Test-Level and Item-Level Model Fit Comparison of General vs. Specific Diagnostic Classification Models: A Case of True DCM

Autor/inn/en	Shafipoor, Mahdieh; Ravand, Hamdollah; Maftoon, Parviz
Titel	Test-Level and Item-Level Model Fit Comparison of General vs. Specific Diagnostic Classification Models: A Case of True DCM
Quelle	In: Language Testing in Asia, 11 (2021), Artikel 33 PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Ravand, Hamdollah)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2229-0443
DOI	10.1186/s40468-021-00148-z
Schlagwörter	Forschungsbericht; Goodness of Fit; Models; Classification; Grammar; Vocabulary Development; Language Tests; Achievement Tests; English (Second Language); Second Language Learning; Diagnostic Tests; Test Items; Item Analysis + Suchen Sie Ihr Suchwort? Analogiemodell; Classification system; Klassifikation; Klassifikationssystem; Grammatik; Wortschatzarbeit; Language test; Sprachtest; Achievement test; Achievement; Testing; Test; Tests; Leistungsbeurteilung; Leistungsüberprüfung; Leistung; Testdurchführung; Testen; English as second language; English; Second Language; Englisch als Zweitsprache; Zweitsprachenerwerb; Diagnostic test; Diagnostischer Test; Test content; Testaufgabe; Itemanalyse
Abstract	The current study compared the model fit indices, skill mastery probabilities, and classification accuracy of six Diagnostic Classification Models (DCMs): a general model (G-DINA) against five specific models (LLM, RRUM, ACDM, DINA, and DINO). To do so, the response data to the grammar and vocabulary sections of a General English Achievement Test, designed specifically for cognitive diagnostic purposes from scratch, was analyzed. The results of the test-level-model fit values obtained strong evidence in supporting the G-DINA and LLM models possessing the best model fit. In addition, the ACDM and RRUM were almost very identical to that of the G-DINA. The value indices of the DINO and DINA models were very close to each other but larger than those of the G-DINA and LLM. The model fit was also investigated at the item level, and the results revealed that model selection should be performed at the item level rather than the test level, and most of the specific models might perform well for the test. The findings of this study suggested that the relationships among the attributes of grammar and vocabulary are not 'either-or' compensatory or non-compensatory but a combination of both. (As Provided).
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Begutachtung	Peer reviewed
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01