Reviewed GenAI literacy literature concentrates on knowledge and skills while equity and agency receive thin treatment¶

Claim · All claims
Evidence · 1 study · review r2 · q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Across 67 reviewed studies (2023–2025), knowledge and skill dimensions received near-universal substantive treatment while equity and agency appeared in a minority of studies. → Shahin Hossain 2026

Evidence¶

Shahin Hossain 2026¶

Shahin Hossain, Sima Ahmadi, Leqi Li, Idowu David Awoyemi, Wei Huang, Chenxi Zhou, Jujia Li, Samaa Haniya, Shapla Khanam, Tasbirun Mashreka Subaha. (2026). Rethinking Generative AI Literacy: An Integrative, Developmental, and Dialectical Framework for K–12 Teacher Education. https://arxiv.org/abs/2608.01705 doi:10.48550/arxiv.2608.01705

q2 · i? · review · r2

Systematic review of 67 publications on AI and GenAI literacy (2023–2025), each coded against five a priori concept-analysis dimensions (knowledge, skill, ethics, equity, agency). Table 1 reports knowledge at 65 studies (97%), skill at 64 (96%), ethics at 66 (99%), equity at 49 (73%), agency at 40 (60%). "Coverage focuses on knowledge and skills, while equity and agency receive substantive treatment in a minority of studies."

"Coverage focuses on knowledge and skills, while equity and agency receive substantive treatment in a minority of studies, the systematic thinness that RAIL-Ed is designed to address."

Discussion¶

Related Claims¶

• The Global South GenAI literature shows limited geographic representation, stakeholder imbalance, and insufficient exploration of long-term outcomes — related
• Existing institutional AI literacy frameworks converge on a consumer model with no substantive treatment of training data politics or governance participation — related
• Equity considerations have received the least research attention among GenAI perception areas despite their critical importance — related
• K-12 AI learning experiences concentrate on technical, conceptual and applied skills in specific domains, while implementation schemes are led by the US and China — related
• Technology disciplines, especially Computer Science and Data Science, lead contributions to AI literacy across TIECD dimensions, while Design (AILE 5.1) is underrepresented across all STEAM clusters — related