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Cited by 130Child Development and Digital TechnologyTeaching and Learning ProgrammingLiteracy, Media, and Education

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

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Druga, Stefania, Christoph, Fee Lia, Ko, Amy J·2022·CHI Conference on Human Factors in Computing Systems
DOI 10.1145/3491102.3502031
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Abstract

Many families engage daily with artificial intelligence (AI) applications, from conversations with a voice assistant to mobile navigation searches. While there are known ways for youth to learn about AI, we do not yet understand how to engage parents in this process. To explore parents’ roles in helping their children develop AI literacies, we designed 11 learning activities organized into four topics: image classification, object recognition, interaction with voice assistants, and unplugged AI co-design. We conducted a 5-week online in-home study with 18 children (5 to 11 years old) and 16 parents. We identify parents’ most common roles in supporting their children and consider the benefits of parent-child partnerships when learning AI literacies. Finally, we discuss how our different activities supported parents’ roles and present design recommendations for future family-centered AI literacies resources.

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  42. 10.1145/3313831.3376130 · DOI

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Metadata

Authors
Druga, S., Christoph, F. L., & Ko, A. J.
Affiliations
  • University of Washington (US)
  • University of Michigan (US)
ORCID
Venue
CHI Conference on Human Factors in Computing Systems
Publisher
ACM
Published
2022-04-29
Pages
1-17
DOI
10.1145/3491102.3502031
OpenAlex
W4225000370
Cited by
130
References
83
Citations by year
2026: 44 · 2025: 40 · 2024: 29 · 2023: 12 · 2022: 5
FWCI
169.40
Type
conference paper
Language
en
Open access
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)
Locations
CHI Conference on Human Factors in Computing Systems (publishedVersion)
Funders
  • Adobe Systems
  • NSF (National Science Foundation) (1539179, 1703304, 1836813, 2031265, 2100296, 2122950, 2137834, 2137312)
Topics
  • Social Sciences › Education › Child Development and Digital Technology
  • Physical Sciences › Computer Science › Computer Science Applications › Teaching and Learning Programming
  • Social Sciences › Education › Literacy, Media, and Education
Keywords
AI literacy, family learning, parent-child partnership, voice assistants, image classification, object recognition

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