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Between-District Test Score Variation, 2009-2012

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Title: Between-District Test Score Variation, 2009-2012
Language: English
Authors: Fahle, Erin, Reardon, Sean, Society for Research on Educational Effectiveness (SREE)
Source: Society for Research on Educational Effectiveness. 2016.
Availability: Society for Research on Educational Effectiveness. 2040 Sheridan Road, Evanston, IL 60208. Tel: 202-495-0920; Fax: 202-640-4401; e-mail: inquiries@sree.org; Web site: http://www.sree.org
Peer Reviewed: Y
Page Count: 10
Publication Date: 2016
Document Type: Reports - Research
Education Level: Elementary Secondary Education
Descriptors: School Districts, Scores, Comparative Analysis, School Effectiveness, Educational Planning, Models, Correlation, Data Analysis, Statistical Distributions, Statistical Studies, School Statistics
Abstract: Describing the variation in test scores between and within school districts is critical for: (1) for policy-related and descriptive work that investigates the sorting of students among districts and the differential effectiveness of those districts; and (2) for methodological work planning future experiments or interventions. Intraclass Correlations (ICCs) and Coefficients of Variation (CVs) are two complementary ways to describe test score variation. ICCs describe the proportion of variance in test scores that is between (rather than within) school districts or schools. CVs describe the extent of heteroscedasticity in district (or school) test score distributions. The most straightforward method of calculating ICCs and CVs is to use student-level data to directly estimate the means and variances of district or school test score distributions. In this study the authors investigate three interrelated research questions: (1) how much between-district variation exists across U.S. states?; (2) what are they key patterns across grades, subject, and years (within or across states) in the between-district variation?; and (3) what state-level factors are associated with a state having more-or-less observed between-district variation? This study leverages the use of ordered probit models to recover distributional information from coarsened test score data proposed by Reardon et al. This method was applied to a large data set provided by the National Center of Education Statistics (NCES) through a restricted data license. Under the No Child Left Behind (NCLB) legislation, states are required to report aggregated test score results to the U.S. Department of Education, through a system called EdFacts. The authors found substantial variation in ICCs and CVs across states. One table and 2 figures are appended.
Abstractor: ERIC
Number of References: 12
Entry Date: 2016
Accession Number: ED567207
Database: ERIC
FullText Text:
  Availability: 0
CustomLinks:
  – Url: https://eric.ed.gov/contentdelivery/servlet/ERICServlet?accno=ED567207
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PubType: Report
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  Data: Between-District Test Score Variation, 2009-2012
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  Data: <searchLink fieldCode="AR" term="%22Fahle%2C+Erin%22">Fahle, Erin</searchLink><br /><searchLink fieldCode="AR" term="%22Reardon%2C+Sean%22">Reardon, Sean</searchLink><br /><searchLink fieldCode="AR" term="%22Society+for+Research+on+Educational+Effectiveness+%28SREE%29%22">Society for Research on Educational Effectiveness (SREE)</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Society+for+Research+on+Educational+Effectiveness%22"><i>Society for Research on Educational Effectiveness</i></searchLink>. 2016.
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  Data: Society for Research on Educational Effectiveness. 2040 Sheridan Road, Evanston, IL 60208. Tel: 202-495-0920; Fax: 202-640-4401; e-mail: inquiries@sree.org; Web site: http://www.sree.org
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  Data: <searchLink fieldCode="DE" term="%22School+Districts%22">School Districts</searchLink><br /><searchLink fieldCode="DE" term="%22Scores%22">Scores</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+Analysis%22">Comparative Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22School+Effectiveness%22">School Effectiveness</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Planning%22">Educational Planning</searchLink><br /><searchLink fieldCode="DE" term="%22Models%22">Models</searchLink><br /><searchLink fieldCode="DE" term="%22Correlation%22">Correlation</searchLink><br /><searchLink fieldCode="DE" term="%22Data+Analysis%22">Data Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+Distributions%22">Statistical Distributions</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+Studies%22">Statistical Studies</searchLink><br /><searchLink fieldCode="DE" term="%22School+Statistics%22">School Statistics</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Describing the variation in test scores between and within school districts is critical for: (1) for policy-related and descriptive work that investigates the sorting of students among districts and the differential effectiveness of those districts; and (2) for methodological work planning future experiments or interventions. Intraclass Correlations (ICCs) and Coefficients of Variation (CVs) are two complementary ways to describe test score variation. ICCs describe the proportion of variance in test scores that is between (rather than within) school districts or schools. CVs describe the extent of heteroscedasticity in district (or school) test score distributions. The most straightforward method of calculating ICCs and CVs is to use student-level data to directly estimate the means and variances of district or school test score distributions. In this study the authors investigate three interrelated research questions: (1) how much between-district variation exists across U.S. states?; (2) what are they key patterns across grades, subject, and years (within or across states) in the between-district variation?; and (3) what state-level factors are associated with a state having more-or-less observed between-district variation? This study leverages the use of ordered probit models to recover distributional information from coarsened test score data proposed by Reardon et al. This method was applied to a large data set provided by the National Center of Education Statistics (NCES) through a restricted data license. Under the No Child Left Behind (NCLB) legislation, states are required to report aggregated test score results to the U.S. Department of Education, through a system called EdFacts. The authors found substantial variation in ICCs and CVs across states. One table and 2 figures are appended.
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  Data: ERIC
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=ED567207
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    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 10
    Subjects:
      – SubjectFull: School Districts
        Type: general
      – SubjectFull: Scores
        Type: general
      – SubjectFull: Comparative Analysis
        Type: general
      – SubjectFull: School Effectiveness
        Type: general
      – SubjectFull: Educational Planning
        Type: general
      – SubjectFull: Models
        Type: general
      – SubjectFull: Correlation
        Type: general
      – SubjectFull: Data Analysis
        Type: general
      – SubjectFull: Statistical Distributions
        Type: general
      – SubjectFull: Statistical Studies
        Type: general
      – SubjectFull: School Statistics
        Type: general
    Titles:
      – TitleFull: Between-District Test Score Variation, 2009-2012
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            NameFull: Society for Research on Educational Effectiveness (SREE)
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            NameFull: Reardon, Sean
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              Y: 2016
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