Year: 2003
Type: article
Study design: Observational Study
Abstract: The performance of schools in a large urban school district was examined using achievement data from a longitudinally matched cohort of middle school students. Schools were evaluated in terms of the mean achievement and mean growth of students in mathematics and language arts. Application of multilevel, longitudinal models to student achievement data revealed that 1) school performance varied across both outcome measures in both subject areas, 2) significant proportions of variation were associated with school-to-school differences in performance, 3) evaluations of school performance differed depending on whether school mean achievement or school mean growth in achievement was examined, and 4) school mean achievement was a weak predictor of school mean growth. These results suggest that assessments of school performance depend on choices of how data are modeled and analyzed. In particular, the present study indicates that schools with low mean scores are not always “poor performing” schools. Use of student growth rates to evaluate school performance enables schools that would otherwise be deemed low performing to demonstrate positive effects on student achievement. Implications for state accountability systems are discussed.
Authors: Keith Zvoch, Joseph J. Stevens
Institutions: Albuquerque Public Schools, University of New Mexico
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W2154689938