Abstract
Generative artificial intelligence (Gen AI) has emerged as a topic of interest in education research. However, its applications in early childhood education (ECE) remain underexplored. This systematic review synthesizes empirical evidence on Gen AI in ECE, organizing findings by stakeholder perspective: young children, families, and teachers. Following PRISMA 2020 guidelines, 29 studies published between December 2022 and July 2025 were identified from eight databases. Results show that publications increased sharply from one in 2023 to 16 in 2024, with research concentrated in the USA and China. Gen AI supports ECE through enhanced learning outcomes, personalized learning, increased engagement, parent support, and teacher efficiency. However, these benefits were consistently dependent on active adult mediation. Challenges include technical limitations, content quality issues, and accuracy concerns. The findings suggest that Gen AI is best positioned as a complement to human guidance rather than a replacement. Future research should employ longitudinal designs and expand geographic diversity.
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Zhang, Y., Binti Halili, S. H., & Zainuddin, Z. (2026). Applications of generative AI in early childhood education: A systematic review. Eurasia Journal of Mathematics, Science and Technology Education. Modestum LTD. https://doi.org/10.29333/ejmste/18068
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