Constructing AI literacy : a hands-on approach for school children

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.