使用生成式 AI 的在线教育项目个性化反馈框架
Personalised Feedback Framework for Online Education Programmes Using Generative AI
AI总结：
本文提出一种扩展 ChatGPT 能力的个性化反馈框架，通过集成 embeddings 实现对教育材料的细致理解，为基于测验的评估提供针对特定主题的反馈，其概念验证方案在开放式和多选题上分别达到 90% 和 100% 的有效率，展现出媲美人类叙述的潜力。
摘要：
AI 工具，特别是大型语言模块，最近已在学习管理系统和在线教育项目中证明了其有效性。由于反馈在学校的学习和评估中继续发挥着至关重要的作用，教育工作者必须仔细定制 AI 工具的使用，以便在学生的学习旅程中提供最佳支持。改善教育反馈系统的努力在研究中已有许多尝试，但大多集中于将 AI 反馈与人类生成的反馈进行定性基准测试。本文探讨了一种替代反馈框架，该框架通过集成 embeddings 扩展了 ChatGPT 的能力，从而能够更细致地理解教育材料，并为基于测验的评估提供针对特定主题的反馈。作为研究的一部分，我们提出并开发了一个概念验证解决方案，针对开放式问题和多选题分别实现了 90% 和 100% 的有效率。结果表明，我们的框架不仅超出了预期，而且可与人类叙述相媲美，突显了 AI 在彻底改变教育反馈机制方面的潜力。
英文摘要：
AI tools, particularly large language modules, have recently proven their effectiveness within learning management systems and online education programmes. As feedback continues to play a crucial role in learning and assessment in schools, educators must carefully customise the use of AI tools in order to optimally support students in their learning journey. Efforts to improve educational feedback systems have seen numerous attempts reflected in the research studies but mostly have been focusing on qualitatively benchmarking AI feedback against human-generated feedback. This paper presents an exploration of an alternative feedback framework which extends the capabilities of ChatGPT by integrating embeddings, enabling a more nuanced understanding of educational materials and facilitating topic-targeted feedback for quiz-based assessments. As part of the study, we proposed and developed a proof of concept solution, achieving an efficacy rate of 90% and 100% for open-ended and multiple-choice questions, respectively. The results showed that our framework not only surpasses expectations but also rivals human narratives, highlighting the potential of AI in revolutionising educational feedback mechanisms.
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。
