Critical Review Examines How Artificial Intelligence Is Conceptualized in Early Childhood Education
By Google News AI ·
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…
Originally published by Google News AI
