Building Bridges to the Future of Learning: Exploring Artificial Intelligence Research Using R-Studio Assisted Bibliometrics

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Bibliographic Details
Title: Building Bridges to the Future of Learning: Exploring Artificial Intelligence Research Using R-Studio Assisted Bibliometrics
Language: English
Authors: Sainee Tamphu, Imam Suyitno, Gatut Susanto, Nia Budiana, M. Rais Salim, Nurhikmah, Wilda Purnawati
Source: Cogent Education. 2024 11(1).
Availability: Cogent OA. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 18
Publication Date: 2024
Document Type: Journal Articles
Reports - Research
Information Analyses
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Research, Educational Change, Transformative Learning, Bibliometrics, Authors, Publications, Citation Analysis, Networks, Educational Trends, Foreign Countries, Learning Processes, Citations (References)
Geographic Terms: United States, China, United Kingdom
DOI: 10.1080/2331186X.2024.2417623
ISSN: 2331-186X
Abstract: Artificial intelligence (AI) has transformed education by enhancing personalization and learning efficiency. However, the application of AI in addressing its challenges and potential remains suboptimal. This study aims to provide a bibliometric analysis of AI in Education research, focusing on publications from 2017 to 2023 sourced from Scopus-indexed journals. Using R-Studio-assisted bibliometrics, the study uses descriptive analysis and co-authorship to explore publication trends, citation patterns, affiliations, institutions, and collaboration networks. Analyzing 161 documents, the study identifies key trends and growth areas of AI-based learning. The findings of this study indicate an increase in AI in learning research publications, especially in 2022 and 2023. The findings also show that developed countries such as the United States, China, and the United Kingdom dominate AI research in education. Their contributions include technology development and international research collaboration. Then, this study offers insight into the global research landscape of AI in education by highlighting areas that require further exploration to optimize the function and role of AI in enhancing the learning process. In addition, challenges regarding the impact of AI on cognitive, affective, and psychomotor domains need to be identified in further research to ensure effective integration in the context of educational sustainability.
Abstractor: As Provided
Entry Date: 2024
Accession Number: EJ1453112
Database: ERIC
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