Kwan Chuen Chan
This project investigates cross-framework interoperability in AI literacy education, with a particular focus on Hong Kong. As AI literacy becomes an increasingly important educational priority, a growing number of international, national, and institutional frameworks have been developed to define the knowledge, skills, attitudes and ethics that learners need in in teaching and learning about AI. However, these frameworks often differ in their framework structures, terminology, and levels of granularity. The rapid proliferation of such frameworks creates an urgent need for interoperability so that their defined knowledge, skills, attitudes and ethics can be systematically compared and connected for different learning stages. Without a systematic cross-framework mapping, educators, curriculum designers, policymakers, and researchers may struggle to identify the possible overlaps and gaps across frameworks. This combination of structural divergence and educational commonality motivates the project investigation. The expected contribution is a scalable, transparent, and reproducible method for supporting cross-framework mapping for future curriculum development in AI literacy education.