Score Reporting for Examinees with Incomplete Data on Large-Scale Educational Assessments

Autor/in	Sinharay, Sandip
Titel	Score Reporting for Examinees with Incomplete Data on Large-Scale Educational Assessments
Quelle	In: Educational Measurement: Issues and Practice, 40 (2021) 1, S.79-91 (13 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Sinharay, Sandip)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0731-1745
DOI	10.1111/emip.12396
Schlagwörter	Data Analysis; Scores; Educational Assessment; Educational Testing; Computer Assisted Testing; Regression (Statistics) + Suchen Sie Ihr Suchwort? Auswertung; Education; assessment; Bewertungssystem; Regression; Regressionsanalyse
Abstract	Technical difficulties occasionally lead to missing item scores and hence to incomplete data on computerized tests. It is not straightforward to report scores to the examinees whose data are incomplete due to technical difficulties. Such reporting essentially involves imputation of missing scores. In this paper, a simulation study based on data from three educational tests is used to compare the performances of six approaches for imputation of missing scores. One of the approaches, based on data mining, is the first application of its kind to the problem of imputation of missing data. The approach based on data mining and a multiple imputation approach based on chained equations led to the most accurate imputation of missing scores, and hence to most accurate score reporting. A simple approach based on linear regression performed the next best overall. Several recommendations are made regarding the reporting of scores to examinees with incomplete data. (As Provided).
Anmerkungen	Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01