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Wyse, Adam E. – Educational and Psychological Measurement, 2021
An essential question when computing test--retest and alternate forms reliability coefficients is how many days there should be between tests. This article uses data from reading and math computerized adaptive tests to explore how the number of days between tests impacts alternate forms reliability coefficients. Results suggest that the highest…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Reliability, Reading Tests
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Wise, Steven L.; Soland, James; Dupray, Laurence M. – Journal of Applied Testing Technology, 2021
Technology-Enhanced Items (TEIs) have been purported to be more motivating and engaging to test takers than traditional multiple-choice items. The claim of enhanced engagement, however, has thus far received limited research attention. This study examined the rates of rapid-guessing behavior received by three types of items (multiple-choice,…
Descriptors: Test Items, Guessing (Tests), Multiple Choice Tests, Achievement Tests
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Wyse, Adam E.; McBride, James R. – Measurement: Interdisciplinary Research and Perspectives, 2022
A common practical challenge is how to assign ability estimates to all incorrect and all correct response patterns when using item response theory (IRT) models and maximum likelihood estimation (MLE) since ability estimates for these types of responses equal -8 or +8. This article uses a simulation study and data from an operational K-12…
Descriptors: Scores, Adaptive Testing, Computer Assisted Testing, Test Length
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MacGregor, David; Yen, Shu Jing; Yu, Xin – Language Assessment Quarterly, 2022
How can one construct a test that provides accurate measurements across the range of performance levels while providing adequate coverage of all of the critical areas of the domain, yet that is not unmanageably long? This paper discusses the approach taken in a linear test of academic English language, and how the transition to a computer-based…
Descriptors: Language Tests, Language Proficiency, Computer Assisted Testing, Adaptive Testing
He, Wei – NWEA, 2022
To ensure that student academic growth in a subject area is accurately captured, it is imperative that the underlying scale remains stable over time. As item parameter stability constitutes one of the factors that affects scale stability, NWEA® periodically conducts studies to check for the stability of the item parameter estimates for MAP®…
Descriptors: Achievement Tests, Test Items, Test Reliability, Academic Achievement
Davis, Marcia H.; Wang, Wenhao; Kingston, Neal M.; Hock, Michael; Tonks, Stephen M.; Tiemann, Gail – Grantee Submission, 2020
Background: The importance of reading motivation has led to the development of a large number of self-report reading motivation measures; however, there is still a need for a usable measure of adolescent reading motivation that captures a large number of theoretically and empirically distinct constructs. Methods: The current paper details the…
Descriptors: Reading Motivation, Computer Assisted Testing, Adaptive Testing, Measures (Individuals)
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Sun, Bo; Zhu, Yunzong; Xiao, Yongkang; Xiao, Rong; Wei, Yungang – IEEE Transactions on Learning Technologies, 2019
In recent years, computerized adaptive testing (CAT) has gained popularity as an important means to evaluate students' ability. Assigning tags to test questions is crucial in CAT. Manual tagging is widely used for constructing question banks; however, this approach is time-consuming and might lead to consistency issues. Automatic question tagging,…
Descriptors: Computer Assisted Testing, Student Evaluation, Test Items, Multiple Choice Tests
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Foorman, Barbara R.; Petscher, Yaacov; Stanley, Christopher; Truckenmiller, Adrea – Journal of Research on Educational Effectiveness, 2017
The objective of this study was to determine the latent profiles of reading and language skills that characterized 7,752 students in kindergarten through tenth grade and to relate the profiles to norm-referenced reading outcomes. Reading and language skills were assessed with a computer-adaptive assessment administered in the middle of the year…
Descriptors: Reading Comprehension, Statistical Analysis, Computer Assisted Testing, Adaptive Testing
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Lee, Jaemu; Park, Sanghoon; Kim, Kwangho – Turkish Online Journal of Distance Education, 2012
Computer Adaptive Testing (CAT) has been highlighted as a promising assessment method to fulfill two testing purposes: estimating student academic ability and classifying student academic level. In this paper, assessment for we introduced the Web-based Adaptive Testing System (WATS) developed to support a cost effective assessment for classifying…
Descriptors: Academic Ability, Academic Support Services, Adaptive Testing, Computer Assisted Testing
Northwest Evaluation Association, 2013
While many educators expect the Common Core State Standards (CCSS) to be more rigorous than previous state standards, some wonder if the transition to CCSS and to a Common Core aligned MAP test will have an impact on their students' RIT scores or the NWEA norms. MAP assessments use a proprietary scale known as the RIT (Rasch unit) scale to measure…
Descriptors: Achievement Tests, Computer Assisted Testing, Adaptive Testing, Item Response Theory
Foorman, Barbara R.; Petscher, Yaacov; Schatschneider, Chris – Florida Center for Reading Research, 2015
The FAIR-FS consists of computer-adaptive reading comprehension and oral language screening tasks that provide measures to track growth over time, as well as a Probability of Literacy Success (PLS) linked to grade-level performance (i.e., the 40th percentile) on the reading comprehension subtest of the Stanford Achievement Test (SAT-10) in the…
Descriptors: Reading Instruction, Screening Tests, Reading Comprehension, Oral Language
Wang, Shudong; Jiao, Hong; He, Wei – Online Submission, 2011
The ability estimation procedure is one of the most important components in a computerized adaptive testing (CAT) system. Currently, all CATs that provide K-12 student scores are based on the item response theory (IRT) model(s); while such application directly violates the assumption of independent sample of a person in IRT models because ability…
Descriptors: Accuracy, Computation, Computer Assisted Testing, Adaptive Testing
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Lane, Suzanne; Leventhal, Brian – Review of Research in Education, 2015
This chapter addresses the psychometric challenges in assessing English language learners (ELLs) and students with disabilities (SWDs). The first section addresses some general considerations in the assessment of ELLs and SWDs, including the prevalence of ELLs and SWDs in the student population, federal and state legislation that requires the…
Descriptors: Psychometrics, Evaluation Problems, English Language Learners, Disabilities
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Stone, Elizabeth; Davey, Tim – ETS Research Report Series, 2011
There has been an increased interest in developing computer-adaptive testing (CAT) and multistage assessments for K-12 accountability assessments. The move to adaptive testing has been met with some resistance by those in the field of special education who express concern about routing of students with divergent profiles (e.g., some students with…
Descriptors: Computer Assisted Testing, Adaptive Testing, Disabilities, Special Education
Edwards, Virginia B., Ed. – Education Week, 2014
Figuring out how to use digital tools to transform testing requires a willingness to invest in new technologies and the patience to experiment with novel approaches, a commitment to ongoing professional development and reliable technical support, and an openness to learn from mistakes. Whatever bumpy ride this technological journey takes, experts…
Descriptors: Elementary Secondary Education, Technological Advancement, Testing, Computer Assisted Testing
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