Evaluating Equating in Progress Monitoring Measures Using Multilevel Modeling

Autor/inn/en	Albano, Anthony D.; Christ, Theodore J.; Cai, Liuhan
Titel	Evaluating Equating in Progress Monitoring Measures Using Multilevel Modeling
Quelle	In: Measurement: Interdisciplinary Research and Perspectives, 16 (2018) 3, S.168-180 (13 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1536-6367
DOI	10.1080/15366367.2018.1483663
Schlagwörter	Progress Monitoring; Hierarchical Linear Modeling; Equated Scores; Raw Scores; Longitudinal Studies; Statistical Analysis; Grade 1; Elementary School Students + Suchen Sie Ihr Suchwort? Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Statistische Analyse; School year 01; 1. Schuljahr; Schuljahr 01
Abstract	Traditional psychometric methods have primarily been developed and applied in the context of high-stakes, large-scale testing. However, these methods are increasingly being used with classroom assessments, including progress monitoring measures where numerous test forms are administered over the course of an academic year. This article provides an overview of progress monitoring and describes a new method for evaluating equating in longitudinal contexts, one that is based on a comparison of results from multilevel models of raw and equated scores. The method is demonstrated using scores from 15 reading fluency tasks administered to 231 students in a longitudinal assessment system. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01