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Constructing AI Literacy: A Hands-On Approach for School Children

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Title: Constructing AI Literacy: A Hands-On Approach for School Children
Language: English
Authors: Leonard Busuttil
Source: Informatics in Education. 2025 24(4):761-779.
Availability: Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: info@mii.vu.lt; Web site: https://infedu.vu.lt/journal/INFEDU
Peer Reviewed: Y
Page Count: 20
Publication Date: 2025
Document Type: Journal Articles
Information Analyses
Education Level: Elementary Education
Secondary Education
Elementary Secondary Education
Descriptors: Artificial Intelligence, Technology Uses in Education, Technological Literacy, Digital Literacy, Best Practices, Barriers, Ethics, Teaching Methods, Elementary Schools, Secondary Schools, Experiential Learning, Elementary Secondary Education, Active Learning, Student Projects, Constructivism (Learning), Models
ISSN: 1648-5831
2335-8971
Abstract: This narrative literature review examines constructionist approaches to AI literacy education for school-aged children, synthesizing research from 2009-2024 to develop a pedagogical framework grounded in hands-on learning principles. Through systematic analysis of studies retrieved from Web of Science, Scopus, IEEE Xplore, and ACM Digital Library, five interconnected themes emerged: active hands-on learning, project-based inquiry, ethics integration, age appropriate scaffolding, and teacher support with accessible tools. The findings demonstrate that constructionist methodologies -- emphasizing learning through creating AI-powered artifacts -- effectively foster conceptual understanding, ethical reasoning, and critical agency among young learners. The review reveals that AI literacy develops most effectively when students actively manipulate and experiment with AI systems rather than passively consuming theoretical content. Age-differentiated strategies are essential, with primary students benefiting from embodied analogies and narrative contexts, while secondary students engage with collaborative design projects addressing real-world challenges. Teacher preparation and accessible tools emerge as critical implementation factors. This framework provides educators and policymakers with evidence-based guidance for integrating meaningful AI literacy experiences into K-12 curricula through constructionist pedagogies.
Abstractor: As Provided
Entry Date: 2026
Accession Number: EJ1494549
Database: ERIC
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  Data: Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: info@mii.vu.lt; Web site: https://infedu.vu.lt/journal/INFEDU
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  Data: This narrative literature review examines constructionist approaches to AI literacy education for school-aged children, synthesizing research from 2009-2024 to develop a pedagogical framework grounded in hands-on learning principles. Through systematic analysis of studies retrieved from Web of Science, Scopus, IEEE Xplore, and ACM Digital Library, five interconnected themes emerged: active hands-on learning, project-based inquiry, ethics integration, age appropriate scaffolding, and teacher support with accessible tools. The findings demonstrate that constructionist methodologies -- emphasizing learning through creating AI-powered artifacts -- effectively foster conceptual understanding, ethical reasoning, and critical agency among young learners. The review reveals that AI literacy develops most effectively when students actively manipulate and experiment with AI systems rather than passively consuming theoretical content. Age-differentiated strategies are essential, with primary students benefiting from embodied analogies and narrative contexts, while secondary students engage with collaborative design projects addressing real-world challenges. Teacher preparation and accessible tools emerge as critical implementation factors. This framework provides educators and policymakers with evidence-based guidance for integrating meaningful AI literacy experiences into K-12 curricula through constructionist pedagogies.
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      – Text: English
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        PageCount: 20
        StartPage: 761
    Subjects:
      – SubjectFull: Artificial Intelligence
        Type: general
      – SubjectFull: Technology Uses in Education
        Type: general
      – SubjectFull: Technological Literacy
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      – SubjectFull: Digital Literacy
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      – SubjectFull: Ethics
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      – SubjectFull: Teaching Methods
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      – SubjectFull: Elementary Schools
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      – SubjectFull: Secondary Schools
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