Using the Hybrid Model of GHMM and IRT to Calibrate the Guessing Effects of Ordering Theory and Item Relational Structure Analysis

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Title:	Using the Hybrid Model of GHMM and IRT to Calibrate the Guessing Effects of Ordering Theory and Item Relational Structure Analysis
Authors:	Pan Huang Chia Chi
Contributors:	Department of Computer Science and Information Engineering
Keywords:	General Hidden Markov Model;Guessing-parameter;Ordering theory;Item relational structure
Date:	2004
Issue Date:	2009-11-18 13:13:07 (UTC+0)
Publisher:	Asia University
Abstract:	It used experience rule generally in setting value for Ordering theory and Item Relational Structure (IRS). And for the computerized adaptive testing (CAT) or computerized adaptive diagnosis testing, it almost be tested by multiple choice method which with guessing-parameter. In this study, it was processed in Monte Carlo Method which using general hidden Markov model with behavior model of smooth none parameter examination question which combining guessing-parameter, and study the suitable for using in OT and IRS.
Appears in Collections:	[Department of Computer Science and Information Engineering] Theses & dissertations

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