University of Illinois Urbana-Champaign

The application of a cognitive diagnostic model on the test of practical Chinese

Tang, Xiuxiu

Content Files
TANG-THESIS-2019.pdf

Permalink

https://hdl.handle.net/2142/105274

Description

Title
The application of a cognitive diagnostic model on the test of practical Chinese
Author(s)
Tang, Xiuxiu
Issue Date
2019-04-26
Director of Research (if dissertation) or Advisor (if thesis)
Zhang, Jinming
Committee Member(s)
  • Anderson, Carolyn
  • Kern, Justin
Department of Study
Educational Psychology
Discipline
Educational Psychology
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Date of Ingest
2019-08-23T20:48:28Z
Keyword(s)
  • CDM
  • Q-matrix
Abstract
Cognitive Diagnostic Models (CDMs) are frequently used in the second language proficiency exams to analyze test takers’ strengths and weaknesses. This study retrofits a CDM known as the Fusion model onto a non-diagnostic test data from the reading comprehension test of the Test of Practical Chinese (C.TEST). It focuses on the construction and modification of the Q-matrix which specifies the relationship between test items and attributes needed to answer each item correctly. There are three stages in this study: (1) identifying reading attributes, (2) constructing the initial Q-matrix, and (3) modifying the initial Q-matrix. In the first stage, six reading attributes were identified based on literature review and 3 experts’ judgment. In the second stage, test items were carefully reviewed by three experts, and then the initial Q-matrix was created by them. In the third stage, item parameters and model fit statistics were evaluated to refine the Q-matrix. Four item parameters, r11.3, c2, c6, c27, were dropped from the Fusion model. Results suggest that the refined Q-matrix is well-defined, and it can be applied to the C.TEST reading test since it has a good model fit and is able to effectively distinguish item masters from item non-masters.
Graduation Semester
2019-05
Type of Resource
text
Permalink
http://hdl.handle.net/2142/105274
Copyright and License Information
Copyright 2019 Xiuxiu Tang

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