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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
Giada Spaccapanico Proietti; Mariagiulia Matteucci; Stefania Mignani; Bernard P. Veldkamp – Journal of Educational and Behavioral Statistics, 2024
Classical automated test assembly (ATA) methods assume fixed and known coefficients for the constraints and the objective function. This hypothesis is not true for the estimates of item response theory parameters, which are crucial elements in test assembly classical models. To account for uncertainty in ATA, we propose a chance-constrained…
Descriptors: Automation, Computer Assisted Testing, Ambiguity (Context), Item Response Theory
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
Russell, Michael; Moncaleano, Sebastian – Educational Assessment, 2019
Over the past decade, large-scale testing programs have employed technology-enhanced items (TEI) to improve the fidelity with which an item measures a targeted construct. This paper presents findings from a review of released TEIs employed by large-scale testing programs worldwide. Analyses examine the prevalence with which different types of TEIs…
Descriptors: Computer Assisted Testing, Fidelity, Elementary Secondary Education, Test Items
Bukhari, Nurliyana – ProQuest LLC, 2017
In general, newer educational assessments are deemed more demanding challenges than students are currently prepared to face. Two types of factors may contribute to the test scores: (1) factors or dimensions that are of primary interest to the construct or test domain; and, (2) factors or dimensions that are irrelevant to the construct, causing…
Descriptors: Item Response Theory, Models, Psychometrics, Computer Simulation
Wise, Steven L. – Measurement: Interdisciplinary Research and Perspectives, 2015
The growing presence of computer-based testing has brought with it the capability to routinely capture the time that test takers spend on individual test items. This, in turn, has led to an increased interest in potential applications of response time in measuring intellectual ability and achievement. Goldhammer (this issue) provides a very useful…
Descriptors: Reaction Time, Measurement, Computer Assisted Testing, Achievement Tests
Hauser, Carl; Thum, Yeow Meng; He, Wei; Ma, Lingling – Educational and Psychological Measurement, 2015
When conducting item reviews, analysts evaluate an array of statistical and graphical information to assess the fit of a field test (FT) item to an item response theory model. The process can be tedious, particularly when the number of human reviews (HR) to be completed is large. Furthermore, such a process leads to decisions that are susceptible…
Descriptors: Test Items, Item Response Theory, Research Methodology, Decision Making
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
Wan, Lei; Henly, George A. – Applied Measurement in Education, 2012
Many innovative item formats have been proposed over the past decade, but little empirical research has been conducted on their measurement properties. This study examines the reliability, efficiency, and construct validity of two innovative item formats--the figural response (FR) and constructed response (CR) formats used in a K-12 computerized…
Descriptors: Test Items, Test Format, Computer Assisted Testing, Measurement
Al-A'ali, Mansoor – Educational Technology & Society, 2007
Computer adaptive testing is the study of scoring tests and questions based on assumptions concerning the mathematical relationship between examinees' ability and the examinees' responses. Adaptive student tests, which are based on item response theory (IRT), have many advantages over conventional tests. We use the least square method, a…
Descriptors: Educational Testing, Higher Education, Elementary Secondary Education, Student Evaluation

Kingsbury, G. Gage; Houser, Ronald L. – Educational Measurement: Issues and Practice, 1993
The utility of item response theory (IRT) models in computerized adaptive tests is considered. Measurement questions that have been answered using IRT, and those that might be overlooked because of IRT, are reviewed. Areas in which fuller use of IRT could improve adaptive testing practices are identified. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Educational Assessment, Elementary Secondary Education

Wainer, Howard; Lewis, Charles – Journal of Educational Measurement, 1990
Three different applications of the testlet concept are presented, and the psychometric models most suitable for each application are described. Difficulties that testlets can help overcome include (1) context effects; (2) item ordering; and (3) content balancing. Implications for test construction are discussed. (SLD)
Descriptors: Algorithms, Computer Assisted Testing, Elementary Secondary Education, Item Response Theory

Patience, Wayne – Journal of Educational Measurement, 1990
The four main subsystems of the MicroCAT Testing System for developing, administering, scoring, and analyzing computerized tests using conventional or item response theory methods are described. Judgments of three users of the system are included in the evaluation of this software. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Computer Software, Computer Software Reviews
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