A Non-parametric CD-CAT Selection Strategy Based on Ideal Response

Journal of Psychological Science ›› 2022, Vol. 45 ›› Issue (2) : 470-480.

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PDF(1827 KB)
Journal of Psychological Science ›› 2022, Vol. 45 ›› Issue (2) : 470-480.

A Non-parametric CD-CAT Selection Strategy Based on Ideal Response

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Cognitive Diagnostic Adaptive Testing (CD-CAT) is featured with its Adaptive characteristics, and it is able to conduct Adaptive diagnosis and feedback on students' knowledge status.In today's personalized education, CD-CAT has a good development prospect and will play an important role in the future educational practice, so it has increasingly become a research hotspot at home and abroad.Topic selection strategy has always been one of the most concerned techniques in CD-CAT. Therefore, many researchers have put forward many topic selection strategies, such as KL, PWKL, SHE, MI and their variants.Most of these strategies are based on a certain amount of information and belong to the parameter category.Although the above parameter selection strategy has a good performance in the research, it also has the following shortcomings: First, in the process of building the question bank, a large number of questions in the test bank should be used in advance, and the test data should be used for parameter estimation, so as to ensure the accuracy of the parameter estimation.Such a large number of samples is not easy to realize in practice, especially in the course teaching.Second, the selection strategy of parameters is generally selected only for those topics with good quality, which will make the exposure rate of some topics too high and threaten the security of the question bank.Thirdly, the selected topic strategy models of parameters are complex, with large computational burden and difficult to understand. In recent years, researchers have developed a simple and effective non-parametric cognitive diagnosis method is suitable for small sample (HDD, EDD, MDD). Therefore, this study based on the thought of distance discriminant method, try to put aside the multifarious calculation formula and parameter estimation, based on the ideal answer, according to have title of each response is courtesy of model build different attributes control the distance weighting function, change numerous for brief, developed two kinds of suitable for hybrid scoring non-parametric CD - CAT DWIR and HDWIR topic selection strategy.The effects of DWIR and HDWIR were explored through two simulation studies. Study 1: Comparison was made between DWIR and HDWIR and selected topic strategies without exposure control (PS-KL and PS-PWKL).Study 2: Comparison between DWIR, HDWIR and selected topic strategy with exposure control.The results show that :(1)DWIR and HDWIR algorithms are simple and easy to understand, with few preconditions and easy to meet application conditions;(2)DWIR and HDWIR have wide applicability. They can be used not only for the topic selection of 01 scoring and multilevel scoring, but also for the parameter CD-CAT and non-parameter CD-CAT.(3) The attribute classification accuracy of DWIR and HDWIR is higher than that of the parameter selection strategy with exposure control, and the selection speed is faster.(4)DWIR and HDWIR have good exposure control effect, and the selection strategy is based on exposure control, so there is no need to add exposure control in the selection strategy to simplify the selection strategy.

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A Non-parametric CD-CAT Selection Strategy Based on Ideal Response[J]. Journal of Psychological Science. 2022, 45(2): 470-480
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