Original Coverage & Source Attribution: bioengineer.org
A comprehensive critical review published in AI, Brain and Child has systematically evaluated how artificial intelligence is conceptualized across early childhood education research. Led by researchers examining empirical and theoretical publications, the investigation adapted the cognitive, situated, and critical computational thinking framings established by Yasmin Kafai and Chris Proctor to explore intelligent technologies in early learning settings. By evaluating how prior scholarship addresses foundational educational questions of what children learn, how experiences are structured, and who benefits from technological tools, the authors identified substantial structural imbalances in the prevailing literature. Existing research demonstrates a heavy concentration of empirical investigations focused on individual cognitive gains and situated environmental interactions. However, the review revealed a conspicuous shortage of critical perspectives examining systemic equity, societal consequences, and democratic access. To bridge these gaps, the authors advocate for integrating a posthumanist perspective and an ethic of care framework to establish socially responsible and sustainable early learning ecosystems.
The researchers conducted their critical review following systematic search and selection principles outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Literature searches were executed across Google Scholar, Web of Science, and Scopus to capture interdisciplinary contributions published through June 2024. The retrieval strategy deployed keyword strings combining artificial intelligence terminology, early childhood age ranges, and foundational learning theories. To focus strictly on direct educational impacts on typically developing young learners, the team excluded investigations centered on special education, teacher or parent training, and non-peer-reviewed commentaries. The initial search yielded 579 records, which narrowed to 301 following title and abstract screening, and subsequently to 159 candidates through secondary evaluation. A final appraisal based on explicit theoretical integration criteria identified 34 qualifying papers, comprising 21 empirical studies and 13 conceptual or review articles. Across these publications, 8 articles represented cognitive framing, 17 represented situated framing, and 10 represented critical framing, with one study overlapping both cognitive and situated domains.
Within the cognitive framing, comprising eight studies, researchers investigated internal mental operations such as reasoning, memory, attention, and motivation, drawing upon cognitivist principles from Jean Piaget and Susan Carey. Empirical studies in this domain focused on children learning with artificial intelligence, using quantitative designs with larger samples to evaluate perceptions of animacy in technological agents. Grounded in concepts of animism originally articulated by Robert Ranulph Marett and expanded by Piaget, these studies assessed how children categorize interactive machines. For instance, Tanya Beran and colleagues studied 184 participants aged 5 to 16, finding that younger children attributed cognitive abilities like memory to robots even during manual control, while affective attributions persisted across age groups. Similarly, Darren Cameron and co-authors examined 72 children aged 4 to 12, discovering that children aged six and under perceived humanoid robots as person-like when autonomous behavior was exhibited, whereas older children classified them as mechanical devices.
Expanding upon cognitive categorizations, research by Miri Kim and colleagues evaluated animacy reasoning among 120 children aged 3 to 5 exposed to humanoid robots across four conditions varying mobility and contingency. Their findings indicated that three-year-olds relied predominantly on movement cues to judge whether an agent was alive, whereas five-year-olds prioritized psychological contingency and responsiveness. Beyond animacy, cognitive frameworks incorporated self-determination theory and developmental stage models. Ting Zhang and Weiqin Tang utilized Piagetian stages to structure three companion robot interaction modes—visual displays, speech recognition, and physical gestures—tailored for learners aged zero to eight. Additionally, Paulien van Minkelen and colleagues evaluated 49 Dutch children aged 5 to 6, observing that self-determination relatedness support enhanced task engagement during second-language learning without improving vocabulary acquisition. Meanwhile, conceptual papers by Jiahong Su, Weipeng Yang, and Yuchun Zhong translated abstract artificial intelligence concepts into early childhood curricula, incorporating playful role-play and structured competencies spanning knowledge, skills, and ethical attitudes.
Situated framings represented the most prevalent category in the review, encompassing 17 articles that examined the dynamic interplay between technological agents, learners, and sociocultural environments. Rooted in Lev Vygotsky’s sociocultural theory, this literature emphasizes how social and linguistic interactions mediate cognitive growth through the Zone of Proximal Development. Multiple investigations demonstrated that artificial intelligence tools can scaffold learning tasks to match children’s emerging capabilities, as evidenced in research by Antonio Silva and colleagues as well as Fredy Baskara. Observational and experimental studies confirmed the relevance of Albert Bandura’s social learning theory, with Qianqian Jia and collaborators demonstrating that robots modeling prosocial behavior significantly increased sharing tendencies among young children. Furthermore, comparative experimental work by Ömer Demir-Lira and colleagues identified that visual cues presented by social robots were more effective than physical gestures in teaching language concepts, while participatory activities using Google’s Teachable Machine enabled active knowledge construction through collaborative exploratory engagement.
