Does State Takeover of School Districts Affect Student Achievement?
Beth Schueler (University of Virginia) – $15,089
Schueler will study how state takeovers of struggling public school districts affect academic achievement. She will pair data on statewide academic performance from SEDA with an original dataset that identifies all school districts that have ever been under state takeover since the 1980s. She will also estimate the effects of state takeovers on educational inputs such as pupil-teacher ratio, total per pupil expenditures, the share of expenditures spent on instruction, and the percent of public school students in charter schools.
The Impact of School Counseling Ratios and Funding on Student Test Scores
Mary Kate Blake (University of Notre Dame) – $7,000
Blake will study how school counselors contribute to the academic success of elementary and middle school students. She will connect state-level policy information regarding school counselors, their actual presence within schools, and SEDA data on student academic performance to provide national estimates of the impact of school counselors on student test scores.
Does Limiting Out-of-school Suspension Improve Student Performance and Reduce Achievement Gaps? Evidence from Apparent Suspension-Restricting Policies
Richard DiSalvo (University of Rochester) – $7,000
DiSalvo will analyze national data from the Office of Civil Rights to identify school districts that would be expected to have high out-of-school suspension rates based on observable characteristics yet suspend students only infrequently. He will use SEDA data to compare academic outcomes in these districts with comparable districts that have suspensions rates closer to expectations to determine how limiting suspensions affects student performance and achievement gaps.
When Crisis Hits Home: A National Study of the Distal Effects of Foreclosures on Student Achievement
Jacob Faber and Chantal Hailey (New York University) – $19,131
Faber and Hailey will assess how the foreclosure crisis of the early twenty-first century affected student academic performance, the racial achievement gap, and school racial segregation (both within and across school districts). They will estimate changes over time in district-level student achievement and segregation using SEDA data and data on foreclosures between 2006 and 2016.
School-entry Vaccination Laws, Non-Medical Exemptions and Academic Achievement
Nicole Hair (University of South Carolina) and Carly Urban (Montana State University) – $20,000
Hair and Urban will investigate how school vaccination policies affect students’ performance on standardized tests of academic achievement and the white-black achievement gap. Using SEDA data on academic achievement, data on vaccination coverage from the National Immunization Surveys, and a new database of mandatory school immunization laws, they will explore whether reducing vaccination exemptions or adding requirements improves student scores and narrows the racial achievement gap.
Student Growth, Choice, and Segregation: The Effects of Academic Growth Data on School District Enrollment Decisions
David M. Houston (Harvard University) – $14,140
Houston will examine the effects of providing information about average student growth (as opposed to average student achievement) on hypothetical school district enrollment decisions. Using student growth measures estimated by SEDA, he will conduct a randomized survey experiment that tests whether subjects who are given average growth data are more likely to choose more diverse school districts than those who are given average achievement data.