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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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Jochanan Veerbeek; Bart Vogelaar – Journal of Psychoeducational Assessment, 2025
Dynamic testing, though underutilized, holds potential for assessing learning and instructional needs. However, its limited adoption is often attributed to the perceived time and labor-intensive nature of its administration. This study explores the viability of a training-only dynamic test (ToDT) with a standardized procedure to identify…
Descriptors: Educational Needs, Testing, Elementary School Students, Grade 4
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Turner, Megan I.; Van Norman, Ethan R.; Hojnoski, Robin L. – Journal of Psychoeducational Assessment, 2022
Star Math (SM) is a popular computer adaptive test (CAT) schools use to screen students for academic risk. Despite its popularity, few independent investigations of its diagnostic accuracy have been conducted. We evaluated the diagnostic accuracy of SM based upon vendor provided cut-scores (25th and 40th percentiles nationally) in predicting…
Descriptors: Accuracy, Adaptive Testing, Computer Assisted Testing, High Stakes Tests
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Van Norman, Ethan R.; Forcht, Emily R. – Assessment for Effective Intervention, 2023
This study explored the validity of growth on two computer adaptive tests, Star Reading and Star Math, in explaining performance on an end-of-year achievement test for a sample of students in Grades 3 through 6. Results from quantile regression analyses indicate that growth on Star Reading explained a statistically significant amount of variance…
Descriptors: Test Validity, Computer Assisted Testing, Adaptive Testing, Grade Prediction
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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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Ayfer Sayin; Sabiha Bozdag; Mark J. Gierl – International Journal of Assessment Tools in Education, 2023
The purpose of this study is to generate non-verbal items for a visual reasoning test using templated-based automatic item generation (AIG). The fundamental research method involved following the three stages of template-based AIG. An item from the 2016 4th-grade entrance exam of the Science and Art Center (known as BILSEM) was chosen as the…
Descriptors: Test Items, Test Format, Nonverbal Tests, Visual Measures
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McCarthy, Tessa; Schles, Rachel Anne; Moore, Debra W. – Journal of Visual Impairment & Blindness, 2023
Introduction: This study evaluated performance and engagement on the tactile science alternate assessment based on alternate academic standards (AA-AAS). This assessment was designed for students with significant intellectual disabilities and visual impairments (i.e., blindness and low vision). Four primary research questions guided this study.…
Descriptors: Student Evaluation, Alternative Assessment, Science Education, Students with Disabilities
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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
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Elena C. Papanastasiou; Michalis P. Michaelides – Large-scale Assessments in Education, 2024
Test-taking behavior is a potential source of construct irrelevant variance for test scores in international large-scale assessments where test-taking effort, motivation, and behaviors in general tend to be confounded with test scores. In an attempt to disentangle this relationship and gain further insight into examinees' test-taking processes,…
Descriptors: Grade 4, Testing, Student Behavior, Test Wiseness
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Eren Can Aybek; Serkan Arikan; Günes Ertas – International Journal of Assessment Tools in Education, 2024
When it is required to estimate item parameters of a large item bank, Multiple Matrix Sampling (MMS) design provides an efficient way while minimizing the test burden on students. The current study exemplifies how to calibrate a large item pool using MMS design for various purposes, such as developing a CAT administration. The purpose of the…
Descriptors: Elementary School Mathematics, Elementary School Students, Grade 4, Item Banks
Goodwin, Amanda P.; Petscher, Yaacov; Tock, Jamie; McFadden, Sara; Reynolds, Dan; Lantos, Tess; Jones, Sara – Assessment for Effective Intervention, 2022
Assessment of language skills for upper elementary and middle schoolers is important due to the strong link between language and reading comprehension. Yet, currently few practical, reliable, valid, and instructionally informative assessments of language exist. This study provides validation evidence for Monster, P.I., which is a gamified,…
Descriptors: Adaptive Testing, Computer Assisted Testing, Language Tests, Vocabulary
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Jewsbury, Paul A.; van Rijn, Peter W. – Journal of Educational and Behavioral Statistics, 2020
In large-scale educational assessment data consistent with a simple-structure multidimensional item response theory (MIRT) model, where every item measures only one latent variable, separate unidimensional item response theory (UIRT) models for each latent variable are often calibrated for practical reasons. While this approach can be valid for…
Descriptors: Item Response Theory, Computation, Test Items, Adaptive Testing
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Steven L. Wise; Megan R. Kuhfeld; Marlit Annalena Lindner – Applied Measurement in Education, 2024
When student achievement is assessed, we seek to elicit a student's maximum performance -- a goal requiring the assumption that the student is fully engaged. Otherwise, to the extent that disengagement occurs, test performance is likely to suffer. Effectively managing test-taking disengagement requires an understanding of the testing conditions…
Descriptors: Testing, Attention Span, Learner Engagement, Time Factors (Learning)
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Alice Lemmo – International Journal of Mathematical Education in Science and Technology, 2025
The use of digital technologies in teaching and learning processes has opened new and wide frontiers in mathematics education. Research in education moves towards teaching and learning (and assessing) twenty-first-century skills and computer-based testing seems an interesting possibility for assessing such skills. From this perspective, comparing…
Descriptors: Computer Assisted Testing, Paper and Pencil Tests, Problem Solving, Mathematics Tests
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Ethan Roy; Mathieu Guillaume; Amandine Van Rinsveld; Project iLead Consortium; Bruce D. McCandliss – npj Science of Learning, 2025
Arithmetic fluency is regarded as a foundational math skill, typically measured as a single construct with pencil-and-paper-based timed assessments. We introduce a tablet-based assessment of single-digit fluency that captures individual trial response times across several embedded experimental contrasts of interest. A large (n = 824) cohort of…
Descriptors: Arithmetic, Mathematics Skills, Tablet Computers, Grade 3
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