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<p>Artificial intelligence (AI) is increasingly integrated into early childhood education (ECE), reshaping how young children learn and develop. While existing studies have explored AI’s practical applications in ECE, they often overlook the critical conceptualization necessary to deepen our understanding of its role in this field. To address this gap, we critically reviewed 34 studies on AI in ECE, adapting Kafai and Proctor’s (2022) cognitive, situated, and critical framings of computational thinking. Our analysis investigates how these studies conceptualize “learning with AI” and “learning about AI” and address foundational questions of “who,” “what,” and “how” in AI education for young children. The findings reveal a strong emphasis on cognitive and situated framings, which focus on individual and contextual applications of AI. However, a critical perspective addressing broader societal impacts and equity concerns is lacking. To bridge this gap, we propose a posthumanist perspective, framing AI as a new ontological category, and advocate for the ethic of&#xa0;care framework in designing AI learning experiences. These approaches aim to foster a sustainable and socially responsible ecosystem for early learning with and about AI.</p>

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From Piaget to posthumanism: critical review of conceptualization of AI in early childhood education

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月8日

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  • Zhuoyun Joy Cai,
  • Grace Yaxin Xing,
  • Yuya Yamamoto,
  • X. Christine Wang

摘要

Artificial intelligence (AI) is increasingly integrated into early childhood education (ECE), reshaping how young children learn and develop. While existing studies have explored AI’s practical applications in ECE, they often overlook the critical conceptualization necessary to deepen our understanding of its role in this field. To address this gap, we critically reviewed 34 studies on AI in ECE, adapting Kafai and Proctor’s (2022) cognitive, situated, and critical framings of computational thinking. Our analysis investigates how these studies conceptualize “learning with AI” and “learning about AI” and address foundational questions of “who,” “what,” and “how” in AI education for young children. The findings reveal a strong emphasis on cognitive and situated framings, which focus on individual and contextual applications of AI. However, a critical perspective addressing broader societal impacts and equity concerns is lacking. To bridge this gap, we propose a posthumanist perspective, framing AI as a new ontological category, and advocate for the ethic of care framework in designing AI learning experiences. These approaches aim to foster a sustainable and socially responsible ecosystem for early learning with and about AI.