Evaluating CAT-Adjusted Approaches for Suspected Item Parameter Drift Detection

Autor/inn/en	Cappaert, Kevin J.; Wen, Yao; Chang, Yu-Feng
Titel	Evaluating CAT-Adjusted Approaches for Suspected Item Parameter Drift Detection
Quelle	In: Measurement: Interdisciplinary Research and Perspectives, 16 (2018) 4, S.226-238 (13 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1536-6367
DOI	10.1080/15366367.2018.1511199
Schlagwörter	Adaptive Testing; Computer Assisted Testing; Test Items; Identification; Methods; Statistical Analysis; Sampling; Statistical Inference + Suchen Sie Ihr Suchwort? Test content; Testaufgabe; Identifikation; Identifizierung; Method; Methode; Statistische Analyse; Inferential statistics; Schließende Statistik
Abstract	Events such as curriculum changes or practice effects can lead to item parameter drift (IPD) in computer adaptive testing (CAT). The current investigation introduced a point- and weight-adjusted D[superscript 2] method for IPD detection for use in a CAT environment when items are suspected of drifting across test administrations. Type I error and power rates of the proposed method were compared to a more traditional, non-adjusted D[superscript 2] method and two recently suggested methods for use in a CAT environment: pseudo-count robust z and pseudo-count D[superscript 2] methods. Though all CAT-adjusted IPD detection methods compared resulted in high power, the pseudo-count D[superscript 2] method was found to have the highest power rates, with the proposed D[superscript 2] method a close second. All four methods were found to have acceptable type I error rates. (As Provided).
Anmerkungen	Routledge. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01