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Bao, Yu; Bradshaw, Laine – Measurement: Interdisciplinary Research and Perspectives, 2018
Diagnostic classification models (DCMs) can provide multidimensional diagnostic feedback about students' mastery levels of knowledge components or attributes. One advantage of using DCMs is the ability to accurately and reliably classify students into mastery levels with a relatively small number of items per attribute. Combining DCMs with…
Descriptors: Test Items, Selection, Adaptive Testing, Computer Assisted Testing
Dünya, Beyza Aksu – ProQuest LLC, 2017
This study was conducted to analyze potential item parameter drift (IPD) impact on person ability estimates and classification accuracy when drift affects an examinee sub-group. Using a series of simulations, three factors were manipulated: (a) percentage of IPD items in the CAT exam, (b) percentage of examinees affected by IPD, and (c) item pool…
Descriptors: Item Banks, Adaptive Testing, Computer Assisted Testing, Correlation
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Kim, Jiseon; Chung, Hyewon; Dodd, Barbara G.; Park, Ryoungsun – Educational and Psychological Measurement, 2012
This study compared various panel designs of the multistage test (MST) using mixed-format tests in the context of classification testing. Simulations varied the design of the first-stage module. The first stage was constructed according to three levels of test information functions (TIFs) with three different TIF centers. Additional computerized…
Descriptors: Test Format, Comparative Analysis, Computer Assisted Testing, Adaptive Testing
Zheng, Yi; Nozawa, Yuki; Gao, Xiaohong; Chang, Hua-Hua – ACT, Inc., 2012
Multistage adaptive tests (MSTs) have gained increasing popularity in recent years. MST is a balanced compromise between linear test forms (i.e., paper-and-pencil testing and computer-based testing) and traditional item-level computer-adaptive testing (CAT). It combines the advantages of both. On one hand, MST is adaptive (and therefore more…
Descriptors: Adaptive Testing, Heuristics, Accuracy, Item Banks
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Nuntiyagul, Atorn; Naruedomkul, Kanlaya; Cercone, Nick; Wongsawang, Damras – Computers & Education, 2008
We present PKIP, an adaptable learning assistant tool for managing question items in item banks. PKIP is not only able to automatically assist educational users to categorize the question items into predefined categories by their contents but also to correctly retrieve the items by specifying the category and/or the difficulty level. PKIP adapts…
Descriptors: Classification, Item Banks, Adaptive Testing
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Eggen, T. J. H. M.; Straetmans, G. J. J. M. – Educational and Psychological Measurement, 2000
Studied the use of adaptive testing when examinees are classified into three categories. Established testing algorithms with two different statistical computation procedures and evaluated them through simulation using an operative item bank from Dutch basic adult education. Results suggest a reduction of at least 22% in the mean number of items…
Descriptors: Adaptive Testing, Adult Education, Algorithms, Classification
Finney, Sara J.; Smith, Russell W.; Wise, Steven L. – 1999
Two operational item pools were used to investigate the performance of stratum computerized adaptive tests (CATs) when items were assigned to strata based on empirical estimates of item difficulty or human judgments of item difficulty. Items from the first data set consisted of 54 5-option multiple choice items from a form of the ACT mathematics…
Descriptors: Adaptive Testing, Classification, Computer Assisted Testing, High School Students
Veldkamp, Bernard P.; van der Linden, Wim J. – 1999
A method of item pool design is proposed that uses an optimal blueprint for the item pool calculated from the test specifications. The blueprint is a document that specifies the attributes that the items in the computerized adaptive test (CAT) pool should have. The blueprint can be a starting point for the item writing process, and it can be used…
Descriptors: Ability, Adaptive Testing, Classification, Computer Assisted Testing
Frick, Theodore W. – 1986
The sequential probability ratio test (SPRT), developed by Abraham Wald, is one statistical model available for making mastery decisions during computer-based criterion referenced tests. The predictive validity of the SPRT was empirically investigated with two different and relatively large item pools with heterogeneous item parameters. Graduate…
Descriptors: Achievement Tests, Adaptive Testing, Classification, Comparative Analysis