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• W830453801 abstract "Joint estimate the Q matrix, item parameters and attribute-mastery-pattern.Online estimate the Q matrix, item parameters and attribute-mastery-pattern.The modified online estimation algorithm can further improve the recover ratio.The algorithms can recover the true Q matrix based on a good or a bad input.Relative to the original method, the revised algorithms can be more likely to use. Q-matrix is the intermediary between attribute mastery patterns and responses in cognitive diagnostic assessment; therefore, Q-matrix plays a very important role in the assessment. Currently, lacking of reliable method of inferring and validating the expert-specified Q-matrix is the main problem. Based on the algorithm of Liu et al. (2012), three modified algorithms are proposed. There are two major differences between the algorithm of Liu et al. and the modified algorithms, one is to modify the item parameters from fixed to unfixed, the other is to use an incremental Q-matrix estimation, which some named as base items have been correctly prespecified, others (or called as new or raw whose attributes have not been specified) need to be specified. The modified algorithms incrementally add new to the base items one by one, estimate the item parameters and Q-matrix jointly, rather than estimate all of the simultaneously which would bring more noise to affect the accuracy of estimation. Simulation studies showed that the modified algorithms could get satisfactory results, and the empirical study showed that the proposed algorithms could offer useful information about the Q-matrix specification." @default.
• W830453801 created "2016-06-24" @default.
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• W830453801 date "2015-09-01" @default.
• W830453801 modified "2023-09-27" @default.
• W830453801 title "Model identification and Q-matrix incremental inference in cognitive diagnosis" @default.
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• W830453801 doi "https://doi.org/10.1016/j.knosys.2015.05.024" @default.
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