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Daniel Murphy; Sarah Quesen; Matthew Brunetti; Quintin Love – Educational Measurement: Issues and Practice, 2024
Categorical growth models describe examinee growth in terms of performance-level category transitions, which implies that some percentage of examinees will be misclassified. This paper introduces a new procedure for estimating the classification accuracy of categorical growth models, based on Rudner's classification accuracy index for item…
Descriptors: Classification, Growth Models, Accuracy, Performance Based Assessment
Katherine E. Castellano; Daniel F. McCaffrey; Joseph A. Martineau – Educational Measurement: Issues and Practice, 2025
Growth-to-standard models evaluate student growth against the growth needed to reach a future standard or target of interest, such as proficiency. A common growth-to-standard model involves comparing the popular Student Growth Percentile (SGP) to Adequate Growth Percentiles (AGPs). AGPs follow from an involved process based on fitting a series of…
Descriptors: Student Evaluation, Growth Models, Student Educational Objectives, Educational Indicators
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
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
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