我们的网站为什么显示成这样？

可能因为您的浏览器不支持样式，您可以更新您的浏览器到最新版本，以获取对此功能的支持，访问下面的网站，获取关于浏览器的信息：

|本期目录/Table of Contents|

 贝叶斯网在小样本认知诊断中的应用(PDF)

《心理学探新》[ISSN:1003-5184/CN:36-1228/B]

期数:
 2024年03期
页码:
 264-272
栏目:
 心理统计与测量
出版日期:
 2024-07-15

文章信息/Info

Title:
 The Application of Bayesian Networks in Cognitive Diagnosis with Small Sample Size
文章编号:
1003-5184(2024)03-0264-09
作者:
 汪玲玲
 (沈阳师范大学教育科学学院,沈阳 110034)
Author(s):
 Wang Lingling
 (School of Educational Science,Shenyang Normal University,Shenyang 110034)
关键词:
 认知诊断评估;  贝叶斯网络;  课堂评估;  小样本
Keywords:
 cognitive diagnostic assessment;  bayesian networks;  classroom evaluation;  small sample size
分类号:
 B841.2
DOI:
 -
文献标识码:
 A
摘要:
 认知诊断的一个理想应用场景是在小样本情境的课堂测试中提供学生的诊断信息,进而促进补救教学; 当前多数的认知诊断模型需较大的样本量进行参数估计,并且有些参数估计方法存在计算效率问题不能提供及时的诊断反馈。基于贝叶斯网的认知诊断方法可以实现小样本情况下诊断分类,并且能够提供及时的诊断反馈,这对于推进认知诊断在实践中的应用提供了可能。研究尝试使用贝叶斯网络方法进行小样本认知诊断分类,模拟研究表明:贝叶斯网络方法的诊断分类性能优于同样适用于小样本的海明距离法。
Abstract:
 In this study,Bayesian networks(BN)are proposed to conduct cognitive diagnosis in a small sample.The combination of IRP(Ideal Response Pattern)and EM parameter estimating methods can overcome the shortcomings of IRP and EM algorithms respectively,and can realize the BN application in a small sample size.The Monte Carlo simulation study is used to examine the performance of the BN-IRP-EM method in a small sample size,compared with the hamming distance method.In the simulation study,the pattern match ratio and average attribute match ratio are used as criteria to evaluate the classification accuracy of different approaches.To demonstrate the effectiveness of the BN-IRP-EM method,the BN based purely on the IRP method is adopted as the controlling method,another controlling method is the hamming distance(H-D)method.The results are as follows:the classification rate of the BN-IRP method is slightly higher than that of the H-D method which is based on the same IRP information except for some conditions.The classification rate of the BN-IRP-EM method is higher than the BN-IRP method and the H-D method in all circumstances.In the BN-IRP-EM condition,due to the incorporation of the empirical information,the classification rate is gradually increasing with the increase in sample size.These outcomes demonstrated that the BN-IRP-EM method could be used in a small sample size and can promote the application of CDA in classroom assessment.

