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New York State Education Department, 2023
The New York State Education Department (NYSED) has a partnership with Questar Assessment Inc. (Questar) for the online delivery of the 2023 Elementary-Level (Grade 5) and Intermediate-Level (Grade 8) Science Computer-Based Field Tests. Teachers from across the State work with NYSED in a variety of activities to ensure the validity and reliability…
Descriptors: Testing Programs, Elementary School Students, Grade 5, Middle School Students
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National Assessment of Educational Progress (NAEP), 2023
The National Assessment of Educational Progress (NAEP) is an integral measure of academic progress across the nation and over time. It is the largest nationally representative and continuing assessment of what our nation's students know and can do in various subjects such as mathematics, reading, and science. The program also provides valuable…
Descriptors: School Districts, Educational Assessment, Grade 4, Grade 8
New York State Education Department, 2022
The New York State Education Department (NYSED) has a partnership with Questar Assessment Inc. (Questar) for the online delivery of the 2022 Elementary-Level (Grade 5) and Intermediate-Level (Grade 8) Science Computer-Based Field Tests. Teachers from across the State work with NYSED in a variety of activities to ensure the validity and reliability…
Descriptors: Testing Programs, Elementary School Students, Grade 5, Middle School Students
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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
New York State Education Department, 2020
The New York State Education Department (NYSED) has a partnership with Questar Assessment Inc. (Questar) for the development of the 2020 Grades 3-8 English Language Arts Tests. Teachers from across the State work with NYSED in a variety of activities to ensure the validity and reliability of the New York State Testing Program (NYSTP). The 2020…
Descriptors: Grade 6, Grade 7, Grade 8, English
New York State Education Department, 2022
The instructions in this manual explain the responsibilities of school administrators for the New York State Testing Program (NYSTP) Grades 3-8 English Language Arts and Mathematics Field Tests, and the Elementary-level (Grade 5) and Intermediate-level (Grade 8) Science Field Tests. School administrators must be thoroughly familiar with the…
Descriptors: Testing Programs, Mathematics Tests, Test Format, Computer Assisted Testing
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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
New York State Education Department, 2020
The New York State Education Department (NYSED) has a partnership with Questar Assessment Inc. (Questar) for the development of the 2020 Grades 3-8 English Language Arts Tests. Teachers from across the State work with NYSED in a variety of activities to ensure the validity and reliability of the New York State Testing Program (NYSTP). The 2020…
Descriptors: Testing Programs, Language Arts, Language Tests, Computer Assisted Testing
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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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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