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- Publisher Website: 10.1080/15434303.2016.1210610
- Scopus: eid_2-s2.0-84984620228
- WOS: WOS:000383766900004
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Article: Retrofitting Non-cognitive-diagnostic Reading Assessment Under the Generalized DINA Model Framework
Title | Retrofitting Non-cognitive-diagnostic Reading Assessment Under the Generalized DINA Model Framework |
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Authors | |
Issue Date | 2016 |
Citation | Language Assessment Quarterly, 2016, v. 13, n. 3, p. 218-230 How to Cite? |
Abstract | © 2016 Taylor & Francis. Cognitive diagnosis models (CDMs) are psychometric models developed mainly to assess examinees’ specific strengths and weaknesses in a set of skills or attributes within a domain. By adopting the Generalized-DINA model framework, the recently developed general modeling framework, we attempted to retrofit the PISA reading assessments, a non-cognitive-diagnostic assessment, in three steps: (a) Q-matrices construction based on item content analysis; (b) Q-matrices validation and refinement based on a saturated CDM; and (c) reduced CDMs evaluations based on acceptable Q-matrix. Our research showed that (a) the practice of retrofitting non-cognitive-diagnostic assessment for cognitive diagnostic purpose was feasible; (b) Q-matrix construction and CDM selection were especially important when retrofitting approach was adopted; (c) compensatory and saturated CDMs could fit the PISA reading assessment better than other CDMs; and (d) the application of CDMs to reading assessments may promote research on reading construct. |
Persistent Identifier | http://hdl.handle.net/10722/288717 |
ISSN | 2023 Impact Factor: 1.4 2023 SCImago Journal Rankings: 0.912 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Chen, Huilin | - |
dc.contributor.author | Chen, Jinsong | - |
dc.date.accessioned | 2020-10-12T08:05:41Z | - |
dc.date.available | 2020-10-12T08:05:41Z | - |
dc.date.issued | 2016 | - |
dc.identifier.citation | Language Assessment Quarterly, 2016, v. 13, n. 3, p. 218-230 | - |
dc.identifier.issn | 1543-4303 | - |
dc.identifier.uri | http://hdl.handle.net/10722/288717 | - |
dc.description.abstract | © 2016 Taylor & Francis. Cognitive diagnosis models (CDMs) are psychometric models developed mainly to assess examinees’ specific strengths and weaknesses in a set of skills or attributes within a domain. By adopting the Generalized-DINA model framework, the recently developed general modeling framework, we attempted to retrofit the PISA reading assessments, a non-cognitive-diagnostic assessment, in three steps: (a) Q-matrices construction based on item content analysis; (b) Q-matrices validation and refinement based on a saturated CDM; and (c) reduced CDMs evaluations based on acceptable Q-matrix. Our research showed that (a) the practice of retrofitting non-cognitive-diagnostic assessment for cognitive diagnostic purpose was feasible; (b) Q-matrix construction and CDM selection were especially important when retrofitting approach was adopted; (c) compensatory and saturated CDMs could fit the PISA reading assessment better than other CDMs; and (d) the application of CDMs to reading assessments may promote research on reading construct. | - |
dc.language | eng | - |
dc.relation.ispartof | Language Assessment Quarterly | - |
dc.title | Retrofitting Non-cognitive-diagnostic Reading Assessment Under the Generalized DINA Model Framework | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1080/15434303.2016.1210610 | - |
dc.identifier.scopus | eid_2-s2.0-84984620228 | - |
dc.identifier.volume | 13 | - |
dc.identifier.issue | 3 | - |
dc.identifier.spage | 218 | - |
dc.identifier.epage | 230 | - |
dc.identifier.eissn | 1543-4311 | - |
dc.identifier.isi | WOS:000383766900004 | - |
dc.identifier.issnl | 1543-4303 | - |