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.

翻译：人工智能工具，特别是大语言模型，近来在学习管理系统和在线教育项目中已证明其有效性。由于反馈在学校的学习与评估中持续发挥着关键作用，教育工作者必须审慎定制人工智能工具的使用，以最优方式支持学生的学习进程。改进教育反馈系统的努力在研究文献中已有诸多尝试，但大多侧重于将人工智能反馈与人工生成反馈进行定性基准比较。本文探索了一种替代性反馈框架，该框架通过集成嵌入技术扩展了ChatGPT的能力，从而实现对教育材料更细致的理解，并为基于测验的评估提供主题定向反馈。作为研究的一部分，我们提出并开发了概念验证解决方案，在开放式问题和多项选择题上分别实现了90%和100%的有效率。结果表明，我们的框架不仅超越了预期，还能与人工叙述相媲美，凸显了人工智能在革新教育反馈机制方面的潜力。