Data-Driven Learning of Q-Matrix

Autor/inn/en	Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang
Titel	Data-Driven Learning of Q-Matrix
Quelle	In: Applied Psychological Measurement, 36 (2012) 7, S.548-564 (17 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621612456591
Schlagwörter	Matrices; Computation; Statistical Analysis; Models; Classification + Suchen Sie Ihr Suchwort? Matrizenrechnung; Statistische Analyse; Analogiemodell; Classification system; Klassifikation; Klassifikationssystem
Abstract	The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known "Q"-matrix, which specifies the item-attribute relationships. This article proposes a data-driven approach to identification of the "Q"-matrix and estimation of related model parameters. A key ingredient is a flexible "T"-matrix that relates the "Q"-matrix to response patterns. The flexibility of the "T"-matrix allows the construction of a natural criterion function as well as a computationally amenable algorithm. Simulations results are presented to demonstrate usefulness and applicability of the proposed method. Extension to handling of the "Q"-matrix with partial information is presented. The proposed method also provides a platform on which important statistical issues, such as hypothesis testing and model selection, may be formally addressed. (Contains 4 tables and 2 figures.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10