Artificial Intelligence in Early Childhood STEM Education: A Review of Pedagogical Paradigms, Ethical Issues, and Socio-Political Implications

Abstract

This study examines the pedagogical, ethical, and political dimensions of artificial intelligence (AI) in early childhood STEM education from a theoretical perspective. As digital technologies become increasingly prevalent in education, AI applications offer significant opportunities in areas such as personalized learning experiences, game-based education, and data analytics. However, they also pose critical ethical concerns, including data security, algorithmic bias, and privacy, while influencing children's cognitive, linguistic, and social development. Drawing on Piaget’s theory of active discovery and learning, Vygotsky’s emphasis on social interaction and teacher guidance, and Bronfenbrenner’s ecological systems theory, this study explores how AI-supported learning environments can enrich children's natural developmental processes. A qualitative literature review and theoretical analysis reveal the necessity of achieving a balanced integration between the individualized educational opportunities offered by AI and the potential risks it entails. The findings highlight the critical importance of developing human-centered, ethically sound, and inclusive educational models for educators, policymakers, and researchers in the face of technological transformation. In this context, teacher training, parental collaboration, and interdisciplinary strategies are identified as fundamental prerequisites for the sustainable and effective integration of AI in early childhood education.