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Nathan Helsabeck; Jessica A. R. Logan – International Journal of Research & Method in Education, 2024
Assessing student achievement over multiple years is complicated by students' memberships in shifting upper-level nesting structures. These structures are manifested in (1) annual matriculation to different classrooms and (2) mobility between schools. Failure to model these shifting upper-level nesting structures may bias the inferences…
Descriptors: Academic Achievement, Student Evaluation, Growth Models, Data Analysis
How Should States Choose a Growth Model? Aligning Your Growth Model with Policy and Technical Values
Scott Marion; Chris Domaleski; Will Lorié – National Center for the Improvement of Educational Assessment, 2025
Federal law requires that state accountability systems include "another academic indicator" for elementary and middle schools in addition to academic achievement. Nearly all states use a measure of student longitudinal growth as their other academic indicator. But how should states decide which growth model to use? The Center for…
Descriptors: Federal Legislation, Accountability, Educational Indicators, Federal State Relationship
Shayla Wiggins Savage – ProQuest LLC, 2024
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,…
Descriptors: Teacher Leadership, Discipline, Teacher Persistence, Grades (Scholastic)
Hurst, Lucas T. – ProQuest LLC, 2022
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…
Descriptors: Reading Achievement, Mathematics Achievement, Growth Models, High Achievement
Sanford R. Student; Derek C. Briggs; Laurie Davis – Educational Measurement: Issues and Practice, 2025
Vertical scales are frequently developed using common item nonequivalent group linking. In this design, one can use upper-grade, lower-grade, or mixed-grade common items to estimate the linking constants that underlie the absolute measurement of growth. Using the Rasch model and a dataset from Curriculum Associates' i-Ready Diagnostic in math in…
Descriptors: Elementary School Mathematics, Elementary School Students, Middle School Mathematics, Middle School Students
Antonio A. Morgan-López; Lissette M. Saavedra; Heather L. McDaniel; Stephen G. West; Nicholas S. Ialongo; Catherine P. Bradshaw; Alexandra T. Tonigan; Barrett W. Montgomery; Nicole P. Powell; Lixin Qu; Anna C. Yaros; John E. Lochman – Grantee Submission, 2024
Coping Power (CP) is a preventive intervention that focuses on reducing child externalizing problems. Although it is typically delivered in a group format (GCP), individually-delivered CP (ICP) has produced greater mean reductions in externalizing problems. However, standard analysis of randomized trials loses individual-level information…
Descriptors: Coping, Prevention, Intervention, Child Behavior
Sohyun An Kim – ProQuest LLC, 2022
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…
Descriptors: Executive Function, Autism Spectrum Disorders, Children, Longitudinal Studies
Sohyun An Kim; Connie Kasari – Journal of Autism and Developmental Disorders, 2025
While working memory (WM) is a powerful predictor for children's school outcomes, autistic children are more likely to experience delays. This study compared autistic children and their neurotypical peers' WM development over their elementary school years, including relative growth and period of plasticity. Using a nationally-representative…
Descriptors: Elementary School Students, Autism Spectrum Disorders, Students with Disabilities, Student Development
Huang Wu; Jianping Shen; Xin Li; Megan Russell Johnson; Huilan Y. Krenn – Early Childhood Education Journal, 2025
Michigan's Great Start Readiness Program (GSRP) is a state-funded pre-K program that serves at risk four-year-old children across the state. Utilizing longitudinal data from 1,394 children in a mid-sized urban school district, we conducted regression analyses and piecewise linear growth models to examine the growth trajectory of GSRP children and…
Descriptors: State Programs, School Readiness, Preschool Education, At Risk Students
Dong, Yixiao; Dumas, Denis; Clements, Douglas H.; Sarama, Julie – Journal of Experimental Education, 2023
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…
Descriptors: Measurement Techniques, Simulation, Student Development, Educational Research
Heck, Ronald H.; Reid, Tingting; Leckie, George – School Effectiveness and School Improvement, 2022
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…
Descriptors: Student Mobility, Mathematics Achievement, Growth Models, Educational Improvement
Boorse, Jaclin; Van Norman, Ethan R. – Psychology in the Schools, 2021
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…
Descriptors: Achievement Tests, Mathematics Tests, Adaptive Testing, Computer Assisted Testing
Nazari, Sanaz; Leite, Walter L.; Huggins-Manley, A. Corinne – Journal of Experimental Education, 2023
The piecewise latent growth models (PWLGMs) can be used to study changes in the growth trajectory of an outcome due to an event or condition, such as exposure to an intervention. When there are multiple outcomes of interest, a researcher may choose to fit a series of PWLGMs or a single parallel-process PWLGM. A comparison of these models is…
Descriptors: Growth Models, Statistical Analysis, Intervention, Comparative Analysis
Karen Ramlackhan; Yan Wang – Urban Education, 2024
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…
Descriptors: Urban Schools, Academic Achievement, Mathematics Education, English Curriculum
Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
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…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
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