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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
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
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
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
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
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
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
Ochs, Sarah; Keller-Margulis, Milena A.; Santi, Kristi L.; Jones, John H. – Assessment for Effective Intervention, 2020
Universal screening is the first mechanism by which students are identified as at risk of failure in the context of multitiered systems of supports. This study examined the validity and diagnostic accuracy of a reading computer-adaptive test as a screener to identify state achievement test performance for third through fifth graders (N = 1,696).…
Descriptors: Adaptive Testing, Computer Assisted Testing, Accuracy, Reading Tests
Van Norman, Ethan R.; Ysseldyke, James E. – School Psychology Review, 2020
Within multitiered systems of support, assessment practices that limit the amount of time students miss instruction should be prioritized. At the same time, decisions about student response to intervention need to be based upon technically adequate data. We evaluated the impact of data collection frequency and trend estimation method on the…
Descriptors: Data Collection, Adaptive Testing, Computer Assisted Testing, Computation
Van Norman, Ethan R.; Nelson, Peter M.; Parker, David C. – School Psychology Quarterly, 2017
Computer adaptive tests (CATs) hold promise to monitor student progress within multitiered systems of support. However, the relationship between how long and how often data are collected and the technical adequacy of growth estimates from CATs has not been explored. Given CAT administration times, it is important to identify optimal data…
Descriptors: Computer Assisted Testing, Progress Monitoring, Grade 4, Grade 5
Li, Sylvia; Meyer, Patrick – NWEA, 2019
This simulation study examines the measurement precision, item exposure rates, and the depth of the MAP® Growth™ item pools under various grade-level restrictions. Unlike most summative assessments, MAP Growth allows examinees to see items from any grade level, regardless of the examinee's actual grade level. It does not limit the test to items…
Descriptors: Achievement Tests, Item Banks, Test Items, Instructional Program Divisions
Molnar, Gyongyver; Hodi, Agnes; Magyar, Andrea – AERA Online Paper Repository, 2016
Vocabulary knowledge assessment methods and instruments have gone through a significant evolution. Computer-based tests offer more opportunities than their paper-and-pencil counterparts, however, most digital vocabulary assessments are linear and adaptive solutions in this domain are scarce. The aims of this study were to compare the effectiveness…
Descriptors: Adaptive Testing, Vocabulary Skills, Computer Assisted Testing, Student Evaluation
Foorman, Barbara; Espinosa, Anabel; Wood, Carla; Wu, Yi-Chieh – Regional Educational Laboratory Southeast, 2016
A top education priority in the United States is to address the needs of one of the fastest growing yet lowest performing student populations--English learner students (Capps et al., 2005). English learner students come from homes where a non-English language is spoken and need additional academic support to access the mainstream curriculum. These…
Descriptors: Computer Assisted Testing, Adaptive Testing, Literacy, English Language Learners
Wei, Hua; Lin, Jie – International Journal of Testing, 2015
Out-of-level testing refers to the practice of assessing a student with a test that is intended for students at a higher or lower grade level. Although the appropriateness of out-of-level testing for accountability purposes has been questioned by educators and policymakers, incorporating out-of-level items in formative assessments for accurate…
Descriptors: Test Items, Computer Assisted Testing, Adaptive Testing, Instructional Program Divisions
Shapiro, Edward S.; Dennis, Minyi Shih; Fu, Qiong – School Psychology Quarterly, 2015
The purpose of the study was to compare the use of a Computer Adaptive Test and Curriculum-Based Measurement in the assessment of mathematics. This study also investigated the degree to which slope or rate of change predicted student outcomes on the annual state assessment of mathematics above and beyond scores of single point screening…
Descriptors: Computer Assisted Testing, Adaptive Testing, Curriculum Based Assessment, Mathematics Tests
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