Research on AI in K-12 education across Asia has experienced explosive growth since 2017, with China, Hong Kong, and South Korea leading publication output, while emerging trends focus on generative AI tools like ChatGPT and their applications in personalized learning and curriculum design.

Objective: The main goal of this study was to conduct a comprehensive bibliometric analysis of artificial intelligence applications in K-12 education (AIEdK-12) research across Asian countries from 1996 to 2025, examining publication trends, leading contributors, and emerging research themes to provide insights into the current landscape and future directions of this field.

Methods: The researchers employed a systematic bibliometric analysis using the Scopus database, retrieving 531 articles published between 1996 and January 2025. The study followed the PRISMA framework with four key phases: identification, screening, eligibility assessment, and final inclusion. Data collection involved comprehensive search strategies targeting AI-related terms combined with K-12 education keywords across all Asian countries. The analysis utilized multiple tools including Microsoft Excel, Bibliometrix R package, and VOSviewer for network visualization. The methodology encompassed both performance analysis (examining publication trends, sources, authors, countries, and institutions) and science mapping (generating visual representations of collaborations and keyword co-occurrences). Specific inclusion criteria focused on English-language journal articles authored by researchers affiliated with Asian institutions, while exclusion criteria eliminated conference papers, books, and non-journal publications.

Key Findings:

• Publication Growth: Research showed exponential growth from minimal activity (1996-2017) to peak production of 198 articles in 2024, with 90.96% of all publications emerging between 2020-2025.
• Geographic Distribution: China dominated with 180 publications (33.90%), followed by South Korea (67 publications) and Hong Kong (62 publications). East Asian countries accounted for 74.90% of research output.
• Institutional Leadership: The Chinese University of Hong Kong emerged as the most productive institution (60 articles), followed by South China Normal University (45 articles) and The University of Hong Kong (32 articles).
• Journal Impact: Education and Information Technologies led with 27 publications and 442 citations, followed by Computers and Education: Artificial Intelligence (13 publications, 425 citations).
• Author Influence: T.K.F. Chiu was the most productive author (16 publications), while C.S. Chai received the highest citations (1,158 total citations).
• Research Themes: Seven distinct clusters emerged from keyword analysis, including AI-driven learning outcomes, AI-enhanced language education, AI curriculum design, applications of AI tools, the role of AI in K-12 education, generative AI tools usage, and effects of AI-enhanced learning.

Implications: This research significantly contributes to understanding the AI in education landscape by providing the first comprehensive bibliometric analysis of AIEdK-12 in Asia. The findings reveal critical gaps in research distribution, with developing Asian countries significantly underrepresented compared to technologically advanced nations like China and South Korea. The study highlights the need for increased international collaboration and capacity-building initiatives to ensure equitable access to AI educational technologies. The identification of emerging themes, particularly around generative AI tools like ChatGPT, provides valuable guidance for future research directions and policy development. The research also underscores the importance of teacher professional development and curriculum design frameworks to effectively integrate AI technologies in K-12 educational settings.

Limitations: The study was limited to Scopus-indexed publications in English, potentially excluding important regional research published in local languages or non-indexed journals. The focus on Asian countries only may limit comparative insights with global trends. The exclusion of grey literature such as books and reports could have overlooked relevant research contributions. Additionally, the specific search query combinations and timing of data retrieval may have affected the comprehensiveness of the bibliometric analysis. The study also acknowledged potential language bias due to the English-only inclusion criteria.

Future Directions: The researchers recommend expanding data sources to include multilingual publications and additional databases like Web of Science for more comprehensive coverage. Future studies should explore comparative analyses between Asian and global AIEdK-12 research trends. There is a critical need for research focusing on developing countries and underrepresented regions in Asia to address current gaps. The study suggests investigating the long-term impact of AI tools on student learning outcomes and teacher practices. Additionally, research should examine ethical implications, equity issues, and the scalability of AI solutions across diverse educational contexts. The emergence of generative AI tools presents opportunities for studying their transformative potential in educational practices and curriculum development.

Title and Authors: "Research trends on artificial intelligence in K-12 education in Asia: a bibliometric analysis using the Scopus database (1996–2025)" by Irwanto Irwanto.

Published on: 2025

Published by: Discover Artificial Intelligence