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Conference Paper: A General Cognitive Diagnosis Model For Polytomous Attributes

TitleA General Cognitive Diagnosis Model For Polytomous Attributes
Authors
Qiu, Xde la Torre, JSantos, C
Issue Date2021
Citation
The 2021 National Council on Measurement in Education (NCME) Annual Meeting: Bridging Research and Practice, Virtual Meeting, 9-11 June 2021 How to Cite?
AbstractThe pG-DINA model for polytomous attributes can benefit classroom instruction. However, it depends on a stringent assumption. This study proposes a general CDM that relaxes the assumption and allows different attribute levels to contribute differentially to the success probability. Simulation studies were conducted to evaluate the new model’s parameter recovery
DescriptionTopics in Cognitive Diagnosis Modeling: Paper Session
Persistent Identifierhttp://hdl.handle.net/10722/304827

 

DC FieldValueLanguage
dc.contributor.authorQiu, X-
dc.contributor.authorde la Torre, J-
dc.contributor.authorSantos, C-
dc.date.accessioned2021-10-05T02:35:46Z-
dc.date.available2021-10-05T02:35:46Z-
dc.date.issued2021-
dc.identifier.citationThe 2021 National Council on Measurement in Education (NCME) Annual Meeting: Bridging Research and Practice, Virtual Meeting, 9-11 June 2021-
dc.identifier.urihttp://hdl.handle.net/10722/304827-
dc.descriptionTopics in Cognitive Diagnosis Modeling: Paper Session-
dc.description.abstractThe pG-DINA model for polytomous attributes can benefit classroom instruction. However, it depends on a stringent assumption. This study proposes a general CDM that relaxes the assumption and allows different attribute levels to contribute differentially to the success probability. Simulation studies were conducted to evaluate the new model’s parameter recovery-
dc.languageeng-
dc.relation.ispartofNational Council on Measurement in Education (NCME) 2021 Annual Meeting-
dc.titleA General Cognitive Diagnosis Model For Polytomous Attributes-
dc.typeConference_Paper-
dc.identifier.emailQiu, X: xlqiu@hku.hk-
dc.identifier.emailde la Torre, J: j.delatorre@hku.hk-
dc.identifier.authorityde la Torre, J=rp02159-
dc.identifier.hkuros326170-

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