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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
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
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
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
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: Testing Programs, Language Arts, Language Tests, Computer Assisted Testing
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
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)
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 Mathematics 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 Grades 3-5…
Descriptors: Mathematics Tests, Computer Assisted Testing, Scheduling, Testing
Peltier, Corey; Vannest, Kimberly J.; Tomaszewski, Brianne R.; Morin, Kristi; Sallese, Mary Rose; Pulos, Joshua M. – Exceptionality, 2022
The current study examined the criterion validity of a computer adaptive universal screener with an end-of-year state mathematics assessment using extant data provided by a local education agency. Participants included 1,195 third through eighth graders. Correlational analyses were used to report predictive and concurrent validity coefficients for…
Descriptors: Adaptive Testing, Computer Assisted Testing, Screening Tests, Mathematics Tests
New York State Education Department, 2019
The New York State Education Department (NYSED) has a partnership with Questar Assessment Inc. (Questar) for the development of the 2019 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 2019…
Descriptors: English, Language Arts, Computer Assisted Testing, Testing
New York State Education Department, 2020
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 Tests. School administrators must be thoroughly familiar with the contents of the manual, and the policies and procedures must be followed as written so that testing…
Descriptors: Testing Programs, Mathematics Tests, Test Format, Computer Assisted Testing
Mustafa Yildiz; Hasan Kagan Keskin; Saadin Oyucu; Douglas K. Hartman; Murat Temur; Mücahit Aydogmus – Reading & Writing Quarterly, 2025
This study examined whether an artificial intelligence-based automatic speech recognition system can accurately assess students' reading fluency and reading level. Participants were 120 fourth-grade students attending public schools in Türkiye. Students read a grade-level text out loud while their voice was recorded. Two experts and the artificial…
Descriptors: Artificial Intelligence, Reading Fluency, Human Factors Engineering, Grade 4
Solano-Flores, Guillermo; Shyyan, Vitaliy; Chía, Magda; Kachchaf, Rachel – International Multilingual Research Journal, 2023
We examined semiotic exchangeability in pop-up glossary translations and illustrations used as supports for second language learners (SLLs) in computer-administered mathematics tests. In a sample of 516 mathematics items, Grades 3-8 and 11, from a large-scale assessment program in the US, test developers identified terms that could be translated…
Descriptors: Mathematics Tests, Testing Accommodations, Test Items, Semiotics
VanMeveren, Kalie; Hulac, David; Wollersheim-Shervey, Sarah – Assessment for Effective Intervention, 2020
Reading screening assessments help educators identify students who are at risk of reading and determine the need for intervention and supports. However, some schools screen and assess students more often than needed, and the additional information does not improve the accuracy of decisions. This may be especially true for students at the upper…
Descriptors: Reading Tests, Screening Tests, Elementary School Students, High Stakes Tests