A topic modeling-based analysis of research trends in artificial intelligence within the field of early childhood education

This study analyzes current research trends related to Artificial Intelligence (AI) in early childhood education using topic modeling. The primary objective is to identify core thematic domains and propose future directions for the pedagogical integration of AI technologies. Using Latent Dirichlet Allocation (LDA), this study analyzed scholarly publications related to AI in early childhood education, published between 2017 and 2024, thereby identifying key research themes and tracing their development over time. The analysis yielded five prominent topics: (1) AI-integrated education for young children, (2) development of AI-based educational content reflecting parental expectations, (3) implementation of AI speakers in instructional settings, (4) perceptions and experiences of pre-service and in-service early childhood educators concerning AI integration, and (5) development of AI-related competencies among educators. These findings highlight the increasing recognition of Artificial Intelligence (AI) as a transformative agent in early childhood education—contributing to the enhancement of children's creativity, the advancement of family involvement, the professional development of educators, and the articulation of ethical and policy considerations. By transcending a solely technical framework, this study provides a comprehensive perspective on the conceptual foundations and practical applications of AI within the early childhood education landscape.