Tren Global Penelitian Artificial Inteligence dalam Pembelajaran Matematika Anak Usia Dini: Studi Bibliometrik - Hajra Yansa; Aser Parera; Dite Umbara Alfansuri; Yuliana Olga Siba Sabon; Ratu Bulkis Ramli (PEDAGOGIC: Indonesian Journal of Science Education and Technology, 2026)
This study aims to analyze global research trends on Artificial Intelligence (AI) in early childhood mathematics learning through a bibliometric approach. The research data were obtained from the Scopus database within the 2016–2026 period. A total of 41 documents were analyzed using the Bibliometrix package in the R programming language. The analysis was conducted through performance analysis and science mapping, including publication trends, author and institutional productivity, research collaboration, and thematic analysis based on co-occurrence keywords and thematic maps. The results revealed that research on AI in early childhood mathematics learning has increased significantly, with an annual growth rate of 19.58%. The United States was identified as the country with the highest publication contribution, while University of Aveiro was the most productive institution. The dominant research themes included artificial intelligence, mathematics education, numeracy, machine learning, and early childhood education. The thematic map analysis indicated that mathematics education and AI-based learning systems have become rapidly developing core themes, while adaptive learning and machine learning still provide substantial opportunities for further research. This study confirms that AI has considerable potential to support early childhood mathematics learning, particularly in learning personalization and numeracy skill development This study is limited to Scopus-indexed publications and bibliometric analysis, therefore future research is recommended to explore empirical implementation and pedagogical efectiveness of AI in earlu childhood mathematics learning across diverse educational contexts