Examining Relationships Between Where Students Start and how Rapidly they Progress: Using New Developments in Growth Modeling to Gain Insight into the Distribution of Achievement Within Schools

Abstract

Studying change in student achievement is of central importance in numerous areas of educational research, including efforts to monitor school performance, investigations of the effects of educational interventions over time, and school effects studies focusing on how differences in school policies and practices relate to differences in student progress. In this article, we argue that in studying patterns of change, it is often important to consider the relationship between where students start (i.e., their initial status) and how rapidly they progress (i.e., their rates of change). Drawing on recent advances in growth modeling methodology, we illustrate the potential value of such an approach in the context of monitoring school performance. In particular, we highlight the ways in which attending to initial status in analyses of student progress can help draw attention to possible concerns regarding the distribution of achievement within schools. To convey the logic of our approach and illustrate various analysis possibilities, we fit a series of growth models to the time series data for students in several schools in the Longitudinal Study of American Youth (LSAY) sample. In a final section, we discuss some of the possibilities that arise in employing a modeling approach of this kind in evaluating educational programs and in conducting school effects research.

As pesquisas sobre o efeito das escolas: contribuições metodológicas para a sociologia da educação

“…19 A divulgação desse tipo de informação sem levar em conta as diferenças quanto ao perfil socioeconômico dos alunos, bem como as suas trajetórias de crescimento dentro das escolas pode incorrer em equívocos e produzir políticas públicas indesejadas ao não evidenciar escolas de fato eficazes, conforme vem sendo amplamente discutido na literatura da área (Franco, 2001;Goldstein, 1997;Seltzer et al, 2003).…”

“…Ela varia em função das características dos alunos, mas também em função da organização escolar e das práticas pedagógicas. Assim, o desenho longitudinal é considerado o formato mais apropriado para medir o efeito das escolas, porque permite investigar o impacto das escolas nos alunos em termos de aprendizagem, após o controle do nível de conhecimento inicial e as características dos alunos (Singer & Willet, 2003;Seltzer et al, 2003).…”

Estimating a Three-Level Latent Variable Regression Model With Cross-Classified Multiple Membership Data

“…The argument is that it is important to study the expected differences in growth rates while taking into account the levels or variation in student achievement at the initial status (Seltzer, Choi, & Thum, 2003).…”

“…The prediction of growth by initial status might be stronger for females than for males. This hypothesis cannot be directly tested using a conventional GCM although this interaction effect can be tested using an LVR model that incorporates gender as a predictor of the coefficient representing the influence of initial status on growth rate (Seltzer et al, 2003). Alternatively, there might be an interaction effect in that differences in growth rates between educational intervention and control groups may vary as a function of individuals' initial status values (Choi & Seltzer, 2010;Muthén & Curran, 1997).…”

Time Issues in Multilevel Interventions for Cancer Treatment and Prevention

“…Another advantage of applying time and growth models in the context of MLIs relates to the notion that there are at least two parameters of interest to analysts, program designers, and policy makers: initial level of performance (intercept) and the rate of change (slope) (15). These two parameters may also interact.…”