Artificial Intelligence in Education: Global Trends, Clusters, and Perspectives

Integrating artificial intelligence (AI) in education has become a powerful force in transforming teaching practices and fostering personalized learning experiences.This study utilizes bibliometric analysis to investigate global trends and thematic clusters in AI in education, examining 11,779 publications spanning from 2010 to 2024.Using multiple correspondence analysis (MCA), the study identifies six main clusters, including adaptive learning technologies, ethical considerations, intelligent tutoring systems, future skills development, digital teaching tools, and interdisciplinary challenges.The findings underscore the prominence of adaptive and personalized learning systems as crucial areas of research focus, while also highlighting a growing concern regarding ethical issues such as algorithmic bias and accessibility.Additionally, emerging themes like the role of digital teachers and the societal impact of AI-driven education offer valuable insights into the progression of the field.

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Publication Details

Journal
Annals of Dunarea de Jos University of Galati Fascicle I Economics and Applied Informatics
Published
2024-12-31
DOI
https://doi.org/10.35219/eai15840409452
Primary Topic
Online Learning and Analytics
Type
article
Field-Weighted Citation Impact
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article

Artificial Intelligence in Education: Global Trends, Clusters, and Perspectives

Corina Sbughea, Cristina Barbu
Annals of Dunarea de Jos University of Galati Fascicle I Economics and Applied Informatics
Online Learning and Analytics
article

Artificial Intelligence in Education: Global Trends, Clusters, and Perspectives

Corina Sbughea, Cristina Barbu
article en

Abstract

Integrating artificial intelligence (AI) in education has become a powerful force in transforming teaching practices and fostering personalized learning experiences.This study utilizes bibliometric analysis to investigate global trends and thematic clusters in AI in education, examining 11,779 publications spanning from 2010 to 2024.Using multiple correspondence analysis (MCA), the study identifies six main clusters, including adaptive learning technologies, ethical considerations, intelligent tutoring systems, future skills development, digital teaching tools, and interdisciplinary challenges.The findings underscore the prominence of adaptive and personalized learning systems as crucial areas of research focus, while also highlighting a growing concern regarding ethical issues such as algorithmic bias and accessibility.Additionally, emerging themes like the role of digital teachers and the societal impact of AI-driven education offer valuable insights into the progression of the field.

Annals of Dunarea de Jos University of Galati Fascicle I Economics and Applied InformaticsVol. 30(3)
Openalex Percentile: Top 72%
Online Learning and Analytics
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