Earthquaker-AI: A Retrieval-Augmented Generation Framework with Rubric-Based Assessment for Primary School Earthquake Education

  • 类型：arxiv
  • 标识：2607.14046
  • 链接：http://arxiv.org/abs/2607.14046v1
  • 主分类：rag
  • 形态：method
  • 被引：0
  • 被引来源：Semantic Scholar + OpenAlex
  • S2被引：0
  • OpenAlex被引：0
  • 影响力被引：0
  • TLDR：This paper presents Earthquaker-AI, a hybrid educational framework building upon a previously implemented educational robotics project by integrating a conversational AI assistant based on Retrieval-Augmented Generation. It aims to enhance earthquake preparedness and conscious action among primary-school students. The system extends the award-winning STEM project Earthquaker moving from mechanical simulation with Lego WeDo2 to cognitive and metacognitive processing. The robotics component uses Lego WeDo2 automation to simulate seismic response, letting students interact with sensors and actuat
  • OpenAlex ID：W7168516166
  • OpenAlex DOI：10.48550/arxiv.2607.14046
  • DOI：10.48550/arxiv.2607.14046
  • DOI来源：OpenAlex
  • 开放获取：green
  • 开放获取链接：https://doi.org/10.48550/arxiv.2607.14046
  • OpenAlex更新：2026-07-19
  • 待LLM分类：否
  • 标题中文：Earthquaker-AI：面向小学地震教育的、采用评分量表评估的 RAG 框架
  • TLDR中文：本文提出 Earthquaker-AI，一个混合式教育框架，在已有教育机器人项目基础上集成基于 RAG 的对话式 AI 助手，旨在提升小学生的地震应急准备与主动行动意识。该系统将曾获奖的 STEM 项目 Earthquaker 从 Lego WeDo2 的机械模拟拓展至认知与元认知层面：机器人组件利用 Lego WeDo2 自动化模拟地震响应，使学生能够与传感器和执行器进行交互。
  • 来源文件：
  • /inbox/tom/_candidates/2026-07-17-agent-rag-longcontext-candidates.json
  • [S2 enrich]
  • [OpenAlex backfill]