Rambo-Hernandez and McCoach's analysis into the longitudinal growth of high-achieving students offered two conclusions about the reading growth of high achieving students: high-achieving students lose less ground in reading during the summer, but they exhibit less growth over the school year. This study will seek to replicate the reading results…

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…

Student growth percentiles (SGPs) are currently used by several states and school districts to provide information about individual students as well as to evaluate teachers, schools, and school districts. For SGPs to be defensible for these purposes, they should be reliable. In this study, we examine the amount of systematic and random error in…

We used the Stanford education data archive (SEDA) data to examine the heterogeneity among urban school districts in the United States. The SEDA 2.1 includes data sets on students' mathematics (Math) and English language arts (ELA) achievement from 2008 to 2014 at the district level. Growth mixture modeling was used to uncover the underlying…

Monitoring the progress of student learning is an important part of teachers' data-based decision making. One such tool that can equip teachers with information about students' learning progress throughout the school year and thus facilitate monitoring and instructional decision making is learning progress assessments. In practical contexts and…

Sources of longitudinal achievement data are increasing thanks partially to the expansion of available interim assessments. These tests are often used to monitor the progress of students, classrooms, and schools within and across school years. Yet, few statistical models equipped to approximate the distinctly seasonal patterns in the data exist,…

Despite focused efforts, achievement gaps remain a problem in America's education system, especially those between students from higher and lower income families. Continued work on reducing these gaps benefits from an understanding of students' reading and math growth from typical school instruction and how growth differs based on initial…

Despite focused efforts, achievement gaps remain a problem in the America's education system, especially those between students from higher and lower income families. Continued work on reducing these gaps benefits from an understanding of students' reading and math growth from typical school instruction and how growth differs based on initial…

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…

This investigation examined the gender gap in language and reading skills in a sample of low-income African American boys compared to African American girls from the same neighborhoods and schools. Using a longitudinal, accelerated cohort design, we used individual growth curve models to evaluate the reading and language performance of 1st through…

This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual assessment scores over grades for students who are nested within cohorts within schools, the LVR-HM4 attempts to simultaneously model two types of…

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…