2006 - Understanding Trends in the Black-White Achievement Gaps During the First Years of School

Attribution: Murnane, Richard, Willett, John, Bub, Kristen, & McCartney, Kathleen
Researchers: John WillettKathleen McCartneyKristen BubRichard Murnane
University Affiliation: Harvard University
Email: richard_murnane@gse.harvard.edu
Research Question:
Examine results of Fryer and Levitt (2004 & 2005) about patterns in the relative academic achievement of young black and white children.
Published: 1
Journal Name or Institutional Affiliation: Brookings-Wharton Papers on Urban Affairs
Journal Entry: N/A
Year: 2006
Findings:
  • In the NICHD data set, substantial black-white gaps in mathematics and ELA skills are present at the beginning of kindergarten even after accounting for virtually the same set of family background characteristics that Fryer and Levitt used in their studies.
  • Evidence sheds no light on the role of class size in influencing student achievement in classes with thirty-five or forty-five students.
  • The amount of time teachers devote to mathematics instruction influences how much mathematics children learn.
  • Student body composition matters, and the percentage of students living in poverty is a better indicator of the challenges schools face in enhancing student achievement than is the racial-ethnic composition of the student body.
  • The coefficients on the racial-ethnic mix of the student body are not statistically significantly different from zero in this model, but the percentage of student living in poverty is a strong, statistically significant negative predictor of student achievement. This supports that the important characteristic of the student body is the percentage of students living in poverty. Schools serving high concentrations of students from poor families face especially large challenges, ones that relatively few schools have been able to consistently master.
  • Shows that less conventional measures of school quality, including composition of the student body and how instruction time is spent, are important predictors of student achievement.
Keywords: Achievement GapCompositionEnglishEthnicityMathSchool QualitySESRegions: NationalMethodologies: QuantitativeResearch Designs: Secondary Survey DataAnalysis Methods: Fixed and Random Effects Regression Models Sampling Frame:Region
Sampling Types: RandomAnalysis Units: StudentData Types: Quantitative-Cross Sectional
Data Description:
  • Data comes from phases I, II, and III of the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (NICHD SEECYD).
  • Using a conditional random sampling method, 2,352 families were subsequently phoned and 1,364 of the families that were called then participated in a home visit one month later for the purposes of data collection.
  • As outcome measures uses the subscales of the Revised Woodcock-Johnson Psycho-Educational Battery (WJ_R), which is a comprehensive set of individually administered tests designed to measure a broad range of cognitive abilities and achievements. Measures of Mathematics and Vocabulary skills.
  • – DV: math (kindergarten, 54 months, first grade, third grade) & English ELA (kindergarten/54 months, first grade, third grade) scores.
  • – IV: race, ethnicity and gender indications, personal characteristics and family background variables (SES, children’s book, birth weight, teen mother at first birth, mother age 30+ at first birth, assistance, early maternal sensitivity), school quality variables (class size, master’s degree, first two years of teaching, student body composition (25% or more students are black, 25% or more students are Latino, percent students eligible for free lunch), instructional time (proportion of hours spent on math instruction)).
Theoretical Framework:
Relevance:
Archives: K-12 Integration, Desegregation, and Segregation Abstracts