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…

This dissertation informed researchers about the performance of different level-specific and target-specific model fit indices in Multilevel Latent Growth Model (MLGM) using unbalanced design and different trajectories. As the use of MLGMs is a relatively new field, this study helped further the field by informing researchers interested in using…

The purpose of this study was to examine the technical features of slopes produced from the curriculum-based measurement in writing (CBM-W) word dictation task. Seventy-nine elementary students in the U.S. Midwest with intensive learning needs responded to weekly word dictation probes across 20 weeks; responses were scored for correct letter…

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…

Purpose: The aim of this study was to describe and explain changes in severity of speech sound disorder (SSD) and token-to-token inconsistency in children with high levels of inconsistency. Method: Thirty-nine children (aged 4;6-7;11 [years;months]) with SSDs and high levels of token-to-token inconsistency were assessed every 6 months for 2 years…

Growth mixture models (GMMs) are applied to intervention studies with repeated measures to explore heterogeneity in the intervention effect. However, traditional GMMs are known to be difficult to estimate, especially at sample sizes common in single-center interventions. Common strategies to coerce GMMs to converge involve post-hoc adjustments to…

Education experiments frequently assign students to treatment or control conditions within schools. Longitudinal components added in these studies (e.g., students followed over time) allow researchers to assess treatment effects in average rates of change (e.g., linear or quadratic). We provide methods for a priori power analysis in three-level…

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,…

States can and should continue to measure student growth in 2021. Growth data will be crucial to understanding how school closures due to COVID-19 have affected student progress and what supports they will need to get back on track. Education leaders will also need growth data to ensure that any recovery efforts are equitable as well as effective…

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 paper we compare two approaches to measuring the average rate at which students learn in a given school or district. One type of measure--longitudinal growth measures--relies on student-level longitudinal data. A second type--cohort growth measures--relies only on repeated aggregated, cross-sectional data. Because student-level data is…

Evidence of student growth is a primary outcome of interest for educational accountability systems. When three or more years of student test data are available, questions around how students grow and what their predicted growth is can be answered. Given that test scores contain measurement error, this error should be considered in growth and…

Student absenteeism is often conceptualized and quantified in a static, uniform manner, providing an incomplete understanding of this important phenomenon. Applying growth curve models to detailed class-attendance data, we document that secondary school students' unexcused absences grow steadily throughout a school year and over grades, while the…

The current study determined growth patterns during an 8-week writing intervention and then examined the association between growth pattern and students' initial skills as determined by instructional-level data. One hundred forty-seven first-grade students struggling with early literacy skills received a writing intervention at one of two tiers of…

The process of setting and evaluating student learning objectives (SLOs) has become increasingly popular as an example where classroom assessment is intended to fulfill the dual purpose use of informing instruction and holding teachers accountable. A concern is that the high-stakes purpose may lead to distortions in the inferences about students…