Progress, Challenges and Countermeasures of Adaptive Learning: A Systematic Review

Autor/inn/en	Li, Fengying; He, Yifeng; Xue, Qingshui
Titel	Progress, Challenges and Countermeasures of Adaptive Learning: A Systematic Review
Quelle	In: Educational Technology & Society, 24 (2021) 3, S.238-255 (18 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1436-4522
Schlagwörter	Educational Technology; Artificial Intelligence; Student Needs; Individualized Instruction; Student Centered Learning; Technology Uses in Education; Models; Educational Research; Foreign Countries; Barriers; Misconceptions; Information Security; Privacy; Cognitive Processes; Emotional Response; Research Needs; China + Suchen Sie Ihr Suchwort? Unterrichtsmedien; Künstliche Intelligenz; Individualisierender Unterricht; Group work; Student-entered learning; Student-centred learning; Student centred learning; Schülerorientierter Unterricht; Schülerzentrierter Unterricht; Gruppenarbeit; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Analogiemodell; Bildungsforschung; Pädagogische Forschung; Ausland; Missverständnis; Privatsphäre; Cognitive process; Kognitiver Prozess; Emotionales Verhalten; Forschungsbedarf
Abstract	With the deep application of artificial intelligence and big data in education, adaptive learning has become a new research hotspot in online education. Based on the systematic review of the connotation and research progress of adaptive learning, a new definition of adaptive learning is given. By literature analysis, this paper points out the challenges faced by adaptive learning research, such as the lack of cognition of brain and technology, the bottleneck of the model of emotion domain, the separation of education and technology, the security of data management and the risk of privacy leakage. These challenges can be summarized into two aspects: one is mechanical issues, the other is safety issues. Different from traditional research perspectives, the paper opens a new research window, and puts forward countermeasures from the perspectives of cognitive principles, zone of proximal development theory in technology, breakthrough in the emotional domain model, learning data management and privacy security. In view of the centralization of learning data management nowadays, the concept of code chain and the decentralized management mode based on code chain are proposed. Different from the traditional adaptive learning recommendation technology, a new adaptive learning pulling model is proposed. (As Provided).
Anmerkungen	International Forum of Educational Technology & Society. Available from: National Yunlin University of Science and Technology. No. 123, Section 3, Daxue Road, Douliu City, Yunlin County, Taiwan 64002. e-mail: journal.ets@gmail.com; Web site: https://www.j-ets.net/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01