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Grochowalski, Joseph H.; Hendrickson, Amy – Journal of Educational Measurement, 2023
Test takers wishing to gain an unfair advantage often share answers with other test takers, either sharing all answers (a full key) or some (a partial key). Detecting key sharing during a tight testing window requires an efficient, easily interpretable, and rich form of analysis that is descriptive and inferential. We introduce a detection method…
Descriptors: Identification, Cooperative Learning, Cheating, Statistical Analysis
Han, Suhwa; Kang, Hyeon-Ah – Journal of Educational Measurement, 2023
The study presents multivariate sequential monitoring procedures for examining test-taking behaviors online. The procedures monitor examinee's responses and response times and signal aberrancy as soon as significant change is identifieddetected in the test-taking behavior. The study in particular proposes three schemes to track different…
Descriptors: Test Wiseness, Student Behavior, Item Response Theory, Computer Assisted Testing
Lim, Hwanggyu; Choe, Edison M. – Journal of Educational Measurement, 2023
The residual differential item functioning (RDIF) detection framework was developed recently under a linear testing context. To explore the potential application of this framework to computerized adaptive testing (CAT), the present study investigated the utility of the RDIF[subscript R] statistic both as an index for detecting uniform DIF of…
Descriptors: Test Items, Computer Assisted Testing, Item Response Theory, Adaptive Testing
Dorsey, David W.; Michaels, Hillary R. – Journal of Educational Measurement, 2022
We have dramatically advanced our ability to create rich, complex, and effective assessments across a range of uses through technology advancement. Artificial Intelligence (AI) enabled assessments represent one such area of advancement--one that has captured our collective interest and imagination. Scientists and practitioners within the domains…
Descriptors: Validity, Ethics, Artificial Intelligence, Evaluation Methods
Cui, Zhongmin; Liu, Chunyan; He, Yong; Chen, Hanwei – Journal of Educational Measurement, 2018
Allowing item review in computerized adaptive testing (CAT) is getting more attention in the educational measurement field as more and more testing programs adopt CAT. The research literature has shown that allowing item review in an educational test could result in more accurate estimates of examinees' abilities. The practice of item review in…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Test Wiseness
Wang, Shiyu; Lin, Haiyan; Chang, Hua-Hua; Douglas, Jeff – Journal of Educational Measurement, 2016
Computerized adaptive testing (CAT) and multistage testing (MST) have become two of the most popular modes in large-scale computer-based sequential testing. Though most designs of CAT and MST exhibit strength and weakness in recent large-scale implementations, there is no simple answer to the question of which design is better because different…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Format, Sequential Approach
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
Deng, Hui; Ansley, Timothy; Chang, Hua-Hua – Journal of Educational Measurement, 2010
In this study we evaluated and compared three item selection procedures: the maximum Fisher information procedure (F), the a-stratified multistage computer adaptive testing (CAT) (STR), and a refined stratification procedure that allows more items to be selected from the high a strata and fewer items from the low a strata (USTR), along with…
Descriptors: Computer Assisted Testing, Adaptive Testing, Selection, Methods
Pommerich, Mary; Segall, Daniel O. – Journal of Educational Measurement, 2008
The accuracy of CAT scores can be negatively affected by local dependence if the CAT utilizes parameters that are misspecified due to the presence of local dependence and/or fails to control for local dependence in responses during the administration stage. This article evaluates the existence and effect of local dependence in a test of…
Descriptors: Simulation, Computer Assisted Testing, Mathematics Tests, Scores
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

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
van der Linden, Wim J.; Breithaupt, Krista; Chuah, Siang Chee; Zhang, Yanwei – Journal of Educational Measurement, 2007
A potential undesirable effect of multistage testing is differential speededness, which happens if some of the test takers run out of time because they receive subtests with items that are more time intensive than others. This article shows how a probabilistic response-time model can be used for estimating differences in time intensities and speed…
Descriptors: Adaptive Testing, Evaluation Methods, Test Items, Reaction Time

Millman, Jason; Westman, Ronald S. – Journal of Educational Measurement, 1989
Five approaches to writing test items with computer assistance are described. A model of knowledge using a set of structures and a system for implementing the scheme are outlined. The approaches include the author-supplied approach, replacement-set procedures, computer-supplied prototype items, subject-matter mapping, and discourse analysis. (TJH)
Descriptors: Achievement Tests, Algorithms, Computer Assisted Testing, Test Construction
Huitzing, Hiddo A.; Veldkamp, Bernard P.; Verschoor, Angela J. – Journal of Educational Measurement, 2005
Several techniques exist to automatically put together a test meeting a number of specifications. In an item bank, the items are stored with their characteristics. A test is constructed by selecting a set of items that fulfills the specifications set by the test assembler. Test assembly problems are often formulated in terms of a model consisting…
Descriptors: Testing Programs, Programming, Mathematics, Item Sampling

Wainer, Howard – Journal of Educational Measurement, 1989
This paper reviews the role of the item in test construction, and suggests some new methods of item analysis. A look at dynamic, graphical item analysis is provided that uses the advantages of modern, high-speed, highly interactive computing. Several illustrations are provided. (Author/TJH)
Descriptors: Computer Assisted Testing, Computer Graphics, Graphs, Item Analysis