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Pan, Yiqin; Livne, Oren; Wollack, James A.; Sinharay, Sandip – Educational Measurement: Issues and Practice, 2023
In computerized adaptive testing, overexposure of items in the bank is a serious problem and might result in item compromise. We develop an item selection algorithm that utilizes the entire bank well and reduces the overexposure of items. The algorithm is based on collaborative filtering and selects an item in two stages. In the first stage, a set…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Algorithms
Development of a High-Accuracy and Effective Online Calibration Method in CD-CAT Based on Gini Index
Tan, Qingrong; Cai, Yan; Luo, Fen; Tu, Dongbo – Journal of Educational and Behavioral Statistics, 2023
To improve the calibration accuracy and calibration efficiency of cognitive diagnostic computerized adaptive testing (CD-CAT) for new items and, ultimately, contribute to the widespread application of CD-CAT in practice, the current article proposed a Gini-based online calibration method that can simultaneously calibrate the Q-matrix and item…
Descriptors: Cognitive Tests, Computer Assisted Testing, Adaptive Testing, Accuracy
Shengyu Jiang; Jiaying Xiao; Chun Wang – Grantee Submission, 2022
An online learning system has the capacity to offer customized content that caters to individual learner's need and has seen growing interest from industry and academia alike in recent years. Different from traditional computerized adaptive testing setting which has a well-calibrated item bank with new items periodically added, online learning…
Descriptors: Item Response Theory, Item Banks, Bayesian Statistics, Learning Management Systems
Hanif Akhtar – International Society for Technology, Education, and Science, 2023
For efficiency, Computerized Adaptive Test (CAT) algorithm selects items with the maximum information, typically with a 50% probability of being answered correctly. However, examinees may not be satisfied if they only correctly answer 50% of the items. Researchers discovered that changing the item selection algorithms to choose easier items (i.e.,…
Descriptors: Success, Probability, Computer Assisted Testing, Adaptive Testing
Shengyu Jiang – ProQuest LLC, 2020
An online learning system has the capacity to offer customized content that caters to individual learner's need and has seen growing interest from industry and academia alike in recent years. Noting the similarity between online learning and the more established adaptive testing procedures, research has focused on applying the techniques of…
Descriptors: Item Response Theory, Item Banks, Bayesian Statistics, Learning Management Systems
Veldkamp, Bernard P. – 2002
This paper discusses optimal test construction, which deals with the selection of items from a pool to construct a test that performs optimally with respect to the objective of the test and simultaneously meets all test specifications. Optimal test construction problems can be formulated as mathematical decision models. Algorithms and heuristics…
Descriptors: Algorithms, Item Banks, Selection, Test Construction

Adema, Jos J.; van der Linden, Wim J. – Journal of Educational Statistics, 1989
Two zero-one linear programing models for constructing tests using classical item and test parameters are given. These models are useful, for instance, when classical test theory must serve as an interface between an item response theory-based item banking system and a test constructor unfamiliar with the underlying theory. (TJH)
Descriptors: Algorithms, Computer Assisted Testing, Item Banks, Linear Programing

Stocking, 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

van der Linden, Wim J. – Applied Psychological Measurement, 2001
Presents a constrained computerized adaptive testing (CAT) algorithm that can be used to equate CAT number-correct scores to a reference test. Used an item bank from the Law School Admission Test to compare results of the algorithm with those for equipercentile observed-score equating. Discusses advantages of the approach. (SLD)
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Equated Scores
Performance of Item Exposure Control Methods in Computerized Adaptive Testing: Further Explorations.
Chang, Shun-Wen; Ansley, Timothy N.; Lin, Sieh-Hwa – 2000
This study examined the effectiveness of the Sympson and Hetter conditional procedure (SHC), a modification of the Sympson and Hetter (1985) algorithm, in controlling the exposure rates of items in a computerized adaptive testing (CAT) environment. The properties of the procedure were compared with those of the Davey and Parshall (1995) and the…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Banks
Lau, 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
Stocking, Martha L.; And Others – 1991
A previously developed method of automatically selecting items for inclusion in a test subject to constraints on item content and statistical properties is applied to real data. Two tests are first assembled by experts in test construction who normally assemble such tests on a routine basis. Using the same pool of items and constraints articulated…
Descriptors: Algorithms, Automation, Coding, Computer Assisted Testing

van der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L. – Applied Psychological Measurement, 1999
Proposes an item-selection algorithm for neutralizing the differential effects of time limits on computerized adaptive test scores. Uses a statistical model for distributions of examinees' response times on items in a bank that is updated each time an item is administered. Demonstrates the method using an item bank from the Armed Services…
Descriptors: Adaptive Testing, Algorithms, Computer Assisted Testing, Item Banks
Stocking, Martha L.; And Others – 1991
This paper presents a new heuristic approach to interactive test assembly that is called the successive item replacement algorithm. This approach builds on the work of W. J. van der Linden (1987) and W. J. van der Linden and E. Boekkooi-Timminga (1989) in which methods of mathematical optimization are combined with item response theory to…
Descriptors: Algorithms, Automation, Computer Selection, Heuristics
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