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Showing 1 to 15 of 23 results Save | Export
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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
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Kárász, Judit T.; Széll, Krisztián; Takács, Szabolcs – Quality Assurance in Education: An International Perspective, 2023
Purpose: Based on the general formula, which depends on the length and difficulty of the test, the number of respondents and the number of ability levels, this study aims to provide a closed formula for the adaptive tests with medium difficulty (probability of solution is p = 1/2) to determine the accuracy of the parameters for each item and in…
Descriptors: Test Length, Probability, Comparative Analysis, Difficulty Level
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Doble, Christopher; Matayoshi, Jeffrey; Cosyn, Eric; Uzun, Hasan; Karami, Arash – International Journal of Artificial Intelligence in Education, 2019
A large-scale simulation study of the assessment effectiveness of a particular instantiation of knowledge space theory is described. In this study, data from more than 700,000 actual assessments in mathematics using the ALEKS (Assessment and LEarning in Knowledge Spaces) software were used to determine response probabilities for the same number of…
Descriptors: Test Reliability, Adaptive Testing, Mathematics Tests, Computer Assisted Testing
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Kang, Hyeon-Ah; Zhang, Susu; Chang, Hua-Hua – Journal of Educational Measurement, 2017
The development of cognitive diagnostic-computerized adaptive testing (CD-CAT) has provided a new perspective for gaining information about examinees' mastery on a set of cognitive attributes. This study proposes a new item selection method within the framework of dual-objective CD-CAT that simultaneously addresses examinees' attribute mastery…
Descriptors: Computer Assisted Testing, Adaptive Testing, Cognitive Tests, Test Items
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Wang, Chao; Lu, Hong – Educational Technology & Society, 2018
This study focused on the effect of examinees' ability levels on the relationship between Reflective-Impulsive (RI) cognitive style and item response time in computerized adaptive testing (CAT). The total of 56 students majoring in Educational Technology from Shandong Normal University participated in this study, and their RI cognitive styles were…
Descriptors: Item Response Theory, Computer Assisted Testing, Cognitive Style, Correlation
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Nydick, Steven W. – Journal of Educational and Behavioral Statistics, 2014
The sequential probability ratio test (SPRT) is a common method for terminating item response theory (IRT)-based adaptive classification tests. To decide whether a classification test should stop, the SPRT compares a simple log-likelihood ratio, based on the classification bound separating two categories, to prespecified critical values. As has…
Descriptors: Probability, Item Response Theory, Models, Classification
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Belov, Dmitry I. – Journal of Educational Measurement, 2013
The development of statistical methods for detecting test collusion is a new research direction in the area of test security. Test collusion may be described as large-scale sharing of test materials, including answers to test items. Current methods of detecting test collusion are based on statistics also used in answer-copying detection.…
Descriptors: Cheating, Computer Assisted Testing, Adaptive Testing, Statistical Analysis
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Özyurt, Hacer; Özyurt, Özcan – Eurasian Journal of Educational Research, 2015
Problem Statement: Learning-teaching activities bring along the need to determine whether they achieve their goals. Thus, multiple choice tests addressing the same set of questions to all are frequently used. However, this traditional assessment and evaluation form contrasts with modern education, where individual learning characteristics are…
Descriptors: Probability, Adaptive Testing, Computer Assisted Testing, Item Response Theory
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Klinkenberg, S.; Straatemeier, M.; van der Maas, H. L. J. – Computers & Education, 2011
In this paper we present a model for computerized adaptive practice and monitoring. This model is used in the Maths Garden, a web-based monitoring system, which includes a challenging web environment for children to practice arithmetic. Using a new item response model based on the Elo (1978) rating system and an explicit scoring rule, estimates of…
Descriptors: Test Items, Reaction Time, Scoring, Probability
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Rock, Donald A. – ETS Research Report Series, 2012
This paper provides a history of ETS's role in developing assessment instruments and psychometric procedures for measuring change in large-scale national assessments funded by the Longitudinal Studies branch of the National Center for Education Statistics. It documents the innovations developed during more than 30 years of working with…
Descriptors: Models, Educational Change, Longitudinal Studies, Educational Development
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Finkelman, Matthew – Journal of Educational and Behavioral Statistics, 2008
Sequential mastery testing (SMT) has been researched as an efficient alternative to paper-and-pencil testing for pass/fail examinations. One popular method for determining when to cease examination in SMT is the truncated sequential probability ratio test (TSPRT). This article introduces the application of stochastic curtailment in SMT to shorten…
Descriptors: Mastery Tests, Sequential Approach, Computer Assisted Testing, Adaptive Testing
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van der Linden, Wim J.; Veldkamp, Bernard P. – Journal of Educational and Behavioral Statistics, 2007
Two conditional versions of the exposure-control method with item-ineligibility constraints for adaptive testing in van der Linden and Veldkamp (2004) are presented. The first version is for unconstrained item selection, the second for item selection with content constraints imposed by the shadow-test approach. In both versions, the exposure rates…
Descriptors: Law Schools, Adaptive Testing, Item Analysis, Probability
van der Linden, Wim J. – 2002
The Sympson and Hetter (SH; J. Sympson and R. Hetter; 1985; 1997) method is a method of probabilistic item exposure control in computerized adaptive testing. Setting its control parameters to admissible values requires an iterative process of computer simulations that has been found to be time consuming, particularly if the parameters have to be…
Descriptors: Adaptive Testing, College Entrance Examinations, Computer Assisted Testing, Law Schools
van der Linden, Wim J.; Veldkamp, Bernard P. – 2002
Item-exposure control in computerized adaptive testing is implemented by imposing item-ineligibility constraints on the assembly process of the shadow tests. The method resembles J. Sympson and R. Hetter's (1985) method of item-exposure control in that the decisions to impose the constraints are probabilistic. However, the method does not require…
Descriptors: Adaptive Testing, College Entrance Examinations, Computer Assisted Testing, Law Schools
Frick, Theodore W.; And Others – 1989
Expert systems can be used to aid decision making. A computerized adaptive test (CAT) is one kind of expert system, although it is not commonly recognized as such. A new approach, termed EXSPRT, was devised that combines expert systems reasoning and sequential probability ratio test stopping rules. EXSPRT-R uses random selection of test items,…
Descriptors: Adaptive Testing, College Students, Computer Assisted Testing, Expert Systems
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