The Data Revolution Comes to Higher Education: Identifying Students at Risk of Dropout in Chile

Autor/inn/en	Von Hippel, Paul T.; Hofflinger, Alvaro
Titel	The Data Revolution Comes to Higher Education: Identifying Students at Risk of Dropout in Chile
Quelle	In: Journal of Higher Education Policy and Management, 43 (2021) 1, S.2-23 (22 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Von Hippel, Paul T.) ORCID (Hofflinger, Alvaro)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-080X
DOI	10.1080/1360080X.2020.1739800
Schlagwörter	At Risk Students; Dropouts; Intervention; Foreign Countries; College Attendance; Academic Persistence; Graduation Rate; Universities; College Students; Prevention; Program Effectiveness; Academic Achievement; Grades (Scholastic); Predictor Variables; School Holding Power; Student Financial Aid; Majors (Students); Student Attitudes; Institutional Characteristics; Chile + Suchen Sie Ihr Suchwort? Drop-out; Drop-outs; Dropout; Early leavers; Schulversagen; Ausland; College; Colleges; Attendance; Hochschule; Fachhochschule; Anwesenheit; University; Universität; Collegestudent; Prävention; Vorbeugung; Schulleistung; Notenspiegel; Prädiktor; Finanzielle Beihilfe; Studienfinanzierung; Studienförderung; Schülerverhalten
Abstract	Enrolment in higher education has risen dramatically in Latin America, especially in Chile. Yet graduation and persistence rates remain low. One way to improve graduation and persistence is to use data and analytics to identify students at risk of dropout, target interventions, and evaluate interventions' effectiveness at improving student success. We illustrate the potential of this approach using data from eight Chilean universities. Results show that data available at matriculation are only weakly predictive of persistence, while prediction improves dramatically once data on university grades become available. Some predictors of persistence are under policy control. Financial aid predicts higher persistence, and being denied a first-choice major predicts lower persistence. Student success programmes are ineffective at some universities; they are more effective at others, but when effective they often fail to target the highest risk students. Universities should use data regularly and systematically to identify high-risk students, target them with interventions, and evaluate those interventions' effectiveness. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01