Apply findings to simulate the impact of a hypothetical school voucher on private enrollment, the tax rate, public spending per student, and welfare.
Current Selections
ClearSwitching Social Contexts: The Effects of Housing Mobility and School Choice Programs on Youth Outcomes
Assesses research on the educational and socialoutcomes for comparable youth who change school and neighborhood settings through unique housing policy and school voucher programs.
Choice Without Equity: Charter School Segregation and the Need for Civil Rights Standards
Examines diversity and racial isolation within charter schools in 40 states and several dozen metropolitan areas.
Creating Mathematical Futures Through an Equitable Teaching Approach: The Case of Railside School
Gain a better understanding of equitable and successful teaching by analyzing Railside’s success.
Forced Justice: School Desegregation and the Law
To describe and explain conclusions about desegregation policy, especially to show how these viewpoints have evolved from legal doctrines, social and science research, and extensive case experience
Choice, Equity, and the Schools-Within-Schools Reform
- To what extent did subunit themes emphasize students’ disparate occupational and educational futures over their common social and academic needs?
- What rationales did students offer for their subunit selections, and how did their choices reflect their interests, motivations, social backgrounds, and academic abilities?
School Integration and the Academic Achievement of Negroes
Integration effects on Blacks achievement.
An Investigation of the Linkage Between Technology-Based Activities and STEM Major Selection in 4-Year Postsecondary Institutions in the United States: Multilevel Structural Equation Modelling
1) To what extent do technology-based activities affect students’ selections of STEM majors in 4-year postsecondary institutions at the student level, taking into account math performance, gender, racial/ethnic background, and socioeconomic status (SES)? 2) To what extent do technology-based activities and technology-based school environment affect students ‘selections of STEM majors in 4-year postsecondary institutions at the school level, taking into account math performance, gender, racial/ethnic background, and SES?
Pathways to Science and Engineering Bachelor’s Degrees for Men and Women
How would the gender gap in S/E degrees
change if women had the same orientation
toward and preparation for S/E in middle school
and at the end of high school?
Stratifying science: A Bourdieusian analysis of student views and experiences of school selective practices in relation to ‘Triple Science’ at KS4 in England
How do young people experience and construct their ‘choice’ (or not) of General Certificate of Secondary Education (GCSE) science route? And what are the identity and other implications (for social justice and widening participation in science) associated with participation on Double or Triple award routes for different groups of students?
Private Schools and "Latino Flight" from Black School Children
How Latino flight affects the resulting racial composition of the public schools?
Racial and Ethnic Heterogeneity in the Effect of MESA on AP STEM Coursework and College STEM Major Aspirations
-MESA participation increases students’ odds of taking AP STEM courses in high school and their aspirations for declaring a STEM major in college.
– These effects are driven primarily by black and white students, respectively.
– Latino and Asian students remain largely unaffected by MESA partiipation.
– MESA may improve black students’ high school STEM engagement but may have little impact on black and Latino students’ STEM outcomes in college.
The Cost-Effectiveness of Socioeconomic School Integration
1) What is the effect of SES integration on outcomes? 2) Is SES integration a cost effective strategy for diversity? 3) Is SES integration a cost effective strategy for school improvement?
When Opting Out is not a Choice: Implications for NCLB's Transfer Option from Charlotte, North Carolina
Examines the implementation and early outcomes of No Child Left Behind’s voluntary transfer option for the Charlotte-Mecklenburg School after end of court-mandated desegregation.
Cohort changes in the relationship between adolescents' family attitudes, STEM intentions and attainment
1) Are family attitudes less likely to constrain young women’s STEM intentions and attainment in the 1990s, as compared to the 1970s? 2) Alternatively, did the effect of family attitudes become less gendered during this period, such that family attitudes constrained both women’s and men’s STEM intentions and attainment among the 1992 cohort?
How Desegregation Changed Us: The Effects of Racially Mixed Schools on Students and Society
Ideas of graduates, educators, advocates and local policy makers who were directly involved in racially mixed public high schools 25 years ago.
Socio-economic Status and Subject Choice at 14: Do They Interact to Affect University Access
– There are substantial socioeconomic differences in the subjects that young people study from age 14 to 16.
– Young people from advantaged households take more selective subjects, have higher odds of doing three or more facilitating subjects, higher odds of studying a full set of EBacc-eligible subjects (including English, Maths, History or Geography, two sciences and a modern or ancient language), but lower odds of taking Applied GCSEs (e.g. Applied Hospitality, Applied Health or Applied Manufacturing) than less advantaged young people.
