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<p>This study offers a comprehensive state-of-the-art review of Artificial Intelligence (AI) and Early Childhood Education (ECE) research, focusing on publications from 2020 to 2024. The primary objectives are to map, analyse and answer research questions about the landscape of AI and ECE. The review process involved searching databases, including Scopus, ERIC, SpringerLink, ScienceDirect, and Web of Science. 39 studies were selected after applying exclusion criteria to ensure relevance to AI and ECE. This review adopts an international perspective, incorporating studies written in English, aiming to provide a global view of trends and practice of AI and ECE. Furthermore, the review categorises AI into classifications such as Traditional AI and Generative AI to identify trends within this field. The content analysis covers publication frequency, participant demographics, methodological approaches, and AI classifications while highlighting existing gaps in the current research on AI and ECE. The findings reveal a significant increase in AI research within ECE from 2020 to 2024, with a notable rise in publications in 2024. The results show that studies predominantly focus on children aged 4–6 and employ mixed-method approaches. Despite advancements, gaps in long-term studies, diverse population inclusion, and comprehensive ethical frameworks remain, underscoring the need for future research to address these issues.</p>

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The Interaction of AI and Early Childhood Education. A State-of-the-art Review 2020–2024

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年1月13日

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  • Lukas Ljungcrantz

摘要

This study offers a comprehensive state-of-the-art review of Artificial Intelligence (AI) and Early Childhood Education (ECE) research, focusing on publications from 2020 to 2024. The primary objectives are to map, analyse and answer research questions about the landscape of AI and ECE. The review process involved searching databases, including Scopus, ERIC, SpringerLink, ScienceDirect, and Web of Science. 39 studies were selected after applying exclusion criteria to ensure relevance to AI and ECE. This review adopts an international perspective, incorporating studies written in English, aiming to provide a global view of trends and practice of AI and ECE. Furthermore, the review categorises AI into classifications such as Traditional AI and Generative AI to identify trends within this field. The content analysis covers publication frequency, participant demographics, methodological approaches, and AI classifications while highlighting existing gaps in the current research on AI and ECE. The findings reveal a significant increase in AI research within ECE from 2020 to 2024, with a notable rise in publications in 2024. The results show that studies predominantly focus on children aged 4–6 and employ mixed-method approaches. Despite advancements, gaps in long-term studies, diverse population inclusion, and comprehensive ethical frameworks remain, underscoring the need for future research to address these issues.