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July 10, 2026

AI and Neuroeducation

Puntos clave

The review aims to explore how AI can be integrated into early childhood education through a neuroeducational lens, emphasizing ethics and personalized learning.
Conducted systematic review following PRISMA 2020 guidelines across five databases: Scopus, Web of Science, PubMed, PsycINFO, Elsevier.
Analyzed 41 peer-reviewed studies from an initial 812 records, combining empirical and conceptual research.
Organized findings into thematic areas including cognitive growth, socio-emotional development, and ethical implications.
AI tools demonstrated potential in enhancing cognitive and digital literacies and supporting early engagement in education.
Identified need for ethical safeguards concerning equity, transparency, and privacy when integrating AI in education.
Highlighting the importance of collaboration among educators and policymakers for responsible AI integration.

Resumen

This systematic review examines the integration of artificial intelligence (AI) into early childhood education through a neuroeducational perspective, emphasizing ethical approaches to personalized learning. Following PRISMA 2020 guidelines, the review applied a rigorous and transparent methodology across five databases: Scopus, Web of Science, PubMed, PsycINFO, and Elsevier. From 812 identified records, forty-one peer-reviewed studies met the inclusion criteria and were analyzed in depth. The selected studies included both empirical and conceptual research, allowing a balanced synthesis of evidence regarding the cognitive, socio-emotional, and ethical implications of AI in education. The findings were organized into four thematic areas: development of cognitive and digital literacies; stimulation of executive functions, attention, and socio-emotional growth; personalized learning and educational assessment; and governance, ethical frameworks, and multimodal integration. Empirical evidence showed that AI tools, including robotics, adaptive learning systems, and voice-based agents, can support early development, inclusion, and engagement in learning environments. Conceptual studies highlighted the importance of ethical safeguards related to equity, transparency, privacy, and child-centered design. The review concludes that AI, when aligned with neuroeducational principles, can become a transformative resource in early education by supporting personalized learning pathways. Nevertheless, methodological heterogeneity, limited sample sizes, and the underrepresentation of studies from diverse regions reveal the need for more robust, longitudinal, and cross-cultural research. Overall, the review underscores the importance of collaboration among educators, neuroscientists, policymakers, and developers to ensure that AI applications remain appropriate, ethically grounded, and accessible to diverse educational contexts. These considerations are essential for promoting responsible innovation and transformation globally.

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