2026-10-01T15:58:25Z https://dcpapers.dublincore.org/oai

oai:dcpapers.dublincore.org:952637945 2026-09-10 dcmi-2026 openaire

Reconstructing Metadata Literacy in the AI Era: A Conceptual Framework and Educational Reflections for LIS Education Ba, Xi Hussin, Nurussobah Kamarudin, Hanis Diyana This paper calls for a rethinking of metadata literacy in the age of AI. Previous discussions often defined metadata literacy as knowledge of descriptive structures or skills in creating and using metadata records. But this understanding is no longer enough – though still necessary – when AI systems create, transform, rank, summarise and recommend information at scale. In such environments, metadata is not simply about post hoc description of resources; it structures provenance, visibility, accountability, cultural representation, and the conditions under which machine outputs can be interpreted and trusted. Using metadata, metadata instruction, AI literacy, and information literacy scholarship, this conceptual paper presents a reconstructed model of metadata literacy for LIS education. The model is built on five dimensions: understanding of infrastructure, contextual description and representation, provenance and disclosure, evaluation of algorithmically mediated outputs and intervention in terms of ethics and governance. The paper also gives examples of learning tasks and assessment evidence to illustrate how the model can be applied. It argues for viewing metadata literacy not as a narrow technical specialisation but as a fundamental educational response to AI-mediated knowledge environments. Dublin Core Metadata Initiative 2026-09-10 info:eu-repo/semantics/conferenceObject Text application/pdf text/html https://doi.org/10.23106/dcmi.952637945 https://dcpapers.dublincore.org/article/952637945 Dublin Core Metadata Initiative Conference Proceedings eng info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/