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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
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
Zsolnai, Anikó; Kasik, László – International Journal of School & Educational Psychology, 2017
The aim of our cross-sectional investigation was to explore prosocial behavior at the ages of 9, 11, and 13, and to reveal associations between this social behavior and some background variables such as age, gender, and parents' educational attainment. The participants were 185 Hungarian students and their teachers. Two Likert-type questionnaires…
Descriptors: Foreign Countries, Computer Assisted Testing, Child Behavior, Prosocial Behavior
Rock, Donald A. – ETS Research Report Series, 2007
This paper presents a strategy for measuring cognitive gains in reading during the early school years. It is argued that accurate estimates of gain scores and their appropriate interpretation requires the use of adaptive tests with multiple criterion referenced points that mark learning milestones. It is further argued that two different measures…
Descriptors: Scores, Cognitive Development, Computation, Test Interpretation