[1]汪文义,宋丽红,丁树良.基于探索性因素分析的Q矩阵标定方法[J].江西师范大学学报(自然科学版),2015,(02):138-144.
 WANG Wenyi,SONG Lihong,DING Shuliang.The Statistical Specification of the Q-Matrix ——an Integration of EFA and Q-Matrix Validation Method[J].,2015,(02):138-144.
点击复制

基于探索性因素分析的Q矩阵标定方法()
分享到:

《江西师范大学学报》(自然科学版)[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2015年02期
页码:
138-144
栏目:
出版日期:
2015-04-10

文章信息/Info

Title:
The Statistical Specification of the Q-Matrix ——an Integration of EFA and Q-Matrix Validation Method
作者:
汪文义;宋丽红;丁树良
1.江西师范大学计算机信息工程学院,江西 南昌 330022; 2.江西师范大学初等教育学院,江西 南昌 330027
Author(s):
WANG WenyiSONG LihongDING Shuliang
关键词:
Q矩阵 探索性方法 验证性方法 模型整体拟合指标 分类准确性指标
Keywords:
the Q-matrix exploratory method confirmatory method model fit index classification accuracy index
分类号:
B 841.7; TP 301.6
文献标志码:
A
摘要:
标定Q矩阵是认知诊断评估中最基本也是最为关键的一步.如今Q矩阵标定的统计方法,多数为验证性方法,即验证或修正已有Q矩阵中元素的方法.在常见的Q矩阵未知和已有作答数据情形下,提出将探索性因素分析方法和验证性方法相结合的Q矩阵标定方法,并采用模型整体拟合指标、分类准确性指标等,综合确定属性数和Q矩阵.模拟研究表明:新方法可较好标定Q矩阵.
Abstract:
The vast majority of the existing statistical methods to specify the Q-matrix do rely on the draft Q -matrix constructed by the subject matter experts or the researches.Based on previous related research,the authors consider the estimation problem of the Q-matrix under the condition of without having the draft Q-matrix.In particular,they introduce a Q-matrix identification approach which integrates exploratory factor analysis(EFA)with Q-matrix validation method.The results of a simulation study show that the initial Q-matrix can be correctly explored with high recovery rate using the EFA and the validation methods.

参考文献/References:

