[1]席崇钦,涂冬波,蔡 艳*.兼顾能力与知识状态的Higher-Order CD-CAT选题方法[J].江西师范大学学报(自然科学版),2022,(02):111-117.[doi:10.16357/j.cnki.issn1000-5862.2022.02.01]
　XI Chongqin,TU Dongbo,CAI Yan*.The Item Selection Method Considering the Ability and Cognitive Profile in Higher-Order CD-CAT[J].Journal of Jiangxi Normal University:Natural Science Edition,2022,(02):111-117.[doi:10.16357/j.cnki.issn1000-5862.2022.02.01]
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兼顾能力与知识状态的Higher-Order CD-CAT选题方法()
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《江西师范大学学报》（自然科学版）[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2022年02期
页码:
111-117
栏目:
心理与教育测量
出版日期:
2022-03-25

文章信息/Info

Title:
The Item Selection Method Considering the Ability and Cognitive Profile in Higher-Order CD-CAT
文章编号:
1000-5862(2022)02-0111-07
作者:
席崇钦; 涂冬波; 蔡 艳*
江西师范大学心理学院,江西 南昌 330022
Author(s):
XI Chongqin; TU Dongbo; CAI Yan*
College of Psychology,Jiangxi Normal University,Nanchang Jiangxi 330022,China
关键词:
双目标CD-CAT;  高阶模型;  higher-order CD-CAT;  选题方法
Keywords:
dual-objective CD-CAT;  higher-order model;  higher-order CD-CAT;  item selection method
分类号:
B 814.7
DOI:
10.16357/j.cnki.issn1000-5862.2022.02.01
文献标志码:
A
摘要:
Higher-order CD-CAT的选题方法是传统单目标(即只对知识状态自适应)选题方法,这将导致被试能力的测量精度不高.基于此,在高阶模型和PWKL选题方法的框架下,该文开发了适用于Higher-order CD-CAT的新选题方法,该方法在选题时能同时兼顾能力和知识状态.实验结果表明:与传统选题方法相比,新选题方法的能力和知识状态估计精度都更高,并且在题库安全性上也具有明显的优势.
Abstract:
Current item selection methods used in the CAT system select items adaptively according to only the attribute profile,which may lead to low precision with respect to ability.In light of this,under the item selection method of the higher-order CD-CAT and PWKL,the new item selection method that simultaneously considers the ability and attribute profile information is proposed for the higher-order CD-CAT in the paper.The results from the simulation study indicate that the new method proposed in this study always outperforms the existing methods in terms of measurement accuracy of the ability and cognitive profile,and the proposed method has also a significant advantage over the traditional methods in item pool security.

参考文献/References:

