AI RESEARCH
From Learning Resources to Competencies: LLM-Based Tagging with Evidence and Graph Constraints
arXiv CS.AI
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ArXi:2605.28483v1 Announce Type: new Linking learning resources to a structured competency framework is key to enabling competency-based search and curriculum analytics in Learning Management Systems (LMS). However, manual tagging is labor-intensive, and fully automatic methods often lack transparency. In this paper, we present an end-to-end alignment pipeline that uses a large language model (LLM) as a constrained, evidence-producing tagger. LMS resources -both instructional content and assessments -are first segmented into meaningful pedagogical fragments.