Exploring parental AI literacy in the context of early childhood learning

Key findings from this study

This research indicates that:

• Parental mediation strategies for AI technologies in early childhood education vary substantially based on socioeconomic status, cultural background, age, and educational level.
• Parental AI literacy—encompassing knowledge evaluation, practical skills, and attitudes—directly influences the effectiveness of parental mediation and children's learning outcomes.
• AI applications in early childhood education span six distinct categories with varying implications for development and learning experiences.
• Data privacy concerns and potential amplification of digital disparities present significant challenges alongside the pedagogical advantages of AI integration.
• Family-centered policy and training approaches are essential for leveraging AI benefits while mitigating developmental and ethical risks.

Overview

This review examines parental artificial intelligence literacy within early childhood education contexts. The analysis addresses how parental knowledge, skills, and attitudes influence children's learning experiences as AI technologies become embedded in educational and household environments. The review identifies AI applications across six categories: interactive AI, generative AI, AI prediction, AI literacy instruction, AI-driven personalized learning, and affective AI systems.

Methods and approach

The review synthesizes existing literature on AI integration in early childhood education and parental mediation strategies. The authors developed a novel conceptual framework for parental AI literacy comprising three dimensions: knowledge evaluation, skills for use and guidance, and attitudes regarding AI understanding. The framework anchors analysis in family-centered contexts rather than institutional settings alone.

Results

Six main categories of AI applications emerged across early childhood education: interactive AI, generative AI, AI prediction systems, AI literacy programs, personalized learning platforms, and affective AI. Parental mediation strategies vary along a spectrum from restrictive to supportive approaches, with outcomes influenced by socioeconomic status, cultural background, age, and educational attainment. The proposed parental AI literacy framework integrates three interdependent dimensions: knowledge competencies enabling evaluation of AI tools; practical skills encompassing both use and guidance provision; and attitudes reflecting understanding of AI's role in childhood development. Parental AI literacy levels directly correlate with mediation effectiveness, suggesting that enhanced parental knowledge and skills substantially improve outcomes.

Implications

Policy development must account for family-centered approaches to AI integration in early childhood education. Educational institutions require frameworks supporting parental training programs that address knowledge gaps and skill development across diverse socioeconomic and cultural contexts. The identified digital disparities risk widening without targeted interventions addressing parental AI literacy across socioeconomic strata.

Scope and limitations

This summary is based on the study abstract and available metadata. It does not include a full analysis of the complete paper, supplementary materials, or underlying datasets unless explicitly stated. Findings should be interpreted in the context of the original publication.