Successive Student Cohorts and Longitudinal Growth Models: An Investigation of Elementary School Mathematics Performance

Abstract

Mathematics achievement data from three longitudinally matched student cohorts were analyzed with multilevel growth models to investigate the viability of using status and growth-based indices of student achievement to examine the multi-year performance of schools. Elementary schools in a large southwestern school district were evaluated in terms of the mean achievement status and growth of students across cohorts as well as changes in the achievement status and growth of students between student cohorts. Results indicated that the cross and between-cohort performance of schools differed depending on whether the mean achievement status or growth of students was considered. Results also indicated that the cross-cohort indicators of school performance were more reliably estimated than their between-cohort counterparts. Further examination of the performance indices revealed that cross-cohort achievement status estimates were closely related to student demographics while between-cohort estimates were associated with cohort enrollment size and cohort initial performance status. Of the four school performance indices studied, only student growth in achievement (averaged across cohorts) provided a relatively reliable and unbiased indication of school performance. Implications for the No Child Left Behind school accountability framework are discussed.