Artificial Intelligence in Early Childhood Education: A Systematic Review of Educational Implications and Ethical Considerations
DOI:
https://doi.org/10.53905/ChildDev.v2i01.10Keywords:
artificial intelligence, early childhood education, pedagogical impact, ethical challenges, adaptive learning, educational robotsAbstract
Purpose of the study: This systematic literature review examines the pedagogical implications and ethical considerations arising from the integration of Artificial Intelligence (AI) technologies within Early Childhood Education (ECE) environments worldwide. The review seeks to consolidate empirical evidence concerning AI-supported learning outcomes, the evolving dynamics of teacher–AI interactions, and the ethical issues associated with the implementation of intelligent technologies for children aged 0–8 years..
Materials and methods: Guided by the PRISMA 2020 framework, a comprehensive literature search was undertaken across seven major scholarly databases, namely Scopus, Web of Science, ERIC, PsycINFO, IEEE Xplore, ACM Digital Library, and Google Scholar. The search encompassed studies published between January 2015 and December 2024. Following a rigorous screening process based on predefined eligibility criteria, 63 peer-reviewed studies were selected for inclusion. Data extraction was conducted using a standardized procedure, and findings were synthesized through thematic and narrative analysis.
Results: The analysis revealed five dominant thematic areas: (1) AI-driven personalized learning and adaptive instructional practices (n = 18); (2) AI companions and educational robots supporting social-emotional development (n = 14); (3) conversational AI applications facilitating language and literacy development (n = 13); (4) teacher professional learning and pedagogical innovation enabled by AI technologies (n = 10); and (5) ethical challenges related to privacy, data protection, and algorithmic bias (n = 8). Across diverse educational and cultural contexts, AI-supported interventions were associated with significant improvements in phonological awareness, early numeracy competencies, and learner engagement. Nevertheless, persistent concerns were identified regarding data privacy, digital inequalities, and the potential erosion of human-centred pedagogical relationships.
Conclusions: AI technologies offer considerable potential to enhance learning experiences in ECE when implemented within robust ethical frameworks that prioritize child well-being, developmental appropriateness, and equitable access. However, the current body of evidence highlights substantial gaps concerning long-term developmental outcomes, cross-cultural applicability, and the establishment of effective governance mechanisms. Future policy and practice should promote collaborative design approaches that foreground the developmental rights and best interests of young children
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