Family as a Third Space for AI Literacies: How do children and parents learn about AI together?

Title of the Paper

Family as a Third Space for AI Literacies: How do children and parents learn about AI together?

Paper Information

• Subject Area: Artificial Intelligence Education and Family Learning Interaction
• Keywords: AI literacy, family learning interaction, parental roles, multimodal learning, children's education, collaborative design, parental guidance, algorithmic fairness

Research Background and Issues

• Identified Problems or Challenges:

  • As AI technologies increasingly permeate family life, there is a lack of guidance and education in the use of smart devices (e.g., voice assistants, navigation tools) within households.
  • While there are abundant AI educational resources aimed at children, solutions that actively involve and guide parents are scarce.
  • Issues such as bias, fairness, and privacy protection associated with AI technologies present new challenges for educating children and families.

• Significance:

  • Enhancing AI literacy among family members can facilitate safer and more rational use of AI technologies at home, improving overall technological adaptability.
  • Understanding how families learn AI knowledge together can empower parents to become more effective supporters of technological learning and foster critical thinking in children.

• Research Motivation and Related Work:

  • Previous academic studies have explored parental roles in supporting children's technological learning (e.g., as teachers, collaborators), but practical experience in the field of AI education remains limited.
  • The "multi-literacies" framework has been proposed as the theoretical background for this study, emphasizing multilingual and cultural participation to guide the design of family AI learning activities.

Proposed Solution

• Proposed Solution:

  • Designed 11 family-centered learning activities covering four key dimensions of AI learning, including image classification, object recognition, voice assistant interaction, and collaborative AI design.
  • Developed AI literacy dimensions based on the "multi-literacies" framework, including:
    • Multimodal and embodied learning practices
    • Conceptual learning of AI
    • Critical AI frameworks
    • The ability to translate learning into practical usage scenarios

• Innovative Aspects:

  • Positioning the family as a "third space" where bidirectional learning enables both parents and children to develop AI literacy together.
  • Designing highly interactive and practical multimodal learning activities tailored for families.
  • Systematically exploring the multiple roles parents can play in AI learning activities and their impact on children's learning.

• Implementation Steps:

  • Recruited 15 families to participate in a 5-week learning program, with weekly online learning sessions.
  • Recorded videos and transcribed texts to analyze family interactions, using joint media theory and parental assistance behavior theory to identify parental roles in the learning activities.
  • Conducted feedback surveys and thematic analysis to provide recommendations for designing family AI education resources.

Research Outcomes

• Specific Outcomes:

  • Parents can play eight distinct roles in family AI learning: collaborator, mentor, learner, teacher, observer, and others.
  • The designed AI learning activities enhanced family interactions and supported parents in guiding children's learning.
  • Results showed that multimodal and embodied learning activities (e.g., AI training and disconnected design tasks) were most effective in engaging family members collaboratively.

• Advantages Over Existing Solutions:

  • Compared to traditional learning resources designed solely for children, this study's activity design strengthened collaborative learning between children and parents.
  • Expanded AI education beyond technical learning to include critical considerations of technology ethics and privacy, encouraging families to participate in future AI design practices.

• Experimental or Evaluation Results:

  • Parents and children gained a deeper understanding of AI behaviors through collaborative tasks and learned how to solve technical issues and troubleshoot problems.
  • Most families rated interactive games and design tasks highly, noting that the activities stimulated creativity in both children and parents.

• Limitations and Future Directions:

  • Approximately half of the participating parents had some technical background, which may limit the effectiveness of activities for non-technical families.
  • The study was conducted online, which restricted the observation of daily AI interactions in real-life family settings.
  • Future research could expand the sample scope, explore the impact of multicultural contexts on AI literacy education, and design more inclusive and culturally relevant AI applications.

Conclusion

This study is the first to systematically explore the role of families in AI literacy education and provides practical recommendations for designing educational resources. The findings highlight the importance of families as a "third space" for technological education, aiming to foster discussions on technology ethics and practical design among family members, thereby creating conditions for the fair use of AI technologies.