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Autor/inn/enKucirkova, Natalia; Gray, Sandra Leaton
TitelBeyond Personalization: Embracing Democratic Learning within Artificially Intelligent Systems
QuelleIn: Educational Theory, 73 (2023) 4, S.469-489 (21 Seiten)Infoseite zur Zeitschrift
PDF als Volltext Verfügbarkeit 
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN0013-2004
DOI10.1111/edth.12590
SchlagwörterDemocratic Values; Citizenship; Artificial Intelligence; Individualized Instruction; Children; Self Concept; Technology Uses in Education; Educational Technology
AbstractThis essay explains how, from the theoretical perspective of Basil Bernstein's three "conditions for democracy," the current pedagogy of artificially intelligent personalized learning seems inadequate. Building on Bernstein's comprehensive work and more recent research concerned with personalized education, Natalia Kucirkova and Sandra Leaton Gray suggest three principles for advancing personalized education and artificial intelligence (AI). They argue that if AI is to reach its full potential in terms of promoting children's identity as democratic citizens, its pedagogy must go beyond monitoring the technological progression of personalized provision of knowledge. It needs to pay more careful attention to the democratic impact of data-driven systems. Kucirkova and Leaton Gray propose a framework to distinguish the value of personalized learning in relation to pluralization and to guide educational researchers and practitioners in its application to socially just classrooms. (As Provided).
AnmerkungenWiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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