Receiver Operating Characteristic (ROC) Area under the Curve (AUC): A Diagnostic Measure for Evaluating the Accuracy of Predictors of Education Outcomes

Autor/inn/en	Bowers, Alex J.; Zhou, Xiaoliang
Titel	Receiver Operating Characteristic (ROC) Area under the Curve (AUC): A Diagnostic Measure for Evaluating the Accuracy of Predictors of Education Outcomes
Quelle	In: Journal of Education for Students Placed at Risk, 24 (2019) 1, S.20-46 (28 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1082-4669
DOI	10.1080/10824669.2018.1523734
Schlagwörter	Accuracy; Predictor Variables; Outcomes of Education; Educational Diagnosis; Longitudinal Studies; High School Students; Dropouts; Enrollment; Higher Education; STEM Education; Occupations; Theories; Graphs + Suchen Sie Ihr Suchwort? Prädiktor; Lernleistung; Schulerfolg; Pedagogical diagnostics; Pädagogische Diagnostik; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Drop-out; Drop-outs; Dropout; Early leavers; Schulversagen; Einschulung; Hochschulbildung; Hochschulsystem; Hochschulwesen; STEM; Beruf; Berufsumfeld; Theory; Theorie; Grafische Darstellung
Abstract	Early Warning Systems (EWS) and Early Warning Indictors (EWI) have recently emerged as an attractive domain for states and school districts interested in predicting student outcomes using data that schools already collect with the intention to better time and tailor interventions. However, current diagnostic measures used across the domain do not consider the dual issues of sensitivity and specificity of predictors, key components for considering accuracy. We apply signal detection theory using Receiver Operating Characteristic (ROC) Area Under the Curve (AUC) analysis adapted from the engineering and medical domains, and using the pROC package in R. Using nationally generalizable data from the Education Longitudinal Study of 2002 (ELS:2002) we provide examples of applying ROC accuracy analysis to a variety of predictors of student outcomes, such as dropping out of high school, college enrollment, and postsecondary STEM degrees and careers. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01