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Article: DINA model and parameter estimation: A didactic

TitleDINA model and parameter estimation: A didactic
Authors
KeywordsCognitive diagnosis
Issue Date2009
Citation
Journal of Educational and Behavioral Statistics, 2009, v. 34, n. 1, p. 115-130 How to Cite?
AbstractCognitive and skills diagnosis models are psychometric models that have immense potential to provide rich information relevant for instruction and learning. However, wider applications of these models have been hampered by their novelty and the lack of commercially available software that can be used to analyze data from this psychometric framework. To address this issue, this article focuses on one tractable and interpretable skills diagnosis model-the DINA model-and presents it didactically. The article also discusses expectation-maximization and Markov chain Monte Carlo algorithms in estimating its model parameters. Finally, analyses of simulated and real data are presented. © 2009 AERA.
Persistent Identifierhttp://hdl.handle.net/10722/228079
ISSN
2015 Impact Factor: 1.083
2015 SCImago Journal Rankings: 2.025

 

DC FieldValueLanguage
dc.contributor.authorde la Torre, Jimmy-
dc.date.accessioned2016-08-01T06:45:08Z-
dc.date.available2016-08-01T06:45:08Z-
dc.date.issued2009-
dc.identifier.citationJournal of Educational and Behavioral Statistics, 2009, v. 34, n. 1, p. 115-130-
dc.identifier.issn1076-9986-
dc.identifier.urihttp://hdl.handle.net/10722/228079-
dc.description.abstractCognitive and skills diagnosis models are psychometric models that have immense potential to provide rich information relevant for instruction and learning. However, wider applications of these models have been hampered by their novelty and the lack of commercially available software that can be used to analyze data from this psychometric framework. To address this issue, this article focuses on one tractable and interpretable skills diagnosis model-the DINA model-and presents it didactically. The article also discusses expectation-maximization and Markov chain Monte Carlo algorithms in estimating its model parameters. Finally, analyses of simulated and real data are presented. © 2009 AERA.-
dc.languageeng-
dc.relation.ispartofJournal of Educational and Behavioral Statistics-
dc.subjectCognitive diagnosis-
dc.titleDINA model and parameter estimation: A didactic-
dc.typeArticle-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.doi10.3102/1076998607309474-
dc.identifier.scopuseid_2-s2.0-68049141890-
dc.identifier.volume34-
dc.identifier.issue1-
dc.identifier.spage115-
dc.identifier.epage130-

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