RAG Learner: An Interactive Tool for Teaching Retrieval-Augmented Generation
Abstract
Large language models have made AI literacy an essential graduate skill, yet underlying architectures like Retrieval-Augmented Generation (RAG) remain inaccessible to most students, particularly outside specialist computing programmes. We designed RAG Learner as an interactive tool to teach core RAG concepts through structured modules; its evaluation with 26 university participants demonstrated significant learning gains (55.8% to 88.5%, p < 0.001) alongside consistently high perceived effectiveness (mean 3.78/4.0).
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