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Brendan A. Schuetze – Educational Psychology Review, 2024
The computational model of school achievement represents a novel approach to theorizing school achievement, conceptualizing educational interventions as modifications to students' learning curves. By modeling the process and products of educational achievement simultaneously, this tool addresses several unresolved questions in educational…
Descriptors: Computation, Growth Models, Academic Achievement, Student Evaluation
Kjorte Harra; David Kaplan – Structural Equation Modeling: A Multidisciplinary Journal, 2024
The present work focuses on the performance of two types of shrinkage priors--the horseshoe prior and the recently developed regularized horseshoe prior--in the context of inducing sparsity in path analysis and growth curve models. Prior research has shown that these horseshoe priors induce sparsity by at least as much as the "gold…
Descriptors: Structural Equation Models, Bayesian Statistics, Regression (Statistics), Statistical Inference
Fay, Derek M.; Levy, Roy; Schulte, Ann C. – Journal of Experimental Education, 2022
Longitudinal data structures are frequently encountered in a variety of disciplines in the social and behavioral sciences. Growth curve modeling offers a highly extensible framework that allows for the exploration of rich hypotheses. However, owing to the presence of interrelated sources of potential data-model misfit at multiple levels, the…
Descriptors: Measurement, Models, Bayesian Statistics, Hierarchical Linear Modeling
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
Pei-Hsuan Chiu – ProQuest LLC, 2018
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…
Descriptors: Bayesian Statistics, Scores, Error of Measurement, Growth Models
Reform Support Network, 2015
This publication summarizes the key discussion from experts in the field of measuring student growth during a convening held February 2015. Experts heard about two emerging approaches to measuring growth: Portfolios of student work samples and unit value-added models that provide teachers with timely and actionable feedback that they can use to…
Descriptors: Evaluation Methods, Portfolio Assessment, Teacher Evaluation, Teacher Effectiveness
Wang, Cen; Williams, Kate E.; Shahaeian, Ameneh; Harrison, Linda J. – School Psychology Quarterly, 2018
The objective of this study is to examine the trajectory of internalizing problems across middle childhood among a population sample of Australian children, and to understand the timing of explanatory factors related to children's development of internalizing problems, by using multiple-indicator latent growth curve modeling. Participants were…
Descriptors: Predictor Variables, Behavior Problems, Parenting Styles, Parent Child Relationship