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Title:Some practical item selection algorithms in cognitive diagnostic computerized adaptive testing -- smart diagnosis for smart learning
Author(s):Zheng, Chanjin
Director of Research:Chang, Hua-Hua
Doctoral Committee Chair(s):Chang, Hua-Hua
Doctoral Committee Member(s):Anderson, Carolyn J.; Zhang, Jinming; Douglas, Jeffrey A.; Culpepper, Steven A.
Department / Program:Educational Psychology
Discipline:Educational Psychology
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):cognitive diagnostic computerized adaptive testing (CD-CAT)
item selection algorithms
Abstract:The current studies represent an effort to advance the feasibility of cognitive diagnostic computerized adaptive testing (CD-CAT), an intelligent educational measurement tool that was envisioned as enhancing individualized learning over twenty years ago. Several new selection algorithms are proposed for addressing two important issues in CD-CAT: measurement efficiency and item exposure control. The posterior-weighted CDM discrimination index (PWCDI) and posterior-weighted attribute-level CDM discrimination index (PWACDI) are computationally affordable and highly efficient alternatives to other information index-based algorithms. The binary stratification algorithm offers an elegant solution to item exposure control in both fixed-length and variable-length CD-CAT, compared with the restrictive stochastic methods for fixed-length CD-CAT and SHTVOR for variable-length CD-CAT.
Issue Date:2015-04-21
Type:Thesis
URI:http://hdl.handle.net/2142/78750
Rights Information:Copyright 2015 Chanjin Zheng
Date Available in IDEALS:2015-07-22
Date Deposited:May 2015


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