A Bibliometric Analysis of Artificial Intelligence for Multimedia in Education by Dimensions AI


  •  Potsirin Limpinan    
  •  Ampawan Yindeemak    
  •  Rungfa Pasmala    
  •  Manop Nammanee    
  •  Thada Jantakoon    

Abstract

This study presents a comprehensive bibliometric analysis of Artificial Intelligence (AI) research for Multimedia in Education from 2020 to 2024. Using the Dimensions AI database, VOSviewer software and Scimago Graphica, we examined 45 publications to identify key trends, influential contributors, and emerging directions in this rapidly evolving field. The analysis reveals a significant publication surge from 2020 to 2021, followed by stabilization in subsequent years. China is the dominant contributor, with 19 publications and 214 citations, highlighting its leadership in AI and educational technology research. Co-authorship network analysis shows a tightly interconnected research community lacking distinct clusters. The most cited papers focus on student engagement and specific AI applications in education, indicating the field's emphasis on practical implementations. Keyword analysis reveals a consistent focus on core concepts such as artificial intelligence, education, technology, and learning, with a recent shift towards more user-centered research. The study also identifies challenges in implementing AI for multimedia in education, including data privacy concerns, ethical considerations, and the need for educator training. These findings provide valuable insights for researchers, educators, and policymakers, highlighting the need to balance technological advancements with pedagogical needs and ethical considerations. Future research directions include investigating the long-term impact of AI-enhanced multimedia education, developing ethical frameworks, conducting cross-cultural studies, and enhancing AI's capability to provide personalized learning experiences through multimedia content.



This work is licensed under a Creative Commons Attribution 4.0 License.