Integration of generative artificial intelligence (GenAI) in metadata training
DOI:
https://doi.org/10.47989/ir31iConf64272Keywords:
Generative Artificial Intelligence training, Metadata creation and management, Metadata quality assessments, Cataloging with Artificial IntelligenceAbstract
Introduction. GenAI tools are adopted by information professionals globally, including GenAI incorporation into metadata workflows in archives and libraries. Researchers and practitioners emphasise the critical need for GenAI learning integration into coursework to prepare iSchools graduates for this emerging professional demand. While reports on GenAI content integration in iSchools curricula are increasing, there is a lack of publications about GenAI integration in courses focusing on digital repository metadata.
Method. University of North Texas recently integrated GenAI practical metadata learning in an advanced graduate course. This paper describes this integration and reports results of its testing.
Analysis. The author performed qualitative and quantitative analyses of practical assignment submissions in which students used GenAI tools for generating metadata records and evaluated the process and outcomes.
Results. AI-generated metadata varied in completeness depending on the GenAI tool, its version, and prompt used, while typically lacking accuracy. Students expressed appreciation of this practical experience, reported developing greater confidence in using GenAI tools and understanding their advantages and disadvantages in metadata work, demonstrated development of analytical and troubleshooting skills.
Conclusion. This paper is expected to be useful for iSchools metadata educators, researchers, and practitioners.
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