Adrian-Marius Dumitran, Iulia-Maria Popescu (2026) — arXiv preprint.
Across 15 nations, the paper examines how secondary computer-science education embeds AI literacy into general-track subjects (Digital Literacy, ICT, TIC, SNT) rather than specialized tracks, creating structural inequities in who develops AI capability. The comparative analysis shows that policy choices about which programming language and subject bears 'universal' AI literacy determine differential access to computational futures.
Frames AI literacy 'for all' as an equity problem rooted in k-12 curriculum policy, with direct relevance to policy-maker and teacher-role decisions. It ties to ai-literacy as a civil competency and to faculty-development-genai for teacher preparedness, arguing that without equitable language/policy grounding, AI literacy widens rather than closes gaps in higher-ed readiness.
Related Pages
- ai-literacy — AI literacy as equity-critical competency
- equity — Structural inequities in access
- k-12 — Secondary CS education policy
- policy-maker — Curriculum policy decisions
- faculty-development-genai — Teacher AI-literacy preparedness
- teacher-role — Teachers implementing policy
- suacode-african-students-motivations — African students' motivations for a smartphone-based coding MOOC center on access, career aspiration