Incorporating Generative AI (GenAI) and Large Language Models (LLMs) in
education can enhance teaching efficiency and enrich student learning. Current
LLM usage involves conversational user interfaces (CUIs) for tasks like
generating materials or providing feedback. However, this presents challenges
including the need for educator expertise in AI and CUIs, ethical concerns with
high-stakes decisions, and privacy risks. CUIs also struggle with complex
tasks. To address these, we propose transitioning from CUIs to user-friendly
applications leveraging LLMs via API calls. We present a framework for
ethically incorporating GenAI into educational tools and demonstrate its
application in our tool, Feedback Copilot, which provides personalized feedback
on student assignments. Our evaluation shows the effectiveness of this
approach, with implications for GenAI researchers, educators, and
technologists. This work charts a course for the future of GenAI in education.

将生成式 AI（GenAI）和大型语言模型（LLMs）应用于教育可以提高教学效率，丰富学生学习。使用当前的 LLM 涉及到会话式用户界面（CUIs）用于生成材料或提供反馈，但这带来了教育者在 AI 和 CUI 领域的专业知识需求、高风险决策的道德问题以及隐私风险。为了解决这些问题，我们建议从 CUIs 过渡到通过 API 调用利用 LLMs 的用户友好应用程序。我们提出了一个将 GenAI 道德地融入教育工具的框架，并展示了其在我们的工具 Feedback Copilot 中的应用，该工具为学生作业提供个性化反馈。我们的评估结果显示了这种方法的有效性，对 GenAI 研究人员、教育者和技术人员具有重要意义。这项工作为教育中的 GenAI 未来制定了一条路线。