Technology for Mining the Big Data of MOOCs

Autor/inn/en	O'Reilly, Una-May; Veeramachaneni, Kalyan
Titel	Technology for Mining the Big Data of MOOCs
Quelle	In: Research & Practice in Assessment, 9 (2014), S.29-37 (9 Seiten) PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2161-4210
Schlagwörter	Data; Technology Uses in Education; Online Courses; Open Education; Standard Setting; Data Analysis; Data Processing; Open Source Technology; Visualization; Information Management; Computer System Design; Technological Advancement; Program Descriptions; Performance Technology; Higher Education + Suchen Sie Ihr Suchwort? Daten; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Online course; Online-Kurs; Offene Erziehung; Offener Unterricht; Standardisierung; Auswertung; Datenverarbeitung; Visualisation; Visualisierung; Procurement of information; Informationsbeschaffung; Technological development; Technologische Entwicklung; Hochschulbildung; Hochschulsystem; Hochschulwesen
Abstract	Because MOOCs bring big data to the forefront, they confront learning science with technology challenges. We describe an agenda for developing technology that enables MOOC analytics. Such an agenda needs to efficiently address the detailed, low level, high volume nature of MOOC data. It also needs to help exploit the data's capacity to reveal, in detail, how students behave and how learning takes place. We chart an agenda that starts with data standardization. It identifies crowd sourcing as a means to speed up data analysis of forum data or predictive analytics of student behavior. It also points to open source platforms that allow software to be shared and visualization analytics to be discussed. (As Provided).
Anmerkungen	Virginia Assessment Group. Tel: 504-314-2898; Fax: 504-247-1232; e-mail: editor@rpajournal.com; Web site: http://www.rpajournal.com/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01