English  |  正體中文  |  简体中文  |  Items with full text/Total items : 58323/91876 (63%)
Visitors : 14081706      Online Users : 69
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/120648


    Title: A Gibbs sampling algorithm that estimates the Q-matrix for the DINA model
    Authors: Chung, Mengta
    Keywords: Q-matrix;DINA;CDM;Bayesian;Gibbs sampler;MCMC
    Date: 2019-09-12
    Issue Date: 2021-04-24 12:10:42 (UTC+8)
    Abstract: Cognitive diagnostic assessment has drawn more attention in recent years, which attempts to evaluate whether an examinee has mastered those cognitive skills or attributes being measured in an assessment. To achieve this objective, a variety of cognitive diagnosis models have been developed. The core element of these models is the Q-matrix, which is a binary matrix that establishes item-to-attribute mapping in an exam. Traditionally, the Q-matrix is fixed and designed by domain experts. However, there are concerns that some domain experts might neglect certain attributes, and that different experts could have different opinions. It is therefore of practical importance to develop an automated method for estimating the attribute-to-item mapping, and the purpose of this study is to develop a Markov Chain Monte Carlo (MCMC) algorithm to estimate the Q-matrix in a Bayesian framework.
    Relation: Journal of Mathematical Psychology 93, 102275
    DOI: 10.1016/j.jmp.2019.07.002
    Appears in Collections:[Department of Management Sciences] Journal Article

    Files in This Item:

    File Description SizeFormat
    index.html0KbHTML3View/Open

    All items in 機構典藏 are protected by copyright, with all rights reserved.


    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback