Predicting Dropout Using Student- and School-Level Factors: An Ecological Perspective

Autor/inn/en	Wood, Laura; Kiperman, Sarah; Esch, Rachel C.; Leroux, Audrey J.; Truscott, Stephen D.
Titel	Predicting Dropout Using Student- and School-Level Factors: An Ecological Perspective
Quelle	In: School Psychology Quarterly, 32 (2017) 1, S.35-49 (15 Seiten) PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1045-3830
DOI	10.1037/spq0000152
Schlagwörter	High School Students; Predictor Variables; Dropouts; Potential Dropouts; Ecological Factors; Hierarchical Linear Modeling; Dropout Prevention; Longitudinal Studies; Academic Achievement; School Holding Power; Gender Differences; Family Income; Socioeconomic Status; Extracurricular Activities; School Size; Race; Ethnicity; Special Education; Citizenship; English; Native Language; School Location; Probability; Statistical Analysis + Suchen Sie Ihr Suchwort? High school; High schools; Student; Students; Oberschule; Schüler; Schülerin; Studentin; Prädiktor; Drop-out; Drop-outs; Dropout; Early leavers; Schulversagen; Ökologischer Ansatz; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung; Schulleistung; Geschlechterkonflikt; Familieneinkommen; Socio-economic status; Sozioökonomischer Status; Außerunterrichtliche Aktivität; Rasse; Abstammung; Ethnizität; Special needs education; Sonderpädagogik; Sonderschulwesen; Staatsbürgerschaft; English language; Englisch; Schulgelände; Wahrscheinlichkeitsrechnung; Wahrscheinlichkeitstheorie; Statistische Analyse
Abstract	High school dropout has been associated with negative outcomes, including increased rates of unemployment, incarceration, and mortality. Dropout rates vary significantly depending on individual and environmental factors. The purpose of our study was to use an ecological perspective to concurrently explore student- and school-level predictors associated with dropout for the purpose of better understanding how to prevent it. We used the Education Longitudinal Study of 2002 dataset. Participants included 14,106 sophomores across 684 public and private schools. We identified variables of interest based on previous research on dropout and implemented hierarchical generalized linear modeling. In the final model, significant student-level predictors included academic achievement, retention, sex, family socioeconomic status (SES), and extracurricular involvement. Significant school-level predictors included school SES and school size. Race/ethnicity, special education status, born in the United States, English as first language, school urbanicity, and school region did not significantly predict dropout after controlling for the aforementioned predictors. Implications for prevention and intervention efforts within a multitiered intervention model are discussed. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01