A Latent Class Signal Detection Model for Rater Scoring with Ordered Perceptual Distributions

Autor/inn/en	DeCarlo, Lawrence T.; Zhou, Xiaoliang
Titel	A Latent Class Signal Detection Model for Rater Scoring with Ordered Perceptual Distributions
Quelle	In: Journal of Educational Measurement, 58 (2021) 1, S.31-53 (23 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0022-0655
DOI	10.1111/jedm.12265
Schlagwörter	Scoring; Models; Bias; Perception; Accuracy; Language Tests + Suchen Sie Ihr Suchwort? Bewertung; Analogiemodell; Wahrnehmung; Language test; Sprachtest
Abstract	In signal detection rater models for constructed response (CR) scoring, it is assumed that raters discriminate equally well between different latent classes defined by the scoring rubric. An extended model that relaxes this assumption is introduced; the model recognizes that a rater may not discriminate equally well between some of the scoring classes. The extension recognizes a different type of rater effect and is shown to offer useful tests and diagnostic plots of the equal discrimination assumption, along with ways to assess rater accuracy and various rater effects. The approach is illustrated with an application to a large-scale language test. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01