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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
Howard, Christy M.; Miller, Sam – Urban Education, 2022
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,…
Descriptors: Middle School Teachers, Merit Pay, Teacher Salaries, Incentives
Marcoulides, Katerina M. – Measurement: Interdisciplinary Research and Perspectives, 2019
Longitudinal data analysis has received widespread interest throughout educational, behavioral, and social science research, with latent growth curve modeling currently being one of the most popular methods of analysis. Despite the popularity of latent growth curve modeling, limited attention has been directed toward understanding the issues of…
Descriptors: Reliability, Longitudinal Studies, Growth Models, Structural Equation Models
Wells, Craig S.; Sireci, Stephen G. – Applied Measurement in Education, 2020
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…
Descriptors: Growth Models, Reliability, Scores, Error Patterns
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
Daria Khanolainen; Maria Psyridou; Kenneth Eklund; Tuija Aro; Minna Torppa – Scientific Studies of Reading, 2024
Purpose: Reading fluency establishes the basis for the strong literacy skills needed for academic success. We aim to trace how reading fluency develops from childhood to adulthood and identify factors that influence this development. Method: In this study, 200 families were followed. All participating children (N = 200, 47% female) were ethnic…
Descriptors: Reading Fluency, Growth Models, Student Development, Children
Seohyeon Choi; Emma Shanahan; Jechun An; Kristen McMaster – Assessment for Effective Intervention, 2023
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…
Descriptors: Progress Monitoring, Elementary School Students, Verbal Communication, Curriculum Based Assessment
Forthmann, Boris; Förster, Natalie; Souvignier, Elmar – Journal of Intelligence, 2022
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…
Descriptors: Learning Processes, Progress Monitoring, Robustness (Statistics), Bayesian Statistics
McNeill, Brigid; McIlraith, Autumn L.; Macrae, Toby; Gath, Megan; Gillon, Gail – Journal of Speech, Language, and Hearing Research, 2022
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…
Descriptors: Predictor Variables, Speech Language Pathology, Communication Disorders, Language Impairments
Li, Wei; Konstantopoulos, Spyros – Journal of Experimental Education, 2019
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…
Descriptors: Research Design, Statistical Analysis, Sample Size, Effect Size
Soland, James; Thum, Yeow Meng – Journal of Research on Educational Effectiveness, 2022
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,…
Descriptors: Academic Achievement, Longitudinal Studies, Data Use, Computation
Zhan, Peida; Jiao, Hong; Liao, Dandan; Li, Feiming – Journal of Educational and Behavioral Statistics, 2019
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…
Descriptors: Classification, Growth Models, Educational Diagnosis, Models
Parker, David C.; Burns, Matthew K.; McMaster, Kristen L.; Al Otaiba, Stephanie; Medhanie, Amanuel – Assessment for Effective Intervention, 2018
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…
Descriptors: Writing Instruction, Grade 1, Elementary School Students, Emergent Literacy
Briggs, Derek C.; Chattergoon, Rajendra; Burkhardt, Amy – Journal of Educational Measurement, 2019
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…
Descriptors: Student Educational Objectives, Student Evaluation, Teacher Evaluation, Scores