A Knowledge-Driven Model to Personalize E-Learning

Autor/inn/en	Teo, Chao Boon; Gay, Robert Kheng Leng
Titel	A Knowledge-Driven Model to Personalize E-Learning
Quelle	In: Journal on Educational Resources in Computing, 6 (2006) 1, Artikel 3 PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1531-4278
DOI	10.1145/1217862.1217865
Schlagwörter	Electronic Learning; Information Processing; Models; Educational Technology; Educational Improvement; Program Implementation + Suchen Sie Ihr Suchwort? Informationsverarbeitung; Analogiemodell; Unterrichtsmedien; Teaching improvement; Unterrichtsentwicklung
Abstract	This article highlights basic issues that have hindered e-learning systems from becoming the revolutionary force it could be for education. While current systems aim to foster significant improvements in learning, this article argues that most systems are still limited to just being online repositories. This and the lack of learning personalization has become a topic for research. A knowledge-driven model to personalize e-learning is proposed in this article. A novel methodology for eliciting and personalizing tacit knowledge is presented. We focus on describing the complex information processing in terms of knowledge, rather than the details of its implementation. (As Provided).
Anmerkungen	Association for Computing Machinery. 2 Penn Plaza Suite 701, New York, NY 10121. Tel: 800-342-6626; Tel: 212-626-0500; Fax: 212-944-1318; e-mail: acmhelp@acm.org; Web site: http://www.acm.org
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2017/4/10