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Understanding Parents' Perspectives on Responsible AI for Children's Self-Directed Learning

Jingyi Xie, Chuhao Wu, Ge Wang, Rui Yu, He Zhang, Ronald A. Metoyer, Si Chen

2026Year
3Citations
1Top-tier citations

Abstract

Generative AI is increasingly present in children’s learning environments, yet little is known about how families navigate this technology in middle childhood (ages 7–13), when parental guidance remains strong but children seek independence. Drawing on self-directed learning (SDL), we explore how parents in our exploratory sample perceived children’s emerging self-directness and agency. Through focus groups with 13 parent–child pairs, we examine parents’ views on children’s AI literacy development, readiness factors, and mediation strategies. Parents described emergent pathways shaped by screen time, self-directness, and knowledge growth. They often confined AI to learning-only contexts, positioning it as a tutor while overlooking non-learning uses and risks such as privacy and infrastructural embedding. Many acknowledged limited AI literacy and turned to joint engagement as opportunities for co-learning. Our findings surface possible parental pathways of children’s AI literacy, highlight gaps between pragmatic expectations and critical literacies, and offer situated design considerations for AI systems that scaffold SDL while balancing oversight with autonomy.

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