[1] Leighton J P,Gierl M J,Hunka S M.The attribute hierarchy method for cognitive assessment:A variation on Tatsuoka's rule-space approach [J].Journal of Educational Measurement,2004,41(3):205-237.
[2] 戴海琦,罗照盛.心理测量学 [M].北京:高等教育出版社,2010.
[3] Embretson S E.A general latent trait model for response processes [J].Psychometrika,1984,49(2):175-186.
[4] Tatsuoka K K.Toward an integration of item-response theory and cognitive error diagnosis [C]// Frederiksen N,Glaser R L,Lesgold A M,et al.Diagnostic Monitoring of Skill and Knowledge Acquisition [A].NJ:Erlbaum,1990:453–488.
[5] Huebner A.An overview of recent developments in cognitive diagnostic computer adaptive assessments [J].Practical Assessment,Research & Evaluation,2010,15(3):1-7.
[6] Im S.Statistical consequences of attribute misspeciication of the rule space model [D].New York:Columbia University,2007.
[7] McGlohen M K,Chang Huahua.Combining computer adaptive testing technology with cognitively diagnostic assessment [J].Behavior Research Methods,2008,40(3):808-821.
[8] Chen Ping,Xin Tao,Wang Chun,et al.Online calibration methods for the DINA model with independent attributes in CA-CAT [J].Psychometrika,2012,77(2):201-222.
[9] Chiu C Y.Statistical Refinement of the Q-Matrix in Cognitive Diagnosis [J].Applied Psychological Measurement,2013,37(8):598-618.
[10] DeCarlo L T.On the analysis of fraction subtraction data:the DINA model,classification,latent class sizes,and the Q-matrix [J].Applied Psychological Measurement,2011,35(1):8-26.
[11] DeCarlo L T.Recognizing uncertainty in the Q-matrix via a Bayesian extension of the DINA model [J].Applied Psychological Measurement,2012,36(6):447-468.
[12] 陈平,辛涛.认知诊断计算机化自适应测验中的项目增补[J].心理学报,2011,43(7):836-850.
[13] 汪文义,丁树良,游晓锋.计算机化自适应诊断测验中原始题的属性标定[J].心理学报,2011,43(8):964-976.
[14] de la Torre J.An empirically based method of Q-matrix validation for the DINA model:development and applications [J].Journal of Educational Measurement,2008,45(4):343-362.
[15] Liu Jingchen,,Xu Gongjun,Ying Zhiliang.Data-driven Learning of Q-matrix[J].Applied Psychological Measurement,2012,36(7):548-564.
[16] 涂冬波,蔡艳,戴海琦.基于DINA模型的Q矩阵修正方法 [J].心理学报,2012,44(4):558-568.
[17] Liu Jingchen,Xu Gongjun,Ying Zhiliang.Theory of self-learning Q-matrix [J].Bernoulli,2013,19(5A):1790-1817.
[18] 俞宗火,戴海崎,唐小娟.全息项目因素分析在心理学研究中的应用[J].心理与行为研究,2006,4(4):306-311.
[19] 王权.现代因素分析[M].杭州:杭州大学出版社,1993.
[20] Asparouhov T,Muthén B,Muthén M.Exploratory structural equation modeling [J].Structural Equation Modeling:A Multidisciplinary Journal,2009,16(3):397-438.
[21] Wang Wenyi,Ding Shuliang,Song Lihong.New Q-matrix validation methods and their sensitivity under the DINA model [C].San Francisco:CA,2013.
[22] 丁树良,罗芬,汪文义.认知诊断分类中心的确定[J].心理学探新,2013(05):396-401.
[23] 陈平,辛涛.认知诊断计算机化自适应测验中在线标定方法的开发 [J].心理学报,2011,43(6):710-724.
[24] Chen J S,de la Torre J,Zhang Zao.Relative and absolute fit evaluation in cognitive diagnosis modeling [J].Journal of Educational Measurement,2013,50(2):123-140.
[25] 汪文义,宋丽红,丁树良 等.认知诊断测验的属性分类一致性和分类准确性指标[EB/OL].
[2014-06-01].http://www.paper.edu.cn/html/releasepaper/2014/06/177/.
[26] Feng Yuling,Habing B T,Huebner A.Parameter estimation of the reduced RUM Using the EM algorithm [J].Applied Psychological Measurement,2014,38(2):137-150.
[27] Leighton J P,Gierl M J.Cognitive diagnostic assessment for education:theory and applications [M].New York:Cambridge University Press,2007.
[28] 汪文义,丁树良,题库结构对原始题在线属性标定准确性之影响研究 [J].心理科学,2012,35(2):452-456.
[29] 丁树良,杨淑群,汪文义.可达矩阵在认知诊断测验编制中的重要作用 [J].江西师范大学学报:自然科学版,2010,34(5):490-495.
[30] 丁树良,汪文义,杨淑群.认知诊断测验蓝图的设计 [J].心理科学,2011,34(2):258-265.
[31] Jang E E.A validity narrative Effects of reading skills diagnosis on teaching and learning [D].Urbana:University of Illinois at Urbana-Champaign,2005.

相似文献/References:

[1]甘朝红,汪文义,丁树良.项目属性标错时可达阵补救作用的研究[J].江西师范大学学报(自然科学版),2014,(06):600.
 GAN Chao-hong,WANG Wen-yi,DING Shu-liang.The Research on the Remedial Effects of Reachability Matrix When Identifying an Item Attribute Incorrectly[J].,2014,(02):600.
[2]祝玉芳,王黎华,丁树良,等.多策略的多级评分认知诊断方法的开发[J].江西师范大学学报(自然科学版),2015,(04):371.
 ZHU Yufang,WANG Lihua,DING Shuliang,et al.The Development of Multiple-Strategies Cognitive Diagnosis with Polytomous Response[J].,2015,(02):371.

备注/Memo

备注/Memo:
国家自然科学基金(31360237,31300876,31160203,31100756,30860084);教育部人文社会科学研究青年基金(13YJC880060);江西省教育科学2013年度一般课题(13YB032)
更新日期/Last Update: 1900-01-01