{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/105274"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/105274","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"The application of a cognitive diagnostic model on the test of practical Chinese","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Tang, Xiuxiu"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Educational Psychology","degree_department":null,"school":null,"contributors":["Zhang, Jinming","Anderson, Carolyn","Kern, Justin"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2019,"date_issued":"2019-08-23T20:48:28Z","date_published":"2019-08-23T20:48:28Z","updated_at":"2026-07-22T22:24:44Z","subjects":["CDM","Q-matrix"],"languages":["en"],"rights":["Copyright 2019 Xiuxiu Tang"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/105274","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Zhang, Jinming","Anderson, Carolyn","Kern, Justin"]},{"key":"dc:creator","label":"Author","values":["Tang, Xiuxiu"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2019-08-23T20:48:28Z","2021-08-24T09:15:38Z","2019-04-26","2019-05"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Educational Psychology"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["CDM","Q-matrix"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2019 Xiuxiu Tang"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/105274"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01","The student, Xiuxiu Tang, accepted the attached license on 2019-04-26 at 08:22.","The student, Xiuxiu Tang, submitted this Thesis for approval on 2019-04-26 at 08:24.","This Thesis was approved for publication on 2019-04-26 at 10:25.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13941 on 2019-08-22 at 16:24:02","Made available in DSpace on 2019-08-23T20:48:28Z (GMT). No. of bitstreams: 2 TANG-THESIS-2019.pdf: 463490 bytes, checksum: 85dea6c81c9327abe5405e66e0fc509f (MD5) LICENSE.txt: 4208 bytes, checksum: 71e8c9d18412a1db56ac56a38b3274b7 (MD5) Previous issue date: 2019-04-26","Embargo set by: Seth Robbins for item 112396 Lift date: 2021-08-23T20:48:32Z Reason: Author requested closed access (OA after 2yrs) in Vireo ETD system","Limited Restriction Lifted for Item 112396 on 2021-08-24T09:15:38Z."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["The application of a cognitive diagnostic model on the test of practical Chinese"]}]}],"canonical_facts":{"dc:contributor":["Zhang, Jinming","Anderson, Carolyn","Kern, Justin"],"dc:creator":["Tang, Xiuxiu"],"dc:date":["2019-08-23T20:48:28Z","2021-08-24T09:15:38Z","2019-04-26","2019-05"],"dc:description":["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.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2021-05-01","The student, Xiuxiu Tang, accepted the attached license on 2019-04-26 at 08:22.","The student, Xiuxiu Tang, submitted this Thesis for approval on 2019-04-26 at 08:24.","This Thesis was approved for publication on 2019-04-26 at 10:25.","DSpace SAF Submission Ingestion Package generated from Vireo submission #13941 on 2019-08-22 at 16:24:02","Made available in DSpace on 2019-08-23T20:48:28Z (GMT). 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