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Identification, estimation, and q-matrix validation of hierarchically structured attributes in cognitive diagnosis

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Title
Identification, estimation, and q-matrix validation of hierarchically structured attributes in cognitive diagnosis
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Akbay
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Lokman
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1983-
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Lokman Akbay
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RoleTerm (authority = RULIB)
author
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de la Torre
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Jimmy
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Jimmy de la Torre
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Advisory Committee
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RoleTerm (authority = RULIB)
chair
Name (type = personal)
NamePart (type = family)
Chiu
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Chia-Yi
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Chia-Yi Chiu
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Advisory Committee
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internal member
Name (type = personal)
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Suh
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Youngsuk
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Youngsuk Suh
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Advisory Committee
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internal member
Name (type = personal)
NamePart (type = family)
Hou
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Likun
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Likun Hou
Affiliation
Advisory Committee
Role
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outside member
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Rutgers University
Role
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degree grantor
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Graduate School - New Brunswick
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school
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Text
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theses
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2016
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2016-10
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2016
Place
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xx
Language
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eng
Abstract (type = abstract)
Many cognitive diagnosis model (CDM) examples assume independent cognitive skills; however, cognitive skills need not be investigated in isolation (Kuhn, 2011; Tatsuoka, 1995). Kuhn (2001) argues that some preliminary knowledge can be the foundation for more sophisticated knowledge or skills. When this type of hierarchical relationships among the attributes are not taken into account, estimation results of the conventional CDMs may be biased or less accurate. Hence, this dissertation investigates the change in the degree of accuracy and precision in the item parameter estimates and correct attribute classification rates of different estimation approaches based on modi cation of either the Q-matrix or prior distribution. Modi fication of the prior distribution and the Q-matrix depend on the assumed hierarchical structure, as such, identifying the correct hierarchical structure is of the essence. To address the subjectivity in the conventional methods for attribute structure identification (i.e., expert opinions via content analysis and verbal data analyses such as interviews and think-aloud protocols), this dissertation proposes a likelihood-ratio test based exhaustive empirical search for identifying hierarchical structures. It further suggests a likelihood-approach for selection of the most accurate hierarchical structure when multiple candidates are present. Furthermore, implementation of the CDMs requires construction of a Q-matrix to indicate the associations between test items and attributes required for successful completion of the items (de la Torre, 2008; Chiu, 2013). Q-matrix construction heavily depends on content expert opinions, as such this subjective process may result in misspecifications in the Q-matrix. Up to date, several parametric and nonparametric Q-matrix validation methods have been proposed to address the misspeci fications that may emerge due to fallible judgments of experts in Q-matrix construction (Chiu, 2013). Yet, although they have been examined under various conditions, none of these methods was tested under hierarchical attribute structures. Therefore, this dissertation further investigates the reciprocal impact of misspeci fied Q-matrix and hierarchical structure on hierarchy identification and Q-matrix validation. The results showed that structured prior distribution led to the most accurate and precise item parameter estimation, and highest correct examinee classification. When an unstructured prior was employed, impact of structured Q-matrix was different for compensatory and noncompensatory CDMs. Furthermore, study results showed that likelihood-based exhaustive search was promising in identification/validation of hierarchical attribute structure. Lastly, results indicated that performance of Q-matrix validation methods might not be as high when they are used as is under hierarchical attribute structures.
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Topic
Education
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Title
Rutgers University Electronic Theses and Dissertations
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ETD
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ETD_7632
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electronic resource
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application/pdf
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text/xml
Extent
1 online resource (xi, 115 p. : ill.)
Note (type = degree)
Ph.D.
Note (type = bibliography)
Includes bibliographical references
Note (type = statement of responsibility)
by Lokman Akbay
RelatedItem (type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier (type = local)
rucore19991600001
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NjNbRU
Identifier (type = doi)
doi:10.7282/T3RR21JV
Genre (authority = ExL-Esploro)
ETD doctoral
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Rights

RightsDeclaration (ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder (type = personal)
Name
FamilyName
Akbay
GivenName
Lokman
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2016-09-26 08:37:00
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Name
LOKMAN AKBAY
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
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Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
RightsEvent
DateTime (encoding = w3cdtf); (qualifier = exact); (point = start)
2016-10-31
DateTime (encoding = w3cdtf); (qualifier = exact); (point = end)
2017-10-31
Type
Embargo
Detail
Access to this PDF has been restricted at the author's request. It will be publicly available after October 31st, 2017.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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2016-09-26T19:58:42
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2016-09-26T19:58:42
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