Situated research also highlighted the functional roles of artificial intelligence and mediation processes shaping collaborative learning environments. Drawing from George Herbert Mead’s social theory, Katharina Rohlfing and colleagues demonstrated that social robots configured as tutors, peers, or novices fundamentally alter interactive behaviors, engagement depths, and learner expectations. Applying mediation theory, studies by Sarika Kewalramani and co-authors illustrated how robotic toys, when scaffolded by educators, foster collaborative inquiry and creative exploration in early classrooms. Furthermore, studies rooted in multimodality and Seymour Papert’s constructionism showed how embodied interactions reinforce conceptual learning. Cristina Sabena documented how programmable robots facilitate spatial reasoning through physical navigation, while Ilene Berson and colleagues analyzed multimodal creative inquiry utilizing Citizen DJ to combine musical and kinetic exploration, showing how sensory-rich environments promote meaningful early learning.
In sharp contrast to cognitive and situated prevalence, the critical framing remained underdeveloped, represented by only 10 articles addressing ethics, power structures, social equity, and democratic participation. This literature conceptualizes artificial intelligence through metaphors of dual impact, such as a double-edged sword or Pandora’s box, balancing personalized learning affordances against risks of data privacy violations, algorithmic bias, and digital dependency. To guide pedagogical practice, Jiahong Chen and Jiangchun Lin introduced the POWER principles—advocating purposeful, optimal, wise, ethical, and responsible integration—while Wei Luo and colleagues formulated the 3A2S framework addressing accessibility, affordability, accountability, sustainability, and social justice. Other studies focused on nurturing critical technological reflection among children themselves. Blandine Fanny and co-authors investigated metaphorical discourses to cultivate early robot literacy, while Nils Tolksdorf and colleagues demonstrated that interactions with social robots stimulated metatalk and metacognitive reflection in preschool classrooms, though authors emphasized that empirical critical research currently lacks longitudinal, child-centered designs.
Critical perspectives also interrogated systemic equity and explored non-human relational ethics within early childhood spaces. Addressing educational disparities, Helena Pozniak argued that artificial intelligence algorithms could help identify students requiring targeted intervention to mitigate educational exclusion, though rigorous human oversight remains imperative to prevent automated systems from reinforcing institutional biases. Similarly, Weipeng Yang and colleagues evaluated robot programming initiatives in under-resourced schools, demonstrating how hardware scarcity and insufficient teacher training impede equitable technological access. Concurrently, theoretical contributions challenged traditional boundaries by framing robots as a new ontological category, as conceptualized by Peter Kahn and colleagues. Research demonstrated that children often perceive social robots simultaneously as artifacts and social companions, prompting complex moral judgments. Studies by Daniel Martin and colleagues, alongside work by Kristin Brink and Henry Wellman, revealed that children extend prosocial norms, altruism, and trust toward technological agents, while Denise Silvis and collaborators demonstrated that children caring for malfunctioning robots cultivates mutual empathy and reciprocal responsibility.
Synthesizing these findings, the review mapped how each framing corresponds to foundational curriculum questions regarding what children should learn, how instruction must be organized, and who benefits from educational technologies. Research within the cognitive framing primarily addresses what content to teach, emphasizing computational concepts and foundational domain knowledge. The situated framing addresses how pedagogical experiences occur, promoting culturally responsive, play-based, and embodied methods that leverage contextual environments. The critical framing engages the sociotechnical question of who benefits, seeking to dismantle systemic oppression, bridge digital divides, and protect marginalized populations. To resolve tensions across these dimensions, the review authors propose adopting a posthumanist theoretical lens. Drawing on philosophical perspectives that critique anthropocentric assumptions, posthumanism views artificial intelligence not merely as an instrument for human utility, but as an agential material entity engaged in intra-action within broader social and ecological networks, aligning with Rosi Braidotti’s affirmative ethics of mutual interdependence and ecological frameworks positioning artificial intelligence within planetary coexistence.
Finally, the critical review highlighted substantial geographic imbalances and articulated crucial practical implications for international educational practice. Existing literature remains overwhelmingly centered on Western contexts, leaving noticeable empirical gaps regarding early childhood traditions across the Global South. Analyzing research conducted in Asian settings, scholars such as Jing Xu identified that regional studies frequently remain broad without achieving empirical depth. Furthermore, pedagogical traditions such as East Asian Confucian teaching models, which emphasize teacher-directed authority, present distinctive adaptation challenges for child-centered artificial intelligence applications. However, authors noted that posthumanist ethics and ecological care naturally resonate with long-standing Asian philosophies, including Buddhist and Daoist principles prioritizing universal harmony and relational interdependence among living and non-living entities. For early childhood practitioners, the review recommends adopting developmentally tailored tools that match cognitive capacities, utilizing multimodal robots to foster collaborative social expression, maintaining ethical transparency regarding machines’ psychological limits, and ensuring equitable resource distribution to prepare young children for an increasingly automated society.
Subject of Research: Theoretical conceptualization of artificial intelligence in early childhood education
Article Title: From Piaget to posthumanism: critical review of conceptualization of AI in early childhood education
Article References: Cai, Z. J., Xing, G. Y., Yamamoto, Y., & Wang, X. C. (2025). From Piaget to posthumanism: critical review of conceptualization of AI in early childhood education. AI, Brain and Child, 1(1), Article 14. https://doi.org/10.1007/s44436-025-00012-4
Keywords: artificial intelligence, early childhood education, cognitive development, situated learning, critical framing, posthumanism, educational robotics, ethic of care, Piaget, critical, review, conceptualization
