用AI助教在Moodle上实现无幻觉深度教学，学生获苏格拉底式辅导。
From Surface Learning to Deep Understanding: A Grounded AI Tutoring System for Moodle
- 基于RAG技术，用教师材料约束LLM输出防幻觉。
- 评估显示回答忠实度达0.97，用户推荐率4.00/5.00。
- 适合需要精准教学的教育者与追求深度理解的学生。
本演示论文介绍了一款名为AI Teaching & Learning Assistant的模块化Moodle插件，利用检索增强生成（RAG）技术提供高质量、无幻觉的教育支持。系统采用双中心设计，为学生提供基于苏格拉底提问的交互式辅导，为教师提供‘人在回路’的内容生成工作台。通过将大型语言模型（LLM）的回答扎根于教师提供的材料，该系统有效降低错误信息风险，促进深层概念掌握。借助Ragas（LLM作为裁判）框架及初步用户研究评估，系统在忠实度上达到最高0.97分，用户推荐率达4.00/5.00。
原文摘要 · Abstract (English)
This demo paper describes the development of the AI Teaching \& Learning Assistant, a modular Moodle plugin that leverages Retrieval-Augmented Generation (RAG) to deliver high-quality, hallucination-free education. The system employs a dual-centric design, providing students with interactive, Socratic-based tutoring and educators with a "human-in-the-loop" workspace for supervised content generation. By grounding Large Language Model (LLM) responses in teacher-provided materials, the assistant addresses the risks of misinformation while encouraging deep conceptual mastery. Evaluation via the Ragas (LLM-as-a-Judge) framework and a preliminary user study confirms its effectiveness, achieving faithfulness scores up to 0.97 and a 4.00/5.00 recommendation rate.
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