Using Data Mining Methods for Research in Co-Operative Education

Autor/inn/en	Chopra, Shivangi; Golab, Lukasz; Pretti, T. Judene; Toulis, Andrew
Titel	Using Data Mining Methods for Research in Co-Operative Education
Quelle	In: International Journal of Work-Integrated Learning, 19 (2018) 3, S.297-310 (14 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	2538-1032
Schlagwörter	Information Retrieval; Data Analysis; Research Methodology; Educational Research; Cooperative Education; Graphs; Work Experience Programs; Occupational Information + Suchen Sie Ihr Suchwort? Auswertung; Research method; Forschungsmethode; Bildungsforschung; Pädagogische Forschung; Kooperativer Unterricht; Grafische Darstellung; Berufsinformation
Abstract	This paper describes two classes of advanced data mining methods that can obtain actionable insight from cooperative education data: text mining of job descriptions and graph mining of job interview data. While these methods are not new in general, they have not been widely used in co-operative education research. A technical overview of each method is provided, followed by a case study using real data from a large North American university. The case study illustrates that the proposed methods can enable students, employers and institutions to make better data-driven decisions. For example, text mining of job descriptions can reveal sought-after skills while graph mining of interview relationships can characterize the extent of competition for jobs. (As Provided).
Anmerkungen	New Zealand Association for Cooperative Education. University of Waikato, Private Bag 3105, Hamilton 3240, New Zealand. Tel: +64-7-838-4892; e-mail: editor@ijwil.org; Web site: https://www.ijwil.org/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01