Generative AI in preschool education: A systematic review with SWOT analysis

Document Type

Review

Publication Date

1-1-2026

Abstract

This systematic review analyzes 21 studies that met the inclusion criteria, retrieved from academic databases including Web of Science, Scopus, SpringerLink, and ACM Digital Library, to explore the integration of generative AI (GenAI) in preschool education. A systematic review methodology was applied, with specific inclusion and exclusion criteria to ensure the relevance and quality of the selected studies. Thematic analysis was employed to synthesize the findings. The results reveal that GenAI offers significant opportunities to enhance personalized learning, improve collaboration among educators, and foster educational equity. Notably, it supports dynamic and flexible teaching practices, aids in content creation, and promotes multi-role collaboration. However, challenges such as concerns over content reliability and age appropriateness, digital competence, and the potential reduction in children’s creativity must be addressed. Ethical issues, including data privacy risks and unequal access to technology, further complicate the widespread implementation of GenAI. Future research should focus on the long-term impact of GenAI on child development, examine its implementation in low-resource settings, and develop frameworks for responsible artificial intelligence use. By overcoming these challenges, GenAI has the potential to revolutionize preschool education, offering more engaging, equitable, and personalized learning experiences.

Publication Title

Contemporary Educational Technology

DOI

10.30935/cedtech/17866

Volume

18

Issue

1

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