Adaptive item selection under matroid constraints.

Autor/inn/en	Bengs, Daniel; Brefeld, Ulf; Kröhne, Ulf
Titel	Adaptive item selection under matroid constraints.
Quelle	In: Journal of computerized adaptive testing, 6 (2018) 2, S. 15-36 PDF als Volltext (1); PDF als Volltext (2) Link als defekt meldenVerfügbarkeit
Sprache	englisch
Dokumenttyp	online; Zeitschriftenaufsatz
Schlagwörter	Testkonstruktion; Adaptives Testen; Algorithmus; Testkonstruktion; Computerunterstütztes Verfahren; Item; Algorithmus; Computerunterstütztes Verfahren; Messverfahren; Technologiebasiertes Testen; Item
Abstract	The shadow testing approach (STA; van der Linden & Reese, 1998) is considered the state of the art in constrained item selection for computerized adaptive tests. The present paper shows that certain types of constraints (e.g., bounds on categorical item attributes) induce a matroid on the item bank. This observation is used to devise item selection algorithms that are based on matroid optimization and lead to optimal tests, as the STA does. In particular, a single matroid constraint can be treated optimally by an efficient greedy algorithm that selects the most informative item preserving the integrity of the constraints. A simulation study shows that for applicable constraints, the optimal algorithms realize a decrease in standard error (SE) corresponding to a reduction in test length of up to 10% compared to the maximum priority index (Cheng & Chang, 2009) and up to 30% compared to Kingsbury and Zara's (1991) constrained computerized adaptive testing.
Erfasst von	DIPF \| Leibniz-Institut für Bildungsforschung und Bildungsinformation, Frankfurt am Main
Update	2023/1