Application of Bi-Factor MIRT and Higher-Order CDM Models to an In-House EFL Listening Test for Diagnostic Purposes

Autor/inn/en	Min, Shangchao; Cai, Hongwen; He, Lianzhen
Titel	Application of Bi-Factor MIRT and Higher-Order CDM Models to an In-House EFL Listening Test for Diagnostic Purposes
Quelle	In: Language Assessment Quarterly, 19 (2022) 2, S.189-213 (25 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1543-4303
DOI	10.1080/15434303.2021.1980571
Schlagwörter	Listening Comprehension Tests; English (Second Language); Second Language Learning; Foreign Countries; Language Tests; Test Items; Item Response Theory; Diagnostic Tests; Specialists; Comparative Analysis; Models; Goodness of Fit; Classification; College Faculty; Second Language Instruction; College Students; Language Proficiency; China + Suchen Sie Ihr Suchwort? Hörverstehensübung; English as second language; English; Second Language; Englisch als Zweitsprache; Zweitsprachenerwerb; Ausland; Language test; Sprachtest; Test content; Testaufgabe; Item-Response-Theorie; Diagnostic test; Diagnostischer Test; Analogiemodell; Classification system; Klassifikation; Klassifikationssystem; Fakultät; Fremdsprachenunterricht; Collegestudent; Language skill; Language skills; Sprachkompetenz
Abstract	The present study examined the performance of the bi-factor multidimensional item response theory (MIRT) model and higher-order (HO) cognitive diagnostic models (CDM) in providing diagnostic information and general ability estimation simultaneously in a listening test. The data used were 1,611 examinees' item-level responses to an in-house EFL listening test in China and five content experts' item-attribute coding results of the test form. The bi-factor MIRT model was compared with five CDMs with and without a higher-order structure in terms of model fit, attribute classification and general ability estimation. The results showed that the bi-factor MIRT model provided the best model-data fit, followed by the HO-G-DINA model, the saturated G-DINA model, and other reduced CDMs. The HO-G-DINA model produced attribute classification results more similar to the G-DINA model, whereas the bi-factor MIRT model offered better results in discriminating examinees' general listening ability. The findings of this study highlighted the feasibility of using the bi-factor MIRT model as an attractive alternative for diagnostic assessment, especially in language assessment where attributes are assumed to be continuous. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01