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…

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 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…

This research study explored the relationship that exists between National Board certified teachers (NBCTs) and the reading achievement of students in third through fifth grade in comparison to non-NBCTs as measured by EVAAS growth data. Additional research questions analyzed which elements contained in the five core propositions participants…

Visual processes in Grade 1 were examined for their predictive influences in nonalphanumeric and alphanumeric rapid naming (RAN) in 51 poor early and 69 typical readers. In a lagged design, children were followed longitudinally from Grade 1 to Grade 3 over 5 testing occasions. RAN outcomes in early Grade 2 were predicted by speeded and nonspeeded…

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…

Through educational connoisseurship and criticism, this study explores how labels based on standardized student growth affect a rural school in Colorado. While the educators express intentions to help their students to demonstrate academic growth and achievement, they also have concerns that focusing on growth might compromise the well being of…