A Monte Carlo simulation was performed to compare methods for handling missing data in growth mixture models. The methods considered in the current study were (a) a fully Bayesian approach using a Gibbs sampler, (b) full information maximum likelihood using the expectation-maximization algorithm, (c) multiple imputation, (d) a two-stage multiple…

Studies on utility value, metacognitive strategies, and achievement have usually examined these variables in a static manner. However, each of these variables changes across time and the relationships among them are dynamic. Hence, studies that examine changes in individual trajectories (change in each variable over time) and concurrent…

As research must measure and precisely assess the effects of changes and advances in an area of endeavor, mathematics has played. It continues to play a key role in developing realms of science and technology. Academic performance is an important factor in determining an individual's success or failure in mathematics. Mathematics is obligatory in…

JMP® Pro has introduced a new structural equation modeling (SEM) platform to its suite of multivariate methods of analysis. Utilizing their graphical user interface, JMP Pro has created a SEM platform that is easily navigable for both experienced and novice SEM users. As a new platform, JMP Pro does not have the capacity to implement certain…

Modeling within-person change over time and between-person differences in change over time is a primary goal in prevention science. When modeling change in an observed score over time with multilevel or structural equation modeling approaches, each observed score counts toward the estimation of model parameters equally. However, observed scores…

The number of low-performing schools has drastically increased since COVID-19. During the 2018-2019 school year, there were 488 low-performing schools (North Carolina Department of Public Instruction, 2024). The number increased to 736 schools during the 2023- 2024 school year, a 50.8% increase (North Carolina Department of Public Instruction,…

During the past decade, cognitive diagnostic models (CDMs) have become prevalent in providing diagnostic information for learning. Cognitive diagnostic models have generally focused on single cross-sectional time points. However, longitudinal assessments have been commonly used in education to assess students' learning progress as well as…

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…

Teachers and school leaders frequently express a disconnect in the purpose and importance of teacher evaluation, particularly as it relates to educator growth. At the same time, some schools are beginning to communicate student growth through a standards-based grading philosophy. One way schools might "walk the talk" of their grading…

The MAP® Growth™ theory of action describes key features of MAP Growth and its position in a comprehensive assessment system. The basic premise of the theory of action is that all students learn when MAP Growth is situated in a comprehensive assessment system and used for its intended purposes to yield information about student learning and enable…

We propose a new item response theory growth model with item-specific learning parameters, or ISLP, and two variations of this model. In the ISLP model, either items or blocks of items have their own learning parameters. This model may be used to improve the efficiency of learning in a formative assessment. We show ways that the ISLP model's…

California is one of just two states (with Kansas) that does not use a student-level growth model to measure school performance. This brief lays out a number of common beliefs about growth models and provides evidence that these beliefs are inaccurate or unsupported. In so doing, the brief makes a positive case that the state should adopt such a…

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…

Although there is recognition that there may be differential outcomes for groups of students within schools, examination of outcomes for subgroups presents challenges to researchers and policymakers. It complicates analytic procedures, particularly when the number of students per school in the subgroup is small. We explored five alternatives for…

Executive functioning (EF) is found to be a powerful predictor for children's school readiness and long-term school outcomes. However, the current research base indicates that children with autism may have an increased likelihood of experiencing deficits in EF or delayed developmental trajectories. Additionally, although there is ample evidence…