[1] HSU C L,WANG Wenchung.Variable-length computerized adaptive testing using the higher order DINA model[J].Journal of Educational Measurement,2015,52(2):125-143.
[2] WANG Chun,ZHENG Chanjin,CHANG Huahua.An enhanced approach to combine item response theory with cognitive diagnosis in adaptive testing[J].Journal of Educational Measurement,2014,51(4):358-380.
[3] GREENO J G.Trends in the theory of knowledge for problem solving[EB/OL].[2021-12-18].https://www.researchgate.net/publication/244520649_Trends_In_the_theory_of_knowledge_for_problem_solving.
[4] TEMPLIN J L,HENSON R A.Measurement of psychological disorders using cognitive diagnosis models[J].Psychological,Methods,2006,11(3):287-305.
[5] CHANG Huahua.Making computerized adaptive testing diagnostic tools for schools[EB/OL].[2021-12-18].https://www.mendeley.com/catalogue/f222f893-6e44-3fcf-b3ab-661f2fce7047/.
[6] CHENG Ying.The dual information method for item selection in cognitive diagnostic computerized adaptive testing[D].Urbana-Champaign:University of Illinois at Urbana-Champaign,2007.
[7] 罗芬,王晓庆,蔡艳,等.基于基尼指数的双目标CD-CAT选题方法[J].心理学报,2020,52(12):1452-1465.
[8] HUANG Hungyu.Utilizing response times in cognitive diagnostic computerized adaptive testing under the higher-order deterministic input,noisy 'and' gate model[J].British Journal of Mathematical and Statistical Psychology,2020,73(1):109-141.
[9] WANG Chun,CHANG Huahua,DOUGLAS J.Combining CAT with cognitive diagnosis:a weighted item selection approach[J].Behavior Research Methods,2012,44:95-109.
[10] de la TORRE J,DOUGLAS J A.Higher-order latent trait models for cognitive diagnosis[J].Psychometrika,2004,69:333-353.
[11] DAI Buyun,ZHANG Minqiang,LI Guangming.Exploration of item selection in dual-purpose cognitive diagnostic computerized adaptive testing:based on the RRUM[J].Applied Psychological Measurement,2016,40(8):625-640.
[12] KANG HYEON-AH,ZHANG Susu,CHANG Huahua.Dual-objective item selection criteria in cognitive diagnostic computerized adaptive testing[J].Journal of Educational Measurement,2017,54(2):165-183.
[13] MCGLOHEN M,CHANG Huahua.Combining computer adaptive testing technology with cognitively diagnostic assessment[J].Behavior Research Methods,2008,40(3):808-821.
[14] ZHENG Chanjin,HE Guanrui,GAO Chunlei.The information product methods:a unified approach to dual-purpose computerized adaptive testing[J].Applied Psychological Measurement,2018,42(4):321-324.
[15] 涂冬波,蔡艳,戴海琦.几种常用非补偿型认知诊断模型的比较与选用:基于属性层级关系的考量[J].心理学报,2013,45(2):243-252.
[16] TATSUOKA K K.A probabilistic model for diagnosing misconceptions by the pattern classification approach[J].Journal of Educational Statistics,1985,10(1):55-73.
[17] de la TORRE J.The generalized DINA model framework[J].Psychometrika,2011,76:179-199.
[18] JUNKER B W,SIJTSMA K.Cognitive assessment models with few assumptions,and connections with nonparametric item response theory[J].Applied Psychological Measurement,2001,25(3):258-272.
[19] COVER T M,THOMAS J A.Elements of information theory[M].New York:Wiley,1991.
[20] ZHENG Chanjin,CHANG Huahua.High-efficiency response distribution-based item selection algorithms for short-length cognitive diagnostic computerized adaptive testing[J].Applied Psychological Measurement,2016,40(8):608-624.
[21] de la TORRE J,LEE Y S.A note on the invariance of the DINA model parameters[J].Journal of Educational Measurement,2010,47(1):115-127.
[22] de la TORRE J,HONG Y,DENG W.Factors affecting the item parameter estimation and classification accuracy of the DINA model[J].Journal of Educational Measurement,2010,47(2):227-249.
[23] MA Wenchao,de la TORRE J.GDINA:an R package for cognitive diagnosis modeling[J].Journal of Statistical Software,2020,93(14):1-26.
[24] KAPLAN M,de la TORRE J,BARRADA J R.New item selection methods for cognitive diagnosis computerized adaptive testing[J].Applied Psychological Measurement,2015,39(3):167-188.
[25] de la TORRE J.DINA model and parameter estimation:a didactic[J].Journal of Educational and Behavioral Statistics,2009,34(1):115-130.
[26] PATTON J M,CHENG Ying,YUAN Kehai,et al.The influence of item calibration error on variable-length computerized adaptive testing[J].Applied Psychological Measurement,2013,37(1):24-40.
[27] 蔡艳,苗莹,涂冬波.多级评分的认知诊断计算机化适应测验[J].心理学报,2016,48(10):1338-1346.
[28] 韩雨婷,高旭亮,汪大勋,等.多级评分项目的多维CAT选题方法开发[J].心理科学,2018,41(6):1500-1507.
[29] 康春花,辛涛.测验理论的新发展:多维项目反应理论[J].心理科学进展,2010,18(3):530-536.
[30] CHENG Ying.When cognitive diagnosis meets computerized adaptive testing:CD-CAT[J].Psychometrika,2009,74(4):619-632.

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备注/Memo

备注/Memo:
收稿日期:2022-01-03
基金项目:国家自然科学基金(31960186,31760288,31660278)资助项目.
通信作者:蔡 艳(1979—),女,江西宜春人,教授,博士,博士生导师,主要从事心理统计与测量研究.E-mail:cy1979123@aliyun.com
更新日期/Last Update: 2022-03-25