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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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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
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Keller-Margulis, Milena; McQuillin, Samuel D.; Castañeda, Juan Javier; Ochs, Sarah; Jones, John H. – Journal of Applied School Psychology, 2018
Multitiered systems of support depend on screening technology to identify students at risk. The purpose of this study was to examine the use of a computer-adaptive test and latent class growth analysis (LCGA) to identify students at risk in reading with focus on the use of this methodology to characterize student performance in screening.…
Descriptors: At Risk Students, Multivariate Analysis, Adaptive Testing, Computer Assisted Testing