Big(ger) Data as Better Data in Open Distance Learning

Autor/inn/en	Prinsloo, Paul; Archer, Elizabeth; Barnes, Glen; Chetty, Yuraisha; van Zyl, Dion
Titel	Big(ger) Data as Better Data in Open Distance Learning
Quelle	In: International Review of Research in Open and Distributed Learning, 16 (2015) 1, S.284-306 (23 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1492-3831
Schlagwörter	Foreign Countries; Distance Education; Open Universities; Online Courses; Electronic Learning; Case Studies; College Students; Success; Academic Achievement; Data Analysis; Learning Processes; Decision Making; College Admission; Learning Activities; Academic Persistence; Graduation; Employment; Information Systems; South Africa + Suchen Sie Ihr Suchwort? Ausland; Distance study; Distance learning; Fernunterricht; Offene Universität; Online course; Online-Kurs; Case study; Fallstudie; Case Study; Collegestudent; Erfolg; Schulleistung; Auswertung; Learning process; Lernprozess; Decision-making; Entscheidungsfindung; Hochschulzugang; Hochschulzulassung; Zulassung; Lernaktivität; Abschluss; Graduierung; Dienstverhältnis; Südafrika; Süd-Afrika; Republik Südafrika; Südafrikanische Republik
Abstract	In the context of the hype, promise and perils of Big Data and the currently dominant paradigm of data-driven decision-making, it is important to critically engage with the potential of Big Data for higher education. We do not question the potential of Big Data, but we do raise a number of issues, and present a number of theses to be seriously considered in realising this potential. The University of South Africa (Unisa) is one of the mega ODL institutions in the world with more than 360,000 students and a range of courses and programmes. Unisa already has access to a staggering amount of student data, hosted in disparate sources, and governed by different processes. As the university moves to mainstreaming online learning, the amount of and need for analyses of data are increasing, raising important questions regarding our assumptions, understanding, data sources, systems and processes. This article presents a descriptive case study of the current state of student data at Unisa, as well as explores the impact of existing data sources and analytic approaches. From the analysis it is clear that in order for big(ger) data to be better data, a number of issues need to be addressed. The article concludes by presenting a number of theses that should form the basis for the imperative to optimise the harvesting, analysis and use of student data. (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