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Autor/inn/enKumar, Vivekanandan; Ally, Mohamed; Tsinakos, Avgoustos; Norman, Helmi
TitelCognification in Learning, Teaching, and Training
QuelleIn: Canadian Journal of Learning and Technology, 48 (2022) 4, (17 Seiten)
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ZusatzinformationORCID (Kumar, Vivekanandan)
ORCID (Tsinakos, Avgoustos)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1499-6677
SchlagwörterElectronic Learning; Cognitive Processes; Artificial Intelligence; Educational Technology; Blended Learning; Data Analysis; Educational Change; Educational Trends; Models; Democracy; Lifelong Learning; Ethics; Decision Making
AbstractOver the past decade, opportunities for online learning have dramatically increased. Learners around the world now have digital access to a wide array of corporate trainings, certifications, comprehensive academic degree programs, and other educational and training options. Some organizations are blending traditional instruction methods with online technologies. Blended learning generates large volumes of data about both the content (quality and usage) and the learners (study habits and learning outcomes). Correspondingly, the need to properly process voluminous, continuous, and often disparate data has prompted the advent of cognification. Cognification techniques design complex data analytic models that allow natural intelligence to engage artificial smartness in ways that can enhance the learning experience. Cognification is the approach to make something increasingly, ethically, and regulatably smarter. This article highlights how emerging trends in cognification could disrupt online education. (As Provided).
AnmerkungenCanadian Network for Innovation in Education. 260 Dalhousie Street Suite 204, Ottawa, ON K1N 7E4, Canada. Tel: 613-241-0018; Fax: 613-241-0019; e-mail: cnie-rcie@cnie-rcie.ca; Web site: http://www.cjlt.ca
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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