Bibliometric review on teaching methods with artificial intelligence in education

Raúl Alberto Garcia Castro 1 * , Gilber Chura-Quispe 2, Jehovanni Fabricio Velarde Molina 2, Luis Alberto Espinoza Ramos 1, Catherine Alessandra Almonte Durand 1
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1 Universidad Nacional Jorge Basadre Grohmann, Tacna, PERU
2 Escuela de Posgrado Newman, Tacna, PERU
* Corresponding Author
Online Journal of Communication and Media Technologies, Volume 14, Issue 2, Article No: e202419. https://doi.org/10.30935/ojcmt/14367
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ABSTRACT

The purpose of this article is to carry out an analysis of the disclosures made on teaching methods applying artificial intelligence in the Scopus database. The bibliometric review method was used to analyze 349 scientific articles dating from 1978 to 2023. The analysis was carried out using Bibliometrix and VOSviewer software, and the results show that from 2021 onwards there will be a notable increase in publications, with Mobile Information Systems being the journal with the highest production. Among 65 countries identified, China is the country with the highest production and the most productive organization was the Ministry of Education of the People’s Republic of China. No single author stands out for his or her highest scientific output, given that the maximum number of articles published per author is two. However, among the most cited authors is Alimisis, D. and the most co-cited author is Wang, Y. In terms of co-authorship, there is little contribution between authors, while collaboration between countries, China together with Hong Kong, Japan, Malaysia, Mexico, South Korea, Taiwan, Thailand form the most collaborative conglomerate. Cooperation between institutions, the division of computer engineering and the National University of Singapore, show the strongest collaboration. The strongest keywords are “artificial intelligence”, followed by “teaching methods” and “machine learning” and the topics that will be trending from 2021 onwards are “machine learning”, “ChatGPT”, “deep learning”.
Keywords: teaching methods, artificial intelligence, bibliometrics, Scopus

CITATION

Garcia Castro, R. A., Chura-Quispe, G., Velarde Molina, J. F., Espinoza Ramos, L. A., & Almonte Durand, C. A. (2024). Bibliometric review on teaching methods with artificial intelligence in education. Online Journal of Communication and Media Technologies, 14(2), e202419. https://doi.org/10.30935/ojcmt/14367

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