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Kayla V. Campaña; Benjamin G. Solomon – Assessment for Effective Intervention, 2025
The purpose of this study was to compare the classification accuracy of data produced by the previous year's end-of-year New York state assessment, a computer-adaptive diagnostic assessment ("i-Ready"), and the gating combination of both assessments to predict the rate of students passing the following year's end-of-year state assessment…
Descriptors: Accuracy, Classification, Diagnostic Tests, Adaptive Testing
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Thomas, Asia S.; January, Stacy-Ann A. – Assessment for Effective Intervention, 2021
Educators use universal screening to identify students who may be at risk for not meeting proficiency on the state assessment. Given the potential high-stakes of state tests, using accurate screeners is critical. Independent research is emerging on screeners such as the Measures of Academic Progress (MAP), a computer adaptive test, and the…
Descriptors: Reading Tests, Screening Tests, Test Validity, Accuracy
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Ilhan, Mustafa; Tasdelen Teker, Gülsen; Güler, Nese; Ergenekon, Ömer – Journal of Psychoeducational Assessment, 2022
Today, emoji have become a popular option for anchoring the categories of Likert-type scales applied to not only adults but also children. The aim of this study was to investigate the effects of category labeling with emoji by comparing the psychometric properties of the emoji- and verbal-anchored versions of the mathematics motivation scale…
Descriptors: Computer Mediated Communication, Nonverbal Communication, Visual Aids, Classification
Alonzo, Julie; Anderson, Daniel – Behavioral Research and Teaching, 2018
In response to a request for additional analyses, in particular reporting confidence intervals around the results, we re-analyzed the data from prior studies. This supplementary report presents the results of the additional analyses addressing classification accuracy, reliability, and criterion-related validity evidence. For ease of reference, we…
Descriptors: Curriculum Based Assessment, Computation, Statistical Analysis, Accuracy
Alonzo, Julie; Anderson, Daniel – Behavioral Research and Teaching, 2018
In response to a request for additional analyses, in particular reporting confidence intervals around the results, we re-analyzed the data from prior studies. This supplementary report presents the results of the additional analyses addressing classification accuracy, reliability, and criterion-related validity evidence. For ease of reference, we…
Descriptors: Curriculum Based Assessment, Computation, Statistical Analysis, Classification
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Hartman, Kelsey; Gresham, Frank M.; Byrd, Shelby – Behavioral Disorders, 2017
Universal screening for emotional and behavioral risk in schools facilitates early identification and intervention for students as part of multitiered systems of support. Early identification has the potential to mitigate adverse outcomes of emotional and behavioral disorders. The purpose of this study was to extend existing research on the…
Descriptors: Behavior Problems, Screening Tests, Test Validity, Test Reliability
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Sideridis, Georgios; Padeliadu, Susana – Journal of Learning Disabilities, 2013
The purpose of the present studies was to provide the means to create brief versions of instruments that can aid the diagnosis and classification of students with learning disabilities and comorbid disorders (e.g., attention-deficit/hyperactivity disorder). A sample of 1,108 students with and without a diagnosis of learning disabilities took part…
Descriptors: Test Construction, Learning Disabilities, Disability Identification, Classification
Anderson, Daniel; Alonzo, Julie; Tindal, Gerald – Behavioral Research and Teaching, 2011
In this technical report, we document the results of a cross-validation study designed to identify optimal cut-scores for the use of the easyCBM[R] mathematics test in the state of Washington. A large sample, randomly split into two groups of roughly equal size, was used for this study. Students' performance classification on the Washington state…
Descriptors: Testing Programs, Mathematics Tests, Prediction, Measurement Techniques
Park, Bitnara Jasmine; Irvin, P. Shawn; Anderson, Daniel; Alonzo, Julie; Tindal, Gerald – Behavioral Research and Teaching, 2011
This technical report presents results from a cross-validation study designed to identify optimal cut scores when using easyCBM[R] reading tests in Oregon. The cross-validation study analyzes data from the 2009-2010 academic year for easyCBM[R] reading measures. A sample of approximately 2,000 students per grade, randomly split into two groups of…
Descriptors: Testing Programs, Reading Tests, Prediction, Measurement Techniques
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Protopapas, Athanassios; Skaloumbakas, Christos; Bali, Persefoni – Learning Disabilities: A Contemporary Journal, 2008
After reviewing past efforts related to computer-based reading disability (RD) assessment, we present a fully automated screening battery that evaluates critical skills relevant for RD diagnosis designed for unsupervised application in the Greek educational system. Psychometric validation in 301 children, 8-10 years old (grades 3 and 4; including…
Descriptors: Reading Difficulties, Discriminant Analysis, Classification, Computer Assisted Testing
Renshaw, Tyler L.; Eklund, Katie; Dowdy, Erin; Jimerson, Shane R.; Hart, Shelley R.; Earhart, James, Jr.; Jones, Camille N. – California School Psychologist, 2009
Universal screening of emotional and behavioral problems among students warrants further consideration by school professionals. School-based universal screening may provide opportunities for early identification and intervention, ultimately preventing the development of more severe problems and promoting more positive outcomes in the future. The…
Descriptors: Screening Tests, Test Validity, Disability Identification, Scores