Variations in Student Development Trajectories in Reading and Mathematics: A Multilevel Growth Mixture Model Approach.
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Date
2007-04-06
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Abstract
Lack of student achievement has long been a cause of national concern. The No Child Left Behind (NCLB) act of 2001 represents the latest attempt to both correct past educational inequities and to improve the competitiveness of American education. NCLB mandates that all students must meet proficiency standards by the 2013-14 school year. To determine whether students are on track to meet this goal, NCLB uses the metric of Adequate Yearly Progress (AYP). Presently, AYP appears to be set in terms of what is required to meet the 2013-14 goal with no consideration of how student growth and development actually occurs. Moreover, this type of goal assumes that all students can develop or progress at the same rate, in other word, "one size fits all." This study sought to examine this "one size fits all" assumption through the examination of unobserved heterogeneity in student growth trajectories. Specifically, this study sought to determine whether student growth trajectories in reading and mathematics between grade 3 and grade 8 could be adequately described by either single or multiple classes of growth using a multi-level growth mixture modeling approach. Further, the study examined the effects of gender, socio-economic status, ethnicity, parental education, and Local Educational Area (LEA) funding upon these growth trajectories. In terms of classes of growth trajectories, the results clearly suggest the existence of multiple classes of growth for both reading and mathematics. All individual level covariates influenced either membership in a growth class or the latent growth factors or both class membership and growth factors. In contrast, LEA level funding covariates effects were in general not supported. Relationships, for the most part, were consistent across primary and replication samples. Lastly, implications for educational practice, educational policy, Industrial⁄Organization psychology, and research are discussed along with the limitations of the present study.
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NCLB, high-stakes testing, latent variable modeling, mixture modeling
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Degree
PhD
Discipline
Psychology