参考文献/References

 宋丽红,汪文义,戴海琦,丁树良.(2016).基于贝叶斯网的认知诊断模型构建.心理科学,39(4),783-789.
唐小娟,丁树良,俞宗火.(2016).粗糙集理论在认知诊断中的应用.心理科学,39(4),790-795.
涂冬波,蔡艳,戴海琦.(2012).基于DINA模型的Q矩阵修正方法.心理学报,44(4),558-568.
汪文义,丁树良,宋丽红,邝铮,曹慧媛.(2016).神经网络和支持向量机在认知诊断中的应用.心理科学,39(4),777-782.
王军.(2012).贝叶斯网络在认知诊断中的应用(硕士学位论文).南京师范大学,南京.
薛薇,陈欢歌.(2012).基于Clementine的数据挖掘.中国人民大学出版社.
喻晓锋.(2009).贝叶斯网络在认知诊断中的应用(硕士学位论文).江西师范大学,南昌.
喻晓锋,丁树良,秦春影,陆云娜.(2011).贝叶斯网在认知诊断属性层级结构确定中的应用.心理学报,43(3),338-346.
喻晓锋,肖遇春,秦春影.(2023).基于贝叶斯网模型的多级计分诊断测验分类及比较研究.心理与行为研究,21(1),49-57.
张连文,郭海鹏.(2006).贝叶斯网引论.北京:科学出版社.
Almond,R.G.,Mislevy,R.J.,et al.(2015).Bayesian networks in educational assessment.New York,NY:Springer.doi:10.1007/978-1-4939-2125-6
Chiu,C.Y.,Douglas,J.A.,& Li,X.(2009).Cluster analysis for cognitive diagnosis:Theory and applications.Psychometrika,74,633-665.doi:10.1007/s11336-009-9125-0
Chiu,C.-Y.,& Douglas,J.(2013).A nonparametric approach to cognitive diagnosis by proximity to ideal response patterns.Journal of Classification,30,225-250.doi:10.1007/s00357-013-9132-9
Chen,J.S.(2017).A residual-based approach to validate Q Matrix specifications.Applied Psychological Measurement,41,277-293.doi:10.1177/0146621616686021
Cui,Y.,Gierl,M.,& Guo,Q.(2016).Statistical classification for cognitive diagnostic assessment:An artificial neural network approach.Educational Psychology,36(6),1065-1082.doi:10.1080/01443410.2015.1062078
DiBello,L.V.,Roussos,L.A.,& Stout,W.F.(2007).Review of cognitively diagnostic assessment and a summary of psychometric models.In C.R.Rao & S.Sinharay(Eds.),Handbook of statistics psychometrics(Vol.26,pp.979-1030).Amsterdam,The Netherlands:Elsevier Science Publishers.
Embretson,S.(1984).A general latent trait model for response processes. Psychometrika,49(2),175-186.doi:10.1007/BF02294171
Gierl,M.J.,Zheng,Y.,& Cui,Y.(2008).Using the Attribute Hierarchy Method to Identify and Interpret Cognitive Skills that Produce Group Differences.Journal of Educational Measurement,45(1),65-89.
Hartz,S.M.(2002).A Bayesian framework for the unified model for assessing cognitive abilities:Blending theory with practicality.Unpublished doctoral dissertation,University of Illinois at Urbana-Champaign,IL.
Huff,K.,& Goodman,D.P.(2007).The demand for cognitive diagnostic assessment.In.J.P.Leighton & M.J.Gierl(Eds.),Cognitive diagnostic assessment for education:Theory and applications(pp.19-60).New York,NY,US:Cambridge University Press.
Henson,R.A.,Templin,J.L.,& Willse,J.T.(2009).Defining a family of cognitive diagnosis models using log-linear models with latent variables.Psychometrika,74,191-210.doi:10.1007/s11336-008-9089-5.
Korb,K.,& Nicholson,A.E.(2010).Bayesian artificial intelligence(2nd Ed).London:Chapman & Hall.
Leighton,J.P.,& Gierl,M.J.(Eds.).(2007a).Cognitive diagnostic assessment for education:Theory and practices.Cambridge.Cambridge University Press.
Lee,J.,& Corter,J.E.(2011).Diagnosis of subtraction bugs using Bayesian networks.Applied Psychological Measurement,35(1),27-47.doi:10.1177/0146621610377079
Ma,W.C.,& Jiang,Z.H.(2020).Estimating Cognitive Diagnosis Models in Small Samples:Bayes Modal Estimation and Monotonic Constraints.Applied Psychological Measurement,45(2).DOI:10.1177/0146621620977681.
Neapolitan,R.E.(2004).Learning Bayesian Networks.Prentice Hall.
Shu,Z.,Henson,R.,& Willse,J.(2013).Using neural network analysis to define methods of DINA model estimation for small sample sizes.Journal of Classification,30,173-194.doi:10.1007/s00357-013-9134-7
Sinharay,S.(2006).Model diagnostics for Bayesian networks.Journal of Educational and Behavioral Statistics,31,1-33.
Sinharay,S.,& Almond,R.G.(2007).Assessing the fit of cognitive diagnostic models:A case study.Educational and Psychological Measurement,67,239-257.
Scutari,M.(2010).Learning Bayesian Networks with the bnlearn R Package.Journal of Statistical Software,35(3),1-22.URL http://www.jstatsoft.org/v35/i03/.
Tatsuoka,K.K.,& Tatsuoka,M.M.(1997).Computerized cognitive diagnostic adaptive testing:Effect on remedial instruction as empirical validation.Journal of Educational Measurement,34(1),3-20.doi:10.1111/j.1745-3984.1997.tb00504.x
von Davier,M.(2005).A general diagnostic model applied to language testing data(Research Report No.RR-05-16).Princeton,NJ:Educational Testing Service.
von Davier,M.(2008).A general diagnostic model applied to language testing data.British Journal of Mathematical and Statistical Psychology,61,287-301.doi:10.1348/000711007X193957
Wang,C.(2013).Mutual Information Item Selection Method in Cognitive Diagnostic Computerized Adaptive Testing With Short Test Length.Educational and Psychological Measurement,73(6),1017-1035.doi:10.1177/0013164413498256
Wu,H.Y.(2013).Comparison of general diagnostic models(GDM)and Bayesian networks.using a middle school mathematics test(Unpublished doctoral dissertation).Florida State University,America.

备注/Memo

备注/Memo:
 基金项目:教育部人文社科青年基金“基于贝叶斯网的认知诊断Q矩阵估计与检验方法”(22YJCZH160),辽宁省属本科高校基本科研业务费专项资金资助。
通信作者:汪玲玲,E-mail:wling-007@163.com。
更新日期/Last Update:  2024-07-10