Young Children's Understanding of Artificial Intelligence: A Draw-a-Picture Analysis

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Bibliographic Details
Title: Young Children's Understanding of Artificial Intelligence: A Draw-a-Picture Analysis
Language: English
Authors: Xinyu Chang (ORCID 0009-0005-8461-6551), Zhenping Yan (ORCID 0009-0002-5897-9883), Gary K. W. Wong (ORCID 0000-0003-1269-0734)
Source: British Journal of Educational Technology. 2026 57(1):346-372.
Availability: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Peer Reviewed: Y
Page Count: 27
Publication Date: 2026
Document Type: Journal Articles
Reports - Research
Education Level: Elementary Education
Descriptors: Young Children, Knowledge Level, Artificial Intelligence, Cognitive Tests, Freehand Drawing, Personality Measures, Projective Measures, Digital Literacy, Elementary School Students, Foreign Countries, Man Machine Systems, Student Attitudes
Geographic Terms: China
DOI: 10.1111/bjet.70022
ISSN: 0007-1013
1467-8535
Abstract: With the increasingly ubiquitous presence of artificial intelligence (AI) technology in digital society, educators appeal to foster the public's general knowledge about AI from young children. Studies have been conducted to create learning activities for children's development of AI literacy, but seldom did they investigate the resources children have prior to instruction. The purpose of this study is to explore young children's preconceptions of AI and the sources of their viewpoints. A total of 261 students aged 7 to 9 from a public elementary school in a Southern Chinese city were recruited to finish the draw-a-picture task, and 32 students participated in the follow-up sharing in the classrooms. Through the drawing analysis, we identified five categories to describe young children's impressions of AI, including the appearance of AI, tasks handled by AI, environment, human--AI relationship, and feelings and attitudes towards AI. Moreover, our analysis revealed that everyday technology and media act as two main sources of young children's preconceptions of AI. This research offers methodological and empirical contributions to AI literacy research and practical insights for AI production developers, policymakers and curriculum designers.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1493593
Database: ERIC
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