– There were important differences by school characteristics, which may be a result of differential opportunities, subjects offered and within school policies.
– Even holding other factors constant, pupils in non-selective schools within selective local authorities study a less academically selective set of subjects.
– When considering university entry, and admission to high-status universities in particular, there are large raw differences associated with studying more academic combinations of subjects.
However, once differences in young people’s backgrounds and prior attainment associated with these differences in subjects studied are taken into account, these differences are, at most,
small.
– The results for studying the full set of EBacc subjects and for studying any applied subjects do show residual associations with university attendance.
– If young people from different socioeconomic backgrounds were studying a more similar curriculum between ages 14 and 16 it would be unlikely to make much of difference to the inequality in university entry highlighted by previous studies.
– Household income, home ownership and higher parental education increase the odds of taking three STEM subjects
– Socio-economic differentials in access to STEM are largely driven by prior attainment.
– Participation in STEM subjects does not vary by school characteristics, with the exception of the proportion of Free School Meals (FSM) in the school which is negatively associated with doing three or more STEM subjects.
Economic School Integration
Explores the end of court-ordered desgregation, describes the alternative of socioeconomic integration, and sketches prospects for economic school integration in the future.
Academic and Racial Segregation in Charter Schools: Do Parents Sort Students into Specialized Charter Schools?
This article presents a dynamic model that focuses on how parental school choices affect the degree of racial and academic segregation that students experience in charter schools.
Gender Streaming and Prior Achievement in High School Science and Mathematics
– Gendered choices they make remain largely intact after conditioning on prior test scores, indicating that these choices are not driven by differences in perceived mathematical ability, or by boys’ comparative advantage in mathematics.
– Girls who choose matriculation electives in physics and computer science score higher than boys, on average.
– Girls and boys react differently to early signals of mathematical and verbal ability.
– Girls are less adversely affected by socioeconomic disadvantage.
– Girls score higher in all four subjects, with a greater advantage in
language arts than in mathematics and science, implying that boys have a comparative advantage in mathematics and science.
– There is a strong pattern of gender streaming in the choice of electives in science and mathematics. The share of boys choosing advanced physics or computer science is more than twice that of girls; the share of boys choosing advanced mathematics is about 20% higher; while the share of girls choosing advanced biology is about 60% higher than boys and their share in advanced chemistry is 40% higher.
– For physics or computer science and for advanced mathematics, accounting for the observed gender difference in the distribution of prior mathematics achievement widens the gender gap very slightly.
– For biology and chemistry, accounting for differences in prior
achievement reduces the gap favoring girls by 0.6 percentage points.
– In the regression, as girls do slightly better than boys in eighth-
grade mathematics, controlling for prior achievement in mathematics increases the gender gap favoring boys in physics or computer science and in advanced mathematics, by 1.0 and 1.2 percentage points respectively while reducing the gender gap favoring girls in biology or chemistry by 0.8 of a percentage point.
– The largest effect is in advanced mathematics and the smallest in biology or chemistry, in line with the relevance of mathematical ability for each subject.
– All prior scores exhibit a statistically significant, positive (and in most cases convex) relationship with the probability of choosing a science or mathematics elective.
– An interaction term, the product of the mathematics and Hebrew scores, also has a significant positive effect.
– Boys’ and girls’ different propensities to choose science and mathematics electives are partly a reflection of their different responses to prior signals of ability. A signal of strong mathematical ability has a positive effect on both boys and girls for all three categories, but the effect is stronger for boys with regard to choosing advanced mathematics and physics or computer science, and stronger for girls with respect to choosing biology or chemistry; and a similar pattern applies to prior achievement in science.
– Selection of science and mathematics electives increases in parents’ education. The rate of increase is more moderate in biology or chemistry; and the share of girls declines with parents’ education in all electives. These findings are a further indication that boys benefit from a strong family background more than girls.
– The size of the gender gap increases in parental education for all electives, and more steeply in the male-dominated subjects, mathematics and physics or computer science, showing again that boys benefit more from a strong family background.
– Of the three groups, coeducational religious schools serve a population of students from markedly lower income groups, and achieve the lowest GEMS scores in all subjects for both male and female students in these schools. Coeducational non-religious schools and single-sex religious schools have more similar student populations.
