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Ye Ma; Deborah J. Harris – Educational Measurement: Issues and Practice, 2025
Item position effect (IPE) refers to situations where an item performs differently when it is administered in different positions on a test. The majority of previous research studies have focused on investigating IPE under linear testing. There is a lack of IPE research under adaptive testing. In addition, the existence of IPE might violate Item…
Descriptors: Computer Assisted Testing, Adaptive Testing, Item Response Theory, Test Items
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Pan, Yiqin; Livne, Oren; Wollack, James A.; Sinharay, Sandip – Educational Measurement: Issues and Practice, 2023
In computerized adaptive testing, overexposure of items in the bank is a serious problem and might result in item compromise. We develop an item selection algorithm that utilizes the entire bank well and reduces the overexposure of items. The algorithm is based on collaborative filtering and selects an item in two stages. In the first stage, a set…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
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Hwanggyu Lim; Kyung T. Han – Educational Measurement: Issues and Practice, 2024
Computerized adaptive testing (CAT) has gained deserved popularity in the administration of educational and professional assessments, but continues to face test security challenges. To ensure sustained quality assurance and testing integrity, it is imperative to establish and maintain multiple stable item pools that are consistent in terms of…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Banks
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Lewis, Jennifer; Lim, Hwanggyu; Padellaro, Frank; Sireci, Stephen G.; Zenisky, April L. – Educational Measurement: Issues and Practice, 2022
Setting cut scores on (MSTs) is difficult, particularly when the test spans several grade levels, and the selection of items from MST panels must reflect the operational test specifications. In this study, we describe, illustrate, and evaluate three methods for mapping panelists' Angoff ratings into cut scores on the scale underlying an MST. The…
Descriptors: Cutting Scores, Adaptive Testing, Test Items, Item Analysis
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Wang, Wenhao; Kingston, Neal M.; Davis, Marcia H.; Tiemann, Gail C.; Tonks, Stephen; Hock, Michael – Educational Measurement: Issues and Practice, 2021
Adaptive tests are more efficient than fixed-length tests through the use of item response theory; adaptive tests also present students questions that are tailored to their proficiency level. Although the adaptive algorithm is straightforward, developing a multidimensional computer adaptive test (MCAT) measure is complex. Evidence-centered design…
Descriptors: Evidence Based Practice, Reading Motivation, Adaptive Testing, Computer Assisted Testing
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Stephen G. Sireci; Javier Suárez-Álvarez; April L. Zenisky; Maria Elena Oliveri – Educational Measurement: Issues and Practice, 2024
The goal in personalized assessment is to best fit the needs of each individual test taker, given the assessment purposes. Design-in-Real-Time (DIRTy) assessment reflects the progressive evolution in testing from a single test, to an adaptive test, to an adaptive assessment "system." In this article, we lay the foundation for DIRTy…
Descriptors: Educational Assessment, Student Needs, Test Format, Test Construction
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Yamamoto, Kentaro; Shin, Hyo Jeong; Khorramdel, Lale – Educational Measurement: Issues and Practice, 2018
A multistage adaptive testing (MST) design was implemented for the Programme for the International Assessment of Adult Competencies (PIAAC) starting in 2012 for about 40 countries and has been implemented for the 2018 cycle of the Programme for International Student Assessment (PISA) for more than 80 countries. Using examples from PISA and PIAAC,…
Descriptors: International Assessment, Foreign Countries, Achievement Tests, Test Validity
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Qian, Hong; Staniewska, Dorota; Reckase, Mark; Woo, Ada – Educational Measurement: Issues and Practice, 2016
This article addresses the issue of how to detect item preknowledge using item response time data in two computer-based large-scale licensure examinations. Item preknowledge is indicated by an unexpected short response time and a correct response. Two samples were used for detecting item preknowledge for each examination. The first sample was from…
Descriptors: Reaction Time, Licensing Examinations (Professions), Computer Assisted Testing, Prior Learning