Exploring Contributors, Collaborations, and Research Topics in Educational Technology: A Joint Analysis of Mainstream Conferences

Autor/inn/en	Chen, Xieling; Zou, Di; Xie, Haoran; Chen, Guanliang; Lin, Jionghao; Cheng, Gary
Titel	Exploring Contributors, Collaborations, and Research Topics in Educational Technology: A Joint Analysis of Mainstream Conferences
Quelle	In: Education and Information Technologies, 28 (2023) 2, S.1323-1358 (36 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Zou, Di)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1360-2357
DOI	10.1007/s10639-022-11209-y
Schlagwörter	Educational Technology; Conference Papers; Bibliometrics; Conferences (Gatherings); Artificial Intelligence; Learning Analytics; Information Retrieval; Intelligent Tutoring Systems; Educational Research; Technology Uses in Education + Suchen Sie Ihr Suchwort? Unterrichtsmedien; Konferenzmaterial; Bibliometrie; Künstliche Intelligenz; Intelligentes Tutorsystem; Bildungsforschung; Pädagogische Forschung; Technology enhanced learning; Technology aided learning; Technologieunterstütztes Lernen
Abstract	The diversity and advance of information, communication, and analytical technologies and their increasing adoption to assist instruction and learning give rise to various technology-driven conferences (e.g., artificial intelligence in education) in educational technology. Previous reviews on educational technology commonly focused on journal articles while seldom including mainstream conference papers which also contribute to an important part of scientific output in computer science and emerging disciplines like educational technology and are equally and even more important than articles in knowledge transmission. Hence, conference papers should also be included in bibliometric studies to produce a complete and precise picture of scientific production concerning educational technology. This study, therefore, uses bibliometrics and topic modeling to analyze papers from mainstream conferences, including Artificial Intelligence in Education, Learning Analytics and Knowledge, Educational Data Mining, Intelligent Tutoring System, and Learning at Scale, focusing on contributors, collaborations, and particularly research topics and topic evolutions to inform relevant stakeholders about educational technology's development and its future. Results indicate promising areas like affective computing and behavior mining for adaptive instruction, recommender systems in personalized learning recommendations, eye-tracking for cognitive process diagnosis, videos for feedback provision, and natural language processing in discourse analysis and language education. (As Provided).
Anmerkungen	Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01