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Peer reviewedStocking, Martha L.; Lewis, Charles – Journal of Educational and Behavioral Statistics, 1998
Ensuring item and pool security in a continuous testing environment is explored through a new method of controlling exposure rate of items conditional on ability level in computerized testing. Properties of this conditional control on exposure rate, when used in conjunction with a particular adaptive testing algorithm, are explored using simulated…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Difficulty Level
Download full textLau, C. Allen; Wang, Tianyou – 1999
A study was conducted to extend the sequential probability ratio testing (SPRT) procedure with the polytomous model under some practical constraints in computerized classification testing (CCT), such as methods to control item exposure rate, and to study the effects of other variables, including item information algorithms, test difficulties, item…
Descriptors: Algorithms, Computer Assisted Testing, Difficulty Level, Item Banks
Linacre, John Michael – 1988
Computer-adaptive testing (CAT) allows improved security, greater scoring accuracy, shorter testing periods, quicker availability of results, and reduced guessing and other undesirable test behavior. Simple approaches can be applied by the classroom teacher, or other content specialist, who possesses simple computer equipment and elementary…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Cutting Scores
Gershon, Richard; Bergstrom, Betty – 1995
When examinees are allowed to review responses on an adaptive test, can they "cheat" the adaptive algorithm in order to take an easier test and improve their performance? Theoretically, deliberately answering items incorrectly will lower the examinee ability estimate and easy test items will be administered. If review is then allowed,…
Descriptors: Adaptive Testing, Algorithms, Cheating, Computer Assisted Testing
Peer reviewedArmstrong, Ronald D.; And Others – Journal of Educational Statistics, 1994
A network-flow model is formulated for constructing parallel tests based on classical test theory while using test reliability as the criterion. Practitioners can specify a test-difficulty distribution for values of item difficulties as well as test-composition requirements. An empirical study illustrates the reliability of generated tests. (SLD)
Descriptors: Algorithms, Computer Assisted Testing, Difficulty Level, Item Banks
Veerkamp, Wim J. J.; Berger, Martijn P. F. – 1994
Items with the highest discrimination parameter values in a logistic item response theory (IRT) model do not necessarily give maximum information. This paper shows which discrimination parameter values (as a function of the guessing parameter and the distance between person ability and item difficulty) give maximum information for the…
Descriptors: Ability, Adaptive Testing, Algorithms, Computer Assisted Testing
Wainer, Howard; Kiely, Gerard L. – 1986
Recent experience with the Computerized Adaptive Test (CAT) has raised a number of concerns about its practical applications. The concerns are principally involved with the concept of having the computer construct the test from a precalibrated item pool, and substituting statistical characteristics for the test developer's skills. Problems with…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Construct Validity
