Software modeling education often lacks immediate and personalized feedback, making it challenging for novice learners to comprehend modeling principles. This paper continues our ongoing work on developing an AI-driven feedback mechanism to support UML diagram construction. Building on previous efforts, we improved the system by enhancing the RAG-LLM component within the existing UML Miner plugin. The system analyzes students’ modeling behavior and provides real-time, personalized guidance to support learning and improve modeling skills.
A RAG-Enhanced AI Feedback for UML Education
Ardimento, Pasquale
;Scalera, Michele
2025-01-01
Abstract
Software modeling education often lacks immediate and personalized feedback, making it challenging for novice learners to comprehend modeling principles. This paper continues our ongoing work on developing an AI-driven feedback mechanism to support UML diagram construction. Building on previous efforts, we improved the system by enhancing the RAG-LLM component within the existing UML Miner plugin. The system analyzes students’ modeling behavior and provides real-time, personalized guidance to support learning and improve modeling skills.File in questo prodotto:
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