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Yang Jiang; Mo Zhang; Jiangang Hao; Paul Deane; Chen Li – Journal of Educational Measurement, 2024
The emergence of sophisticated AI tools such as ChatGPT, coupled with the transition to remote delivery of educational assessments in the COVID-19 era, has led to increasing concerns about academic integrity and test security. Using AI tools, test takers can produce high-quality texts effortlessly and use them to game assessments. It is thus…
Descriptors: Integrity, Artificial Intelligence, Technology Uses in Education, Ethics
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Bergner, Yoav; Choi, Ikkyu; Castellano, Katherine E. – Journal of Educational Measurement, 2019
Allowance for multiple chances to answer constructed response questions is a prevalent feature in computer-based homework and exams. We consider the use of item response theory in the estimation of item characteristics and student ability when multiple attempts are allowed but no explicit penalty is deducted for extra tries. This is common…
Descriptors: Models, Item Response Theory, Homework, Computer Assisted Instruction
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Joo, Seang-Hwane; Lee, Philseok; Stark, Stephen – Journal of Educational Measurement, 2018
This research derived information functions and proposed new scalar information indices to examine the quality of multidimensional forced choice (MFC) items based on the RANK model. We also explored how GGUM-RANK information, latent trait recovery, and reliability varied across three MFC formats: pairs (two response alternatives), triplets (three…
Descriptors: Item Response Theory, Models, Item Analysis, Reliability
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Hsu, Chia-Ling; Wang, Wen-Chung – Journal of Educational Measurement, 2015
Cognitive diagnosis models provide profile information about a set of latent binary attributes, whereas item response models yield a summary report on a latent continuous trait. To utilize the advantages of both models, higher order cognitive diagnosis models were developed in which information about both latent binary attributes and latent…
Descriptors: Computer Assisted Testing, Adaptive Testing, Models, Cognitive Measurement
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Li, Feiming; Cohen, Allan; Shen, Linjun – Journal of Educational Measurement, 2012
Computer-based tests (CBTs) often use random ordering of items in order to minimize item exposure and reduce the potential for answer copying. Little research has been done, however, to examine item position effects for these tests. In this study, different versions of a Rasch model and different response time models were examined and applied to…
Descriptors: Computer Assisted Testing, Test Items, Item Response Theory, Models
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Finkelman, Matthew; Nering, Michael L.; Roussos, Louis A. – Journal of Educational Measurement, 2009
In computerized adaptive testing (CAT), ensuring the security of test items is a crucial practical consideration. A common approach to reducing item theft is to define maximum item exposure rates, i.e., to limit the proportion of examinees to whom a given item can be administered. Numerous methods for controlling exposure rates have been proposed…
Descriptors: Test Items, Adaptive Testing, Item Analysis, Item Response Theory
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Kalohn, John C.; Spray, Judith A. – Journal of Educational Measurement, 1999
Examined the effects of model misspecification on the precision of decisions made using the sequential probability ratio test (SPRT) in computer testing. Simulation results show that the one-parameter logistic model produced more errors than the true model. (SLD)
Descriptors: Classification, Computer Assisted Testing, Decision Making, Models
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Almond, Russell G.; DiBello, Louis V.; Moulder, Brad; Zapata-Rivera, Juan-Diego – Journal of Educational Measurement, 2007
This paper defines Bayesian network models and examines their applications to IRT-based cognitive diagnostic modeling. These models are especially suited to building inference engines designed to be synchronous with the finer grained student models that arise in skills diagnostic assessment. Aspects of the theory and use of Bayesian network models…
Descriptors: Inferences, Models, Item Response Theory, Cognitive Measurement
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Luecht, Richard M.; Nungester, Ronald J. – Journal of Educational Measurement, 1998
Describes an integrated approach to test development and administration called computer-adaptive sequential testing (CAST). CAST incorporates adaptive testing methods with automated test assembly. Describes the CAST framework and demonstrates several applications using a medical-licensure example. (SLD)
Descriptors: Adaptive Testing, Automation, Computer Assisted Testing, Licensing Examinations (Professions)
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Reise, Steve P.; Yu, Jiayuan – Journal of Educational Measurement, 1990
Parameter recovery in the graded-response model was investigated using the MULTILOG computer program under default conditions. Results from 36 simulated data sets suggest that at least 500 examinees are needed to achieve adequate calibration under the graded model. Sample size had little influence on the true ability parameter's recovery. (SLD)
Descriptors: Computer Assisted Testing, Computer Simulation, Computer Software, Estimation (Mathematics)
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Williamson, David M.; Bejar, Isaac I.; Hone, Anne S. – Journal of Educational Measurement, 1999
Contrasts "mental models" used by automated scoring for the simulation division of the computerized Architect Registration Examination with those used by experienced human graders for 3,613 candidate solutions. Discusses differences in the models used and the potential of automated scoring to enhance the validity evidence of scores. (SLD)
Descriptors: Architects, Comparative Analysis, Computer Assisted Testing, Judges
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Thissen, David; And Others – Journal of Educational Measurement, 1989
An approach to scoring reading comprehension based on the concept of the testlet is described, using models developed for items in multiple categories. The model is illustrated using data from 3,866 examinees. Application of testlet scoring to multiple category models developed for individual items is discussed. (SLD)
Descriptors: Adaptive Testing, Computer Assisted Testing, Item Response Theory, Mathematical Models
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Adema, Jos J. – Journal of Educational Measurement, 1990
Mixed integer linear programing models for customizing two-stage tests are presented. Model constraints are imposed with respect to test composition, administration time, inter-item dependencies, and other practical considerations. The models can be modified for use in the construction of multistage tests. (Author/TJH)
Descriptors: Adaptive Testing, Computer Assisted Testing, Equations (Mathematics), Linear Programing
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Wang, Tianyou; Kolen, Michael J. – Journal of Educational Measurement, 2001
Reviews research literature on comparability issues in computerized adaptive testing (CAT) and synthesizes issues specific to comparability and test security. Develops a framework for evaluating comparability that contains three categories of criteria: (1) validity; (2) psychometric property/reliability; and (3) statistical assumption/test…
Descriptors: Adaptive Testing, Comparative Analysis, Computer Assisted Testing, Criteria
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Gitomer, Drew H.; Yamamoto, Kentaro – Journal of Educational Measurement, 1991
A model integrating latent trait and latent class theories in characterizing individual performance on the basis of qualitative understanding is presented. This HYBRID model is illustrated through experiments with 119 Air Force technicians taking a paper-and-pencil test and 136 Air Force technicians taking a computerized test. (SLD)
Descriptors: Comparative Testing, Computer Assisted Testing, Educational Assessment, Item Response Theory
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