LangLingual：一种利用大型语言模型的个性化、练习导向型英语学习工具
LangLingual: A Personalised, Exercise-oriented English Language Learning Tool Leveraging Large Language Models
AI总结：
本文介绍LangLingual，一个基于LangChain和大型语言模型的对话代理，提供实时语法反馈、上下文感知练习和进度跟踪，评估显示可用性强、学习效果积极。
摘要：
语言教育工作者致力于为学习者创造丰富的学习体验，但他们在能够提供的反馈和练习范围上可能受到限制。我们介绍了LangLingual的设计与开发，这是一个基于LangChain框架构建并由大型语言模型驱动的对话代理。该系统专门设计用于提供实时的、以语法为重点的反馈，生成上下文感知的语言练习，并随时间跟踪学习者的熟练程度。本文详细讨论了LangLingual的架构、实现和评估。结果表明，该系统具有强大的可用性、积极的学习成果和令人鼓舞的学习者参与度。
英文摘要：
Language educators strive to create a rich experience for learners, while they may be restricted in the extend of feedback and practice they can provide. We present the design and development of LangLingual, a conversational agent built using the LangChain framework and powered by Large Language Models. The system is specifically designed to provide real-time, grammar-focused feedback, generate context-aware language exercises and track learner proficiency over time. The paper discusses the architecture, implementation and evaluation of LangLingual in detail. The results indicate strong usability, positive learning outcomes and encouraging learner engagement.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