– In non-religious schools, girls outperform boys, whereas boys outperform girls in religious schools.
– Single-sex religious schools have the highest matriculation rates, followed by coeducational non-religious schools.
After Seattle: Social Science Research and Narrowly Tailored School Desegregation Plans
Offer a social science rationale for Justice Kennedy’s view about narrow tailoring issues and suggesting several approaches to desegregation plans that may meet narrow tailoring requirement.
The Sorting Effect of Charter Schools on Student Composition in Traditional Public Schools
This article investigates how Michigan’s charter school policy influences the composition of students by race and socioeconomic status in urban traditional public schools.
What Do Parents Want from Schools? Evidence from the Internet
The aspects of schools parents prefer and how these preferences will affect the socioeconomic and racial composition of schools.
The Goals of a Voluntary Integration Program and the Problems of Access: A Closer Look at a Magnet School Application Brochure
Analysis of the district’s magnet school choice brochure and application and show that these key texts provide insights about Brown.
Choice of Majors: Are Women Really Different from Men?
– High school academic preparation, faculty gender composition, and major returns have little effect on major switching behaviors, and women and men are equally likely to change their major in response to poor grades in major-related courses.
– Women in male-dominated majors do not exhibit different patterns of switching behaviors relative to their male colleagues.
– Women are more likely to switch out of male-dominated STEM majors in response to poor performance compared to men.
– It takes multiple signals of lack of fit into a major (low grades, gender composition of class, and external stereotyping signals) to impel female students to switch majors.
I Think it's Just Natural': The Spatiality of Racial Segregation at a US High School
How does race and it’s ambivalences occur through girls’ everyday and banal spatial practices at school?
Foreign Peer Effects and STEM Major Choice
This paper aims to estimate the impact of foreign peers on native STEM major choice.
Parental Choice in the Netherlands: Growing Concerns about Segregation
This paper examines why segregation by educational disadvantage has only recently emerged as a policy issue in the Netherlands. In addition, it documents the levels and trends ofschool segregation in Dutch cities.
The Social and Academic Consequences of School Desegregation
Reviews the literature on long term social consequences of school desegregation, & how to opearte desegregated schools effectively.
The Continuing Struggle of African Americans for the Power to Make Real Educational Choices
Studies school choice for African Americans.
Family Socioeconomic Status and Choice of STEM Major in College: An Analysis of a National Sample
Does students’ decision of STEM enrollment in college differ systematically by family SES?
Perceived Mathematical Ability under Challenge: A Longitudinal Perspective on Sex Segregation among STEM Degree Fields
1) To what degree do domain-specific and domain-general perceptions of ability under challenge differ by gender? 2) What is the relationship between perceived ability under challenge in mathematics and advanced high school science course enrollment? 3) To what extent does perceived ability under challenge in mathematics predict staying in a STEM field as intended before entering postsecondary education? How is this relationship moderated by gender? 4) What is the relationship between perceived ability under challenge in mathematics and selection of mathematics-intensive science majors (physics, engineering, mathematics, and computer science(PEMC), and how is that relationship moderated by gender?
College Student Pathways to the STEM Disciplines
1) What individual and school-level factors influence students pathways to STEM fields during college? 2) What institutional factors affect students’ likelihood of majoring in a STEM field in college, controlling for differences in student characteristics?
School Policies and the Test Score Gap
Explores the potential effectiveness of school policies and strategies that have been proposed or justified–at least in part–on the basis of their potential for reducing black-white test score gaps.
The “Post-Racial†Politics of Race: Changing Student Assignment Policy in Three School Districts
Does having residents from multiple jurisdictions make it more difficult for districts to maintain support for student assignment policies, particularly given population differences between city and suburban residents? Does a district’s ability to maintain political support for integration differ by whether the goals and means were race-conscious or race-neutral?
Understanding the Changing Dynamics of the Gender Gap in Undergraduate Engineering Majors: 1971-2011
This paper examines the level and determinants of students’ plans to major in engineering when entering college. (1) How has the gender gap in incoming college students’ intent to major in engineering changed over the past 4 decades? (2) What are the determinants of women’s and men’s decision to major in engineering versus all other fields? To what extent have these determinants and/or their salience changed over time for women and men? (3) To what extent is the gender gap in the selection of engineering due to (a) gender differences in attributes, versus (b) gender differences in the salience of these attributes? How has this changed over time?