Ethical Considerations in the Practical Application of the Unisa Socio-Critical Model of Student Success

Autor/in	Fynn, Angelo
Titel	Ethical Considerations in the Practical Application of the Unisa Socio-Critical Model of Student Success
Quelle	In: International Review of Research in Open and Distributed Learning, 17 (2016) 6, S.206-220 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1492-3831
Schlagwörter	Academic Achievement; Higher Education; Foreign Countries; Data Collection; Data Analysis; Open Education; Distance Education; Access to Education; Technology Uses in Education; Educational Technology; Access to Information; Educational Quality; Predictor Variables; South Africa + Suchen Sie Ihr Suchwort? Schulleistung; Hochschulbildung; Hochschulsystem; Hochschulwesen; Ausland; Data capture; Datensammlung; Auswertung; Offene Erziehung; Offener Unterricht; Distance study; Distance learning; Fernunterricht; Education; Access; Bildung; Zugang; Bildungszugang; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Unterrichtsmedien; Quality of education; Bildungsqualität; Prädiktor; Südafrika; Süd-Afrika; Republik Südafrika; Südafrikanische Republik
Abstract	The prediction and classification of student performance has always been a central concern within higher education institutions. It is therefore natural for higher education institutions to harvest and analyse student data to inform decisions on education provision in resource constrained South African environments. One of the drivers for the use of learning and academic analytics is the pressures for greater accountability in the areas of improved learning outcomes and student success. Added to this is the pressure on local government to produce well-educated populace to participate in the economy. The counter discourse in the field of big data cautions against algocracy where algorithms takeover the human process of democratic decision making. Proponents of this view argue that we run the risk of creating institutions that are beholden to algorithms predicting student success but are unsure of how they work and are too afraid to ignore their guidance. This paper aims to discuss the ethics, values, and moral arguments revolving the use of big data using a practical demonstration of learning analytics applied at Unisa. (As Provided).
Anmerkungen	Athabasca University. 1200, 10011 - 109 Street, Edmonton, AB T5J 3S8, Canada. Tel: 780-421-2536; Fax: 780-497-3416; e-mail: irrodl@athabascau.ca; Web site: http://www.irrodl.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01