01923nas a2200241   4500008004100000245009400041210006900135300001200204490000700216520110100223653002101324653001301345653003001358653005701388653000901445653003201454653002601486653002001512100001401532700001301546700001501559856010701574       2003                        eng d00aA Bayesian method for the detection of item preknowledge in computerized adaptive testing0 aBayesian method for the detection of item preknowledge in comput  a121-1370 v273 aWith the increased use of continuous testing in computerized adaptive testing, new concerns about test security have evolved, such as how to ensure that items in an item pool are safeguarded from theft. In this article, procedures to detect test takers using item preknowledge are explored. When test takers use item preknowledge, their item responses deviate from the underlying item response theory (IRT) model, and estimated abilities may be inflated. This deviation may be detected through the use of person-fit indices. A Bayesian posterior log odds ratio index is proposed for detecting the use of item preknowledge. In this approach to person fit, the estimated probability that each test taker has preknowledge of items is updated after each item response. These probabilities are based on the IRT parameters, a model specifying the probability that each item has been memorized, and the test taker's item responses. Simulations based on an operational computerized adaptive test (CAT) pool are used to demonstrate the use of the odds ratio index. (PsycINFO Database Record (c) 2005 APA )10aAdaptive Testing10aCheating10aComputer Assisted Testing10aIndividual Differences computerized adaptive testing10aItem10aItem Analysis (Statistical)10aMathematical Modeling10aResponse Theory1 aMcLeod, L1 aLewis, C1 aThissen, D  uhttp://www.iacat.org/content/bayesian-method-detection-item-preknowledge-computerized-adaptive-testing