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2003 - Schools and Educational Outcomes: What Causes the ''Race Gap'' in Student Test Scores?

Attribution: Bali, Valentina A., & Alvarez, Michael
Researchers: Michael AlvarezValentina A. Bali
University Affiliation: Michigan State University
Email: baliv@msu.edu
Research Question:
They examine whether school factors influence the test scores of racial groups differentially: all else equal, any school factor that differentially benefits minorities should reduce the ''race gaps.'' Moreover, we examine whether school policies benefit one racial group at the expense of another.
Published: 1
Journal Name or Institutional Affiliation: Social Science Quarterly
Journal Entry: Vol. 84, No. 3
Year: 2003
Findings:
  • Results suggest that school factors can have an impact on test scores but they cannot close the race gap. The school factors that differentially benefit minorities, without hurting non-minorities, such as class size, have small effects

  • The school policies that have a positive influence on minorities’ scores often involve an environment where closer attention is paid to the needs of students.

  • Teachers having full credentials has a significant (but small) positive impact on all students’ test scores, but it does not strongly benefit only minorities and thus it is not a likely candidate to decrease the ”race gaps.”

  • Average class size and teacher diversity hold some limited promise to help reduce the Hispanic-white test score gap, though the latter is qualified by its negative impact on non-minorities.

  • Most school policies do not display redistribution characteristics of benefiting one group while hurting another.

  • They find no systematic evidence of school programs benefiting one group while hurting another

    group.

  • The race gap is vastly reduced for Hispanics, in particular in reading, but not so for African-American students.

Keywords: Achievement GapMathRaceReadingSES CompositionMethodologies: QuantitativeResearch Designs: Secondary DataAnalysis Methods: Fixed Effects Regression Models Sampling Frame:Pasadena Unified School District
Sampling Types: PopulationAnalysis Units: ClassroomSchoolStudentData Types: Quantitative-Cross Sectional
Data Description:
  • They use data from a single school district in southern California—the Pasadena Unified School District (PUSD). In 1999-2000, there were approximately 23,400 students in the PUSD, of whom 18,300 took California’s yearly mandatory academic tests.

  • The PUSD is racially more diverse than California’s public schools overall but the PUSD and the state have comparable levels of English learners. Socio-economically, the PUSD has a student body that is poorer and more disadvantaged than the statewide student body. In terms of academic performance, this school district lagged California in every grade

    .

  • DV: Math and reading scores from the Stanford 9

  • IV: Grouped into two categories; student-family and school variables.

    Student- family variables include; race, English proficiency, legal guardianship.

    School variables are categorized into three sections; policies, programs, school demographics. Polices include; class size, percentage of teachers with full credentials, number of computers per student, and percent of minority teachers. Programs include; magnet schools, gifted and talented education, and school vocational programs. School demographics include; percent Hispanic and African American students.

Theoretical Framework:
Relevance:
Archives: K-12 Integration, Desegregation, and Segregation Abstracts
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