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Permanent link (DOI): https://doi.org/10.7939/R3C712

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Estimating attribute-based reliability in cognitive diagnostic assessment Open Access

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Other title
Subject/Keyword
reliability, cognitive diagnostic assessment
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Zhou, Jiawen
Supervisor and department
Gierl, Mark J. (Educational Psychology)
Leighton, Jacqueline P. (Educational Psychology)
Cui, Ying (Educational Psychology)
Examining committee member and department
Jang, Eunice E. (Education, University of Toronto)
Gokiert, Rebecca (Faculty of Extension)
Carbonaro, Michael (Educational Psychology)
Department
Department of Educational Psychology
Specialization

Date accepted
2010-04-07T19:42:32Z
Graduation date
2010-06
Degree
Doctor of Philosophy
Degree level
Doctoral
Abstract
Cognitive diagnostic assessment (CDA) is a testing format that employs a cognitive model to, first, develop or identify items measuring specific knowledge and skills and, then, use this model to direct psychometric analyses of examinees’ item response patterns to promote diagnostic inferences. The attribute hierarchy method (AHM, Leighton, Gierl, & Hunka, 2004) is a psychometric procedure for classifying examinees’ test item responses into a set of structured attribute patterns associated with different components from a cognitive model of task performance. Attribute reliability is a fundamental concept in cognitive diagnostic assessment because it refers to the consistency of the decisions made in diagnostic test about examinees’ mastery of specific attributes. In this study, an adapted attribute-based reliability estimate was evaluated in comparison of the standard Cronbach’s alpha using simulated data. Factors expected to influence attribute reliability estimates, including test length, sample size, model structure, and model-data fit level, were also studied. Results of this study revealed that the performances of the two attribute-based reliability estimation indices are comparable; however, the adapted index is conceptually more meaningful. Test length, model structure, and model-data fit were shown to impact attribute reliability estimates differentially. Implications to researchers and practitioners were given based on the simulation results. Limitations of the present study and future directions were also discussed.
Language
English
DOI
doi:10.7939/R3C712
Rights
License granted by Jiawen Zhou (jzhou@ualberta.ca) on 2010-04-07T16:11:23Z (GMT): Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of the above terms. The author reserves all other publication and other rights in association with the copyright in the thesis, and except as herein provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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