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Comparison of General Diagnostic Models (GDM) and Bayesian Networks Using a Middle School Mathematics Test

Title: A Comparison of General Diagnostic Models (GDM) and Bayesian Networks Using a Middle School Mathematics Test.
Name(s): Wu, Haiyan, author
Almond, Russell, professor directing dissertation
Rice, Diana, university representative
Becker, Betsy, committee member
Shute, Valerie, committee member
Department of Educational Psychology and Learning Systems, degree granting department
Florida State University, degree granting institution
Type of Resource: text
Genre: Text
Issuance: monographic
Date Issued: 2013
Publisher: Florida State University
Florida State University
Place of Publication: Tallahassee, Florida
Physical Form: computer
online resource
Extent: 1 online resource
Language(s): English
Abstract/Description: General diagnostic models (GDMs) and Bayesian networks are mathematical frameworks that cover a wide variety of psychometric models. Both extend latent class models, and while GDMs also extend item response theory (IRT) models, Bayesian networks can be parameterized using discretized IRT. The purpose of this study is to examine similarities and differences between GDMs and Bayesian networks using both simulated data and real test data sets. The performances of the two frameworks in data generation and estimation under various possible conditions are investigated. Several indices for accuracy and precision are examined as well as the agreement between the GDM and Bayesian network for simulated data and a real data set in this study. Both have problems with identifiability and high-level proficiency variables. Bayesian network slightly better with small samples and can use correlations among proficiency variables to stabilize estimates for scales with few items.
Identifier: FSU_migr_etd-8684 (IID)
Submitted Note: A Dissertation submitted to the Department of Educational Psychology and Learning Systems in partial fulfillment of the requirements for the degree of Doctor of Philosophy.
Degree Awarded: Fall Semester, 2013.
Date of Defense: November 1, 2013.
Keywords: Bayesian network, Cognitive Diagnosis Model, Evidence-centered Assessment Design, Evidence Model, General Diagnostic Model, Proficiency Model
Bibliography Note: Includes bibliographical references.
Advisory Committee: Russell Almond, Professor Directing Dissertation; Diana Rice, University Representative; Betsy Becker, Committee Member; Valerie Shute, Committee Member.
Subject(s): Educational psychology
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Host Institution: FSU

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Wu, H. (2013). A Comparison of General Diagnostic Models (GDM) and Bayesian Networks Using a Middle School Mathematics Test. Retrieved from