Trends in Artificial Intelligence-Supported E-Learning: A Systematic Review and Co-Citation Network Analysis (1998-2019)

Autor/inn/en	Tang, Kai-Yu; Chang, Ching-Yi; Hwang, Gwo-Jen
Titel	Trends in Artificial Intelligence-Supported E-Learning: A Systematic Review and Co-Citation Network Analysis (1998-2019)
Quelle	In: Interactive Learning Environments, 31 (2023) 4, S.2134-2152 (19 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Tang, Kai-Yu) ORCID (Chang, Ching-Yi) ORCID (Hwang, Gwo-Jen)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1049-4820
DOI	10.1080/10494820.2021.1875001
Schlagwörter	Educational Trends; Trend Analysis; Artificial Intelligence; Technology Uses in Education; Electronic Learning; Citation Analysis; Network Analysis; Bibliometrics; Publications; Intelligent Tutoring Systems; Educational Research; Research Methodology + Suchen Sie Ihr Suchwort? Bildungsentwicklung; Trendanalyse; Künstliche Intelligenz; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen; Citation; Citations; Zitatenanalyse; Zitat; Netzplantechnik; Bibliometrie; Intelligentes Tutorsystem; Bildungsforschung; Pädagogische Forschung; Research method; Forschungsmethode
Abstract	Artificial intelligence (AI) has been widely explored across the world over the past decades. A particularly emerging topic is the application of AI in e-learning (AIeL) to improve the effectiveness of teaching and learning in precision education. This study aims to systematically review publication patterns for AIeL research with a focus on leading journals, countries, disciplines, and applications. In addition, a co-citation network analysis was conducted to explore the invisible relationships among the core papers of AIeL to reveal directions for future research. The analysis is based on a total of 86 core AIeL papers accompanied by 1149 citations in follow-up studies obtained from the Web of Science. It was found that a majority of AIeL studies focused on the development and applications of intelligent tutoring systems, followed by using AI to facilitate assessment and evaluation in e-learning contexts. For field researchers, the visualized network diagram serves as a map to explore the invisible relationships among the core AIeL research, providing a structural understanding of AI-supported research in e-learning contexts. A further investigation of the follow-up studies behind the highly co-cited links revealed the extended research directions from the AIeL mainstreams, such as adaptive learning-based evaluation environments. Implications are discussed. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01