Dynamic Measurement Modeling (DMM) is a recently-developed measurement framework for gauging developing constructs (e.g., learning capacity) that conventional single-timepoint tests cannot assess. The current project developed a person-specific DMM Trajectory Deviance Index (TDI) that captures the aberrance of an individual's growth from the…

Increasing pupil mobility has led to widespread concern among parents, educators, and policymakers regarding its negative effects on academic performance. An important issue in examining mobility effects in longitudinal school achievement comparisons is providing accurate estimates. The presence of pupil mobility suggests that we should model…

This study compared the relative contribution of earliest assessment of preschool children's context-specific problem behaviors with subsequent observations of those behaviors for the prediction of later academic and sociobehavioral performance in first grade. Using a nationally representative sample of low-income children from the Head Start…

Important educational policy decisions, like whether to shorten or extend the school year, often require accurate estimates of how much students learn during the year. Yet, related research relies on a mostly untested assumption: that growth in achievement is linear throughout the entire school year. We examine this assumption using a dataset…

The purpose of this report is to investigate the feasibility of constructing a school-level measure of students' academic growth from kindergarten to grade 3, and to assess the validity and precision of that measure. The study measured schoolwide student growth for reading and math using student growth percentiles based on Maryland's 2014/15…

Although letter naming fluency (LNF) and letter sound fluency (LSF) measures are widely available to educators for assessing early literacy skills of kindergarten children, better understanding of the contributions of these skills to reading development can help improve the interpretation of LNF and LSF data for instructional decisions. This study…

The United States faces high demand for science, technology, engineering, or mathematics (STEM) professionals and a scarce supply of individuals who pursue STEM careers, especially minority populations in the U.S with proficiency in a language other than English. The primary goal of this research was to determine the impact of use of Spanish in…

To model students' math growth trajectory, three conventional growth curve models and three growth mixture models are applied to the Early Childhood Longitudinal Study Kindergarten-Fifth grade (ECLS K-5) dataset in this study. The results of conventional growth curve model show gender differences on math IRT scores. When holding socio-economic…

This study utilized latent class analysis (LCA) to identify 5 discernible profiles of Latino children's (N = 1,253) social-emotional, physical, and cognitive school readiness at the time of kindergarten entry. In addition, a growth mixture modeling (GMM) approach was used to identify 3 unique literacy achievement trajectories, across Grades 2-5,…

Single-timepoint educational measurement practices are capable of assessing student ability at the time of testing but are not designed to be informative of student capacity for developing in any particular academic domain, despite commonly being used in such a manner. For this reason, such measurement practice systematically underestimates the…

Over the last several years, Tennessee has rapidly expanded the use of student growth portfolio models for the purpose of teacher evaluation. Participation, both in the number of districts and teachers, has increased steadily since portfolios were first introduced during the 2011-12 school year, and we expect that participation will continue to…

The objective of this study is to examine the trajectory of internalizing problems across middle childhood among a population sample of Australian children, and to understand the timing of explanatory factors related to children's development of internalizing problems, by using multiple-indicator latent growth curve modeling. Participants were…