Jiawen Wu
Research Question 03 · Families and AI

How Families Shape Children's Learning in the AI Era

I study how families make sense of AI together, how parents' own experiences with and beliefs about AI shape the messages they send their children, and how the alignment or mismatch between parent and adolescent AI beliefs shapes young people's learning, reliance, and future readiness.

  • Family AI beliefs
  • Survey research
  • Qualitative interviews
  • Mixed methods
Two-panel cartoon in which a parent asks a child, ‘You AGI yet?’ and the child replies, ‘No, Dad, I’m an LLM,’ followed by ‘Talk to me when you AGI.’
Families may soon need a shared language for understanding what AI can—and cannot—do.

Program overview

The family is where children's AI use first takes shape.

What a new technology does for—or to—a child depends less on the technology than on the adults beside her. This program treats the family as the primary environment in which children's AI use takes shape and follows that question across two developmental periods and two methodological lenses.

Early childhood · ages 9–11

AI inside a shared learning task

The question is immediate and behavioral: when parents and children work together on a hard problem, does AI become a scaffold for thinking or a shortcut that makes effort optional? Parental scaffolding, performance pressure, and the moment-to-moment choices families make around the chatbot are the variables that matter.

Late adolescence · ages 17–20

Beliefs, alignment, and future readiness

The same question extends across time: how do the beliefs parents and teenagers hold about AI, and whether those beliefs align, shape motivation, cognitive strategies, and readiness for an uncertain future?

Study 1

University students’ experiences of learning with AI

Ongoing · Public conference outputs
Method University students in Singapore Survey research Qualitative interviews Mixed methods

This study mapped which AI tools students used, what they used them for, and whether they saw AI as enhancing their capabilities or threatening valued human capacities. The interview component explores how students make sense of AI in their academic lives, including learning, pressure, trust, authenticity, boundaries, and their expectations for the future.

Jiawen Wu presenting in a lecture hall beside a slide explaining how AI can deepen learning when it scaffolds rather than replaces thinking.
Presenting on developing human strengths for learning in the AI era at RPIC 2026.

RPIC 2026 · Keynote masterclass

Setoh, P. P., & Wu, J. (June 2026). Educating for the unpredictable—Developing human strengths in the AI age. Redesigning Pedagogy International Conference (RPIC) 2026, National Institute of Education, Nanyang Technological University, Singapore.

ACDC / SEA-LION 2026 · Workshop presentation

Wu, J., & Setoh, P. P. (April 2026). AI as opportunity more than threat? Student AI practices and cultural meanings of competence in Singapore. Presentation at the Asian Centre for Digital Cultures (ACDC) and Southeast Asian Languages in One Network (SEA-LION) Workshop on Culturally Aligned AI, Nanyang Technological University, Singapore.

Public workshop presentation

Explore the ideas through the ACDC / SEA-LION presentation

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Opening slide for the presentation AI as Opportunity More Than Threat?
AI as opportunity more than threat?
Public status: Survey and interviews are ongoing, and results will be updated soon.

Study 2

How parents and children will navigate AI together

Planned research strand

This planned strand will examine how parents and children understand one another’s expectations for AI, how families establish guidance and boundaries, and what supports AI use that strengthens children’s capabilities and independence. It will also explore parent–child interactions during AI-supported learning tasks to understand how the introduction of AI as a third participant reshapes family learning dynamics.

Survey patterns

Surveys characterize tools, use cases, and the coexistence of positive and negative perceptions.

Interview accounts

Qualitative interviews examine how adolescents and their parents reason about learning, pressure, trust, and authenticity.

Family dynamics

Future family research will add a developmental and relational perspective without prespecifying unsupported designs.

Talks & collaboration

Let’s think together about how families can navigate AI well.

With AI changing everything so fast, none of us have all the answers—and that's exactly why it's exciting to think about these questions together. If any of this resonates with you, I'd love to connect and chat!

  • Family AI guidance
  • AI-supported learning
  • Developmental mixed methods