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    政大機構典藏 > 資訊學院 > 資訊科學系 > 期刊論文 >  Item 140.119/75892
    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/75892


    Title: Using Mutual Information for Adaptive Item Comparison and Student Assessment
    Authors: Liu, Chao-lin
    劉昭麟
    Contributors: 資科系
    Keywords: Educational assessments;Item selection;Intelligent tutoring;Mutual information;Bayesian networks;Mahalanobis distance;Classification;Adaptive interfaces;Uncertain reasoning
    Date: 2005
    Issue Date: 2015-06-17 15:44:17 (UTC+8)
    Abstract: 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, including mutual information-based methods and Euclidean and Mahalanobis distance-based methods, for student classification are evaluated in a simulation-based environment. The simulator relies on Bayesian networks for capturing the uncertainty in students’ responses to test items. Simulated results indicate that the heuristics built upon the theoretical properties offer satisfactory performance profiles for item selection, and, not surprisingly, mutual information-based methods offer better performance for the task of student classification than distance-based methods.
    Relation: Educational Technology & Society - ETS , vol. 8, no. 4, pp. 100-119
    Data Type: article
    Appears in Collections:[資訊科學系] 期刊論文

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