Artificial Intelligence in Early Childhood Education: Transforming Kindergarten Teaching Practices

Abstract

This paper explores the transformative potential of artificial intelligence (AI) in reshaping kindergarten teaching practices through a socio-technical systems lens. Drawing on Vygotsky's sociocultural theory and the SAMR model, it critiques the limitations of existing technology integration frameworks in early childhood education. By synthesizing 127 empirical studies and 35 conceptual papers, the research identifies three critical dimensions of AI implementation: personalized cognitive scaffolding, adaptive assessment systems, and human-AI collaborative pedagogy. The proposed AI-Enhanced Early Learning (AI-EL) model introduces dynamic feedback loops between technological affordances and developmental milestones, addressing gaps in constructivist theories. Findings highlight how AI tools can foster metacognitive skills in 3–6-year-olds through interactive storytelling and gamified assessments while redefining teacher roles as learning orchestrators. Ethical considerations emphasize the need for algorithmic transparency and culturally responsive design to avoid exacerbating educational inequalities. This theoretical contribution advances the discourse on human-technology symbiosis in foundational education, providing a heuristic framework for future empirical investigations.