Using Predictive Analytics to Target and Improve First Year Student Attrition

Autor/inn/en	Seidel, Ewa; Kutieleh, Salah
Titel	Using Predictive Analytics to Target and Improve First Year Student Attrition
Quelle	In: Australian Journal of Education, 61 (2017) 2, S.200-218 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0004-9441
DOI	10.1177/0004944117712310
Schlagwörter	Predictor Variables; Data Analysis; Student Behavior; College Freshmen; Student Attrition; Dropout Prevention; At Risk Students; Academic Achievement; Academic Persistence; Student Satisfaction; Peer Relationship; Social Support Groups; Academic Support Services; Program Effectiveness; Student Personnel Services; Foreign Countries; Australia + Suchen Sie Ihr Suchwort? Prädiktor; Auswertung; Student behaviour; Schülerverhalten; Studienanfänger; Schülerbeurlaubung; Schulleistung; Peer-Beziehungen; Social support; Soziale Unterstützung; Ausland; Australien
Abstract	This article reports on the development and implementation of the Student Success Program, a strategic, University-wide, consistent approach to increasing the success and retention of first year students, during 2014. To this end, a centrally coordinated process integrated historic student, application, enrolment, academic performance and learning management data in a data warehouse. These data were used to build chi-squared automatic iterative detection (CHAID) decision tree models aimed at predicting each student's risk of attrition. Predictions were made multiple times per year before peak attrition time points to allow for changes in student behaviour and availability of new data. An intervention using peer-to-peer phone-call communication targeted students with the largest predicted risks, to offer support, foster retention and enable a successful outcome in higher education. The accuracy of the chi-squared automatic iterative detection models benefited most from the inclusion of data representing first year student study behaviours. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01