Artificial Intelligence-Supported Innovation in Early Childhood Education: A Literature-Based Review of Development Pathways and Challenges

Abstract

Artificial intelligence (AI) has increasingly influenced early childhood education by reshaping curriculum design, learning environments, assessment practices, and teacher professional development. However, existing studies often examine technological applications, learning outcomes, or ethical concerns separately, providing limited understanding of how these dimensions interact within a broader educational transformation process. This study aims to identify the major research themes, challenges, and future development pathways of AI-supported early childhood education through a literature-based review. Twenty representative studies published between 2008 and 2026 were analyzed using thematic synthesis to examine recurring patterns and relationships among existing research findings. The results reveal four interconnected dimensions: AI-supported learning and curriculum innovation, teacher readiness and AI literacy, personalized learning and assessment, and ethical governance. Based on these findings, this review proposes a child-centered conceptual framework integrating technological innovation, pedagogical transformation, and ethical responsibility. The framework provides theoretical insights and practical guidance for promoting sustainable and developmentally appropriate AI implementation in early childhood education.