From Piaget to Posthumanism: Conceptualization of AI in Early Childhood Education

• In Event: Fostering AI Literacy in Early Childhood: Emerging Theoretical and Empirical Insights

Abstract

Artificial Intelligence (AI) has been increasingly introduced to Early Childhood Education (ECE) settings, prompting burgeoning research on its integration with traditional practices (Su et al., 2023). However, there is limited effort to examine the underlying assumptions about AI in the existing research. To bridge the gap, we conduct a critical review to explore how AI is conceptualized in ECE contexts, drawing on the cognitive, situated, and critical framings of computational thinking outlined by Kafai and Proctor (2022). Our review aims to uncover the theoretical roots of current trends and suggest future research directions, emphasizing the importance of addressing educational inequities and fostering equitable renewal in ECE.

This review critically examines 36 studies from Asian and Western contexts, sourced from Scopus, Web of Science, and Google Scholar. Studies are categorized into cognitive, situated, and critical framings, with some intersecting across multiple framings. The sources include peer-reviewed articles and empirical research on AI integration in ECE, examining both “learning about AI” and “learning with AI.” By redefining cognitive, situated, and critical framings, AI is reconceptualized not merely as a technological tool or content within traditional educational settings but also as a form of literacy woven into daily life and learning environments.

This review reveals a significant concentration of studies within cognitive framing, mostly exploring children’s comprehension and skills concerning AI, drawing heavily on constructivism (Piaget, 1958) and constructionism (Papert, 1980). Due to their unique characteristics, these studies propose a new ontological category for intelligent agents that do not easily fit traditional categories, such as humans, animals, or inanimate objects (Kahn et al., 2013). Many studies also adopt the situated framing, viewing learning as an identity-shaping process deeply integrated within socio-cultural contexts to enrich the educational experience. This perspective is shaped by Vygotsky’s theories of social development and mediation (1978) and embodied learning theories (McCafferty, 2002), stressing the importance of creating engaging, age-appropriate, and culturally relevant AI applications. Additionally, studies employing the critical framing scrutinize the complex interactions between AI and young learners, advocating for AI education that supports broader educational values like humanism, diversity, and justice. These studies highlight ethical care (Silvis et al., 2022) as essential for child-technology interactions and suggest redefining AI as a critical educational resource (Su et al., 2023), pushing for its design and application to be viewed through a justice-oriented lens that emphasizes inclusivity and equity for marginalized groups and children with special needs.

Through a critical examination of the conceptualization of AI in ECE in the existing research, our review highlights the urgent need to go beyond narrow cognitive framing and develop broader theoretical models of AI to allow a more expansive research agenda to thrive. For example, we’d encourage future studies to explore ethical care as a theoretical framework for reassessing the interactions between young learners and AI through a post-humanism view, aiming to cultivate a future society characterized by empathy, democracy, and inclusivity. In addition, we’d advocate for research programs that are tailored to the particulars of different cultural contexts, both locally and internationally.

Authors

• Zhuoyun Cai, University at Buffalo - SUNY

• Grace Yaxin Xing, University at Buffalo - SUNY

• Yuya Yamamoto, University at Buffalo - SUNY