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Samira Syal; Marcia Davis; Xiaodong Zhang; Jason Schoeneberger; Samantha Spinney; Douglas J. Mac Iver; Martha Mac Iver – Reading Psychology, 2024
Motivation to read is crucial to improving reading skill. While there is extensive research examining reading motivation among elementary students, with respect to adolescents, research is limited. Employing a person-centered approach can aid in developing a better understanding of adolescent reading motivation and would help address possible…
Descriptors: Reading Motivation, Adolescents, Reading Achievement, High School Students
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Emily R. Forcht; Ethan R. Van Norman – Psychology in the Schools, 2024
The present study compared the diagnostic accuracy of a single computer adaptive test (CAT), Star Reading or Star Math, and a combination of the two in a gated screening framework to predict end-of-year proficiency in reading and math. Participants included 13,009 students in Grades 3-8 who had at least one fall screening score and end-of-year…
Descriptors: Computer Assisted Testing, Adaptive Testing, Diagnostic Tests, Screening Tests
Kristen Panzarella; Angela Walmsley – Phi Delta Kappan, 2025
Computer-based testing is becoming dominant for assessments in education. In New York, students take state assessments, which are now administered digitally. While this transition in technology offers advantages, there are also challenges, including insufficient digital literacy for students to adequately meet the technological demands of the…
Descriptors: Computer Assisted Testing, Standardized Tests, Barriers, Tests
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Ethan R. Van Norman; Emily R. Forcht – Assessment for Effective Intervention, 2024
Curriculum-based measurement of reading (CBM-R) is a common assessment educators use to monitor student growth in broad reading skills and evaluate the effectiveness of instructional programs. Computer-adaptive tests (CATs), such as Star Reading, have been cited as a viable option to formatively assess reading growth. We used Bayesian…
Descriptors: Reading Improvement, Reading Skills, Reading Achievement, Curriculum Based Assessment
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Nikola Ebenbeck; Morten Bastian; Andreas Mühling; Markus Gebhardt – Journal of Computer Assisted Learning, 2024
Background: Computerised adaptive tests (CATs) are tests that provide personalised, efficient and accurate measurement while reducing testing time, depending on the desired level of precision. Schools have different types of assessments that can benefit from a significant reduction in testing time to varying degrees, depending on the area of…
Descriptors: Computer Assisted Testing, Elementary Secondary Education, Public Schools, Special Schools
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Kayla V. Campaña; Benjamin G. Solomon – Assessment for Effective Intervention, 2025
The purpose of this study was to compare the classification accuracy of data produced by the previous year's end-of-year New York state assessment, a computer-adaptive diagnostic assessment ("i-Ready"), and the gating combination of both assessments to predict the rate of students passing the following year's end-of-year state assessment…
Descriptors: Accuracy, Classification, Diagnostic Tests, Adaptive Testing
Matthias von Davier, Editor; Ann Kennedy, Editor – International Association for the Evaluation of Educational Achievement, 2024
The Progress in International Reading Literacy Study (PIRLS) has been monitoring international trends in reading achievement among fourth-grade students for 25 years. As a critical point in a student's education, the fourth year of schooling establishes the foundations of literacy, with reading becoming increasingly central to learning across all…
Descriptors: Reading Achievement, Foreign Countries, Grade 4, International Assessment
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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