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…

Prior research on the Measures of Academic Progress (MAP), a computer-adaptive test distributed by the Northwest Evaluation Association, has primarily focused on the Reading MAP for screening/benchmarking in elementary grades. The purpose of this study was to explore the functional form of growth and the extent to which student variability in…

This study evaluated five teachers from a middle school with a history of low-performances and high teacher turnover. This school participated in a reform program, Pay-For-Performance, where they received financial bonuses to increase performances on literacy and mathematics assessments. Additional requirements included participation in workshops,…

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…

This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…

We evaluate the feasibility of estimating test-score growth with a gap year in testing data, informing the scenario when state testing resumes after the 2020 COVID-19-induced test stoppage. Our research design is to simulate a gap year in testing using pre-COVID-19 data--when a true test gap did not occur--which facilitates comparisons of…

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,…

Providing diagnostic feedback about growth is crucial to formative decisions such as targeted remedial instructions or interventions. This article proposed a longitudinal higher-order diagnostic classification modeling approach for measuring growth. The new modeling approach is able to provide quantitative values of overall and individual growth…

In this study, gain score, and categorical growth models were used to examine the role of student (gender and socioeconomic level) and school characteristics (school size and school resources) in the student growth on comprehension skills in language. The participants of this study were 2,416 sixth-grade students in 2011 who became seventh-grade…

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…

The 2-parameter logistic multidimensional item response theory (MIRT) model was employed to model growth for the National Education Longitudinal Study of 1988 (NELS:88). The 3 measurement waves of NELS:88 (base year, first follow-up, and second follow-up) represented 3 dimensions.The inquiry aimed to improve modeling performance growth based on…

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 study was to examine the associations between behavioral and emotional characteristics and middle school student achievement across different grades based on a growth modeling approach. Using a total of 1,874 students, target predictor variables (i.e., attention, aggressiveness, behavioral control, social withdrawal,…