Diversity Associated With Reductions in the Achievement Gap: Data Mining the 2010–2011 New Jersey Assessment of Skills and Knowledge (NJ ASK)

Stephen José Hanson, Stephanie Saunders, Arcelio Aponte, Robert Copeland, Michael Nettles

Research output: Contribution to journalArticlepeer-review

Abstract

The academic achievement gap is a persistent and pernicious educational challenge confounded with race and socioeconomic status. The achievement gap persists despite over three decades of interventions and federal, state, and local policies and initiatives meant to close it. We examine the achievement gap in one of the most diverse states in the United States, New Jersey. Across the 480 school districts in New Jersey, the school district racial makeup varies from almost complete segregation to high diversity. Using data-mining techniques on the statewide standardized test, the 2010–2011 New Jersey Assessment of Skills and Knowledge (NJ ASK) standard language arts literacy and mathematics, we found that test scores increased with increasing diversity. In particular, the achievement gap between Black and White third grade students was lower by more than 60% in racially diverse districts when compared to racially homogeneous districts. This result is consistent with theories of peer spillover effects that implicate peer racial diversity in reducing the achievement gap. A cluster analysis of New Jersey school districts revealed eight common profiles, which could inform school policy and practice aimed at improving school performance and closing the achievement gap.

Original languageEnglish (US)
Pages (from-to)1-20
Number of pages20
JournalETS Research Report Series
Volume2020
Issue number1
DOIs
StatePublished - Dec 2020

All Science Journal Classification (ASJC) codes

  • Social Psychology
  • Education
  • Applied Psychology
  • Statistics, Probability and Uncertainty

Keywords

  • Achievement gap
  • big data
  • data mining
  • diversity
  • school reforms

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