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Showing 1 to 15 of 27 results Save | Export
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Wang, Xi; Liu, Yang; Robin, Frederic; Guo, Hongwen – International Journal of Testing, 2019
In an on-demand testing program, some items are repeatedly used across test administrations. This poses a risk to test security. In this study, we considered a scenario wherein a test was divided into two subsets: one consisting of secure items and the other consisting of possibly compromised items. In a simulation study of multistage adaptive…
Descriptors: Identification, Methods, Test Items, Cheating
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Cappaert, Kevin J.; Wen, Yao; Chang, Yu-Feng – Measurement: Interdisciplinary Research and Perspectives, 2018
Events such as curriculum changes or practice effects can lead to item parameter drift (IPD) in computer adaptive testing (CAT). The current investigation introduced a point- and weight-adjusted D[superscript 2] method for IPD detection for use in a CAT environment when items are suspected of drifting across test administrations. Type I error and…
Descriptors: Adaptive Testing, Computer Assisted Testing, Test Items, Identification
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Cheng, Ying; Patton, Jeffrey M.; Shao, Can – Educational and Psychological Measurement, 2015
a-Stratified computerized adaptive testing with b-blocking (AST), as an alternative to the widely used maximum Fisher information (MFI) item selection method, can effectively balance item pool usage while providing accurate latent trait estimates in computerized adaptive testing (CAT). However, previous comparisons of these methods have treated…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Item Banks
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Leroux, Audrey J.; Lopez, Myriam; Hembry, Ian; Dodd, Barbara G. – Educational and Psychological Measurement, 2013
This study compares the progressive-restricted standard error (PR-SE) exposure control procedure to three commonly used procedures in computerized adaptive testing, the randomesque, Sympson-Hetter (SH), and no exposure control methods. The performance of these four procedures is evaluated using the three-parameter logistic model under the…
Descriptors: Computer Assisted Testing, Adaptive Testing, Comparative Analysis, Statistical Analysis
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He, Lianzhen; Min, Shangchao – Language Assessment Quarterly, 2017
The first aim of this study was to develop a computer adaptive EFL test (CALT) that assesses test takers' listening and reading proficiency in English with dichotomous items and polytomous testlets. We reported in detail on the development of the CALT, including item banking, determination of suitable item response theory (IRT) models for item…
Descriptors: Computer Assisted Testing, Adaptive Testing, English (Second Language), Second Language Learning
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Veldkamp, Bernard P.; Matteucci, Mariagiulia; de Jong, Martijn G. – Applied Psychological Measurement, 2013
Item response theory parameters have to be estimated, and because of the estimation process, they do have uncertainty in them. In most large-scale testing programs, the parameters are stored in item banks, and automated test assembly algorithms are applied to assemble operational test forms. These algorithms treat item parameters as fixed values,…
Descriptors: Test Construction, Test Items, Item Banks, Automation
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Ali, Usama S.; Chang, Hua-Hua – ETS Research Report Series, 2014
Adaptive testing is advantageous in that it provides more efficient ability estimates with fewer items than linear testing does. Item-driven adaptive pretesting may also offer similar advantages, and verification of such a hypothesis about item calibration was the main objective of this study. A suitability index (SI) was introduced to adaptively…
Descriptors: Adaptive Testing, Simulation, Pretests Posttests, Test Items
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Han, Kyung T. – Journal of Educational Measurement, 2012
Successful administration of computerized adaptive testing (CAT) programs in educational settings requires that test security and item exposure control issues be taken seriously. Developing an item selection algorithm that strikes the right balance between test precision and level of item pool utilization is the key to successful implementation…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
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Wang, Chun; Chang, Hua-Hua; Huebner, Alan – Journal of Educational Measurement, 2011
This paper proposes two new item selection methods for cognitive diagnostic computerized adaptive testing: the restrictive progressive method and the restrictive threshold method. They are built upon the posterior weighted Kullback-Leibler (KL) information index but include additional stochastic components either in the item selection index or in…
Descriptors: Test Items, Adaptive Testing, Computer Assisted Testing, Cognitive Tests
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Wang, Wen-Chung; Liu, Chen-Wei – Educational and Psychological Measurement, 2011
The generalized graded unfolding model (GGUM) has been recently developed to describe item responses to Likert items (agree-disagree) in attitude measurement. In this study, the authors (a) developed two item selection methods in computerized classification testing under the GGUM, the current estimate/ability confidence interval method and the cut…
Descriptors: Computer Assisted Testing, Adaptive Testing, Classification, Item Response Theory
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Davey, Tim; Lee, Yi-Hsuan – ETS Research Report Series, 2011
Both theoretical and practical considerations have led the revision of the Graduate Record Examinations® (GRE®) revised General Test, here called the rGRE, to adopt a multistage adaptive design that will be continuously or nearly continuously administered and that can provide immediate score reporting. These circumstances sharply constrain the…
Descriptors: Context Effect, Scoring, Equated Scores, College Entrance Examinations
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Choi, Seung W.; Swartz, Richard J. – Applied Psychological Measurement, 2009
Item selection is a core component in computerized adaptive testing (CAT). Several studies have evaluated new and classical selection methods; however, the few that have applied such methods to the use of polytomous items have reported conflicting results. To clarify these discrepancies and further investigate selection method properties, six…
Descriptors: Adaptive Testing, Item Analysis, Comparative Analysis, Test Items
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Yang, Chih-Wei; Kuo, Bor-Chen; Liao, Chen-Huei – Turkish Online Journal of Educational Technology - TOJET, 2011
The aim of the present study was to develop an on-line assessment system with constructed response items in the context of elementary mathematics curriculum. The system recorded the problem solving process of constructed response items and transfered the process to response codes for further analyses. An inference mechanism based on artificial…
Descriptors: Foreign Countries, Mathematics Curriculum, Test Items, Problem Solving
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Bulut, Okan; Kan, Adnan – Eurasian Journal of Educational Research, 2012
Problem Statement: Computerized adaptive testing (CAT) is a sophisticated and efficient way of delivering examinations. In CAT, items for each examinee are selected from an item bank based on the examinee's responses to the items. In this way, the difficulty level of the test is adjusted based on the examinee's ability level. Instead of…
Descriptors: Adaptive Testing, Computer Assisted Testing, College Entrance Examinations, Graduate Students
Zhu, Renbang; Yu, Feng; Liu, Su – 2002
A computerized adaptive test (CAT) administration usually requires a large supply of items with accurately estimated psychometric properties, such as item response theory (IRT) parameter estimates, to ensure the precision of examinee ability estimation. However, an estimated IRT model of a given item in any given pool does not always correctly…
Descriptors: Ability, Adaptive Testing, Computer Assisted Testing, Estimation (Mathematics)
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