Mutual Information Item Selection in Adaptive Classification Testing
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چکیده
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منابع مشابه
Using Mutual Information for Adaptive Item Comparison and Student Assessment
The author analyzes properties of mutual information between dichotomous concepts and test items. The properties generalize some common intuitions about item comparison, and provide principled foundations for designing item-selection heuristics for student assessment in computer-assisted educational systems. The proposed item-selection strategies along with some common and conceivable methods, ...
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DOCUMENT RESUME TM 027 361 van der Linden, Wim J. Bayesian Item Selection Criteria for Adaptive Testing. Research Report 96-01. Twente Univ., Enschede (Netherlands). Faculty of Educational Science and Technology. 1996-10-00 32p. Faculty of Educational Science and Technology, University of Twente, P.O. Box 217, 7500 AE Enschede, The Netherlands. Reports Evaluative (142) MF01/PCO2 Plus Postage. A...
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One of the most important artificial immune algorithms is negative selection algorithm, which is an anomaly detection and pattern recognition technique; however, recent research has shown the successful application of this algorithm in data classification. Most of the negative selection methods consider deterministic boundaries to distinguish between self and non-self-spaces. In this paper, two...
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Adaptive item generation may be the next innovation in intelligence testing. In adaptive item generation, the optimally informative item is developed anew for the examinee during the test. Reminiscent of computer versus person chess games, the computer generates the next item based on the previous pattern of the examinee's responses. Adaptive item generation requires the merger of two lines of ...
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