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

Abstract 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.

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Publication Details

Journal
AI Brain and Child
Published
2025-10-08
DOI
https://doi.org/10.1007/s44436-025-00012-4
Citations
2
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
4.73
Controls
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article

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

Zhonghou Cai, X. Christine Wang, Grace Yaxin Xing, Y. Yamamoto
2 citations
AI Brain and Child
Ethics and Social Impacts of AI
4.73
article

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

Zhonghou Cai, X. Christine Wang, Grace Yaxin Xing, Y. Yamamoto
article en
2 citations

Abstract

Abstract 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.

AI Brain and ChildVol. 1(1)
Buffalo State University (US), University at Buffalo, State University of New York (US)
Openalex Percentile: Top 5%
Ethics and Social Impacts of AI
4.73
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