A Binary Programming Approach to Automated Test Assembly for Cognitive Diagnosis Models

Autor/inn/en	Finkelman, Matthew D.; Kim, Wonsuk; Roussos, Louis; Verschoor, Angela
Titel	A Binary Programming Approach to Automated Test Assembly for Cognitive Diagnosis Models
Quelle	In: Applied Psychological Measurement, 34 (2010) 5, S.310-326 (17 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0146-6216
DOI	10.1177/0146621609344846
Schlagwörter	Automation; Test Construction; Programming; Models; Mathematics; Diagnostic Tests; Cognitive Tests; Item Banks; Computation; Comparative Analysis; Simulation + Suchen Sie Ihr Suchwort? Testaufbau; Programmierung; Analogiemodell; Mathematik; Diagnostic test; Diagnostischer Test; Kognitiver Fähigkeitstest; Simulation program; Simulationsprogramm
Abstract	Automated test assembly (ATA) has been an area of prolific psychometric research. Although ATA methodology is well developed for unidimensional models, its application alongside cognitive diagnosis models (CDMs) is a burgeoning topic. Two suggested procedures for combining ATA and CDMs are to maximize the cognitive diagnostic index and to use a genetic algorithm. Each of these procedures has a disadvantage: The cognitive diagnostic index cannot control attribute-level information and the genetic algorithm is computationally intensive. The goal of this article is to solve both problems by using binary programming, together with the item discrimination indexes of Henson et al., for performing ATA with CDMs. The three procedures are compared in simulation. Advantages and disadvantages of each are discussed. (Contains 1 note, 4 tables, and 1 figure.) (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10