与中小学教师共研大模型工具，助力项目式学习落地。
Co-designing Large Language Model Tools for Project-Based Learning with K12 Educators
- 联合多学科教师通过访谈与工作坊，共同设计支持项目式学习的LLM工具。
- 教师希望工具能自动化重复任务，提升个性化教学效率。
- 提出适配教育场景的设计指南，关注伦理与教师角色增效。
生成式AI，尤其是大语言模型（LLMs），为以学生为中心的项目式学习（PBL）提供了新可能。然而，教师在项目设计、管理、评估以及平衡指导与自主性方面面临实际挑战。本研究通过与跨学科中小学教师的合作，开展访谈、协作工作坊及原型迭代设计，探索如何利用LLM支持高质量的PBL教学实践。研究发现，教师期望工具能自动化常规任务、增强个性化学习，并促进自身专业发展，而非取代其角色。同时，教师也指出课堂整合中的资源需求、伦理问题及短期与长期影响等挑战。基于此，本文提出面向未来部署的LLM工具设计指南。
原文摘要 · Abstract (English)
The emergence of generative AI, particularly large language models (LLMs), has opened the door for student-centered and active learning methods like project-based learning (PBL). However, PBL poses practical implementation challenges for educators around project design and management, assessment, and balancing student guidance with student autonomy. The following research documents a co-design process with interdisciplinary K-12 teachers to explore and address the current PBL challenges they face. Through teacher-driven interviews, collaborative workshops, and iterative design of wireframes, we gathered evidence for ways LLMs can support teachers in implementing high-quality PBL pedagogy by automating routine tasks and enhancing personalized learning. Teachers in the study advocated for supporting their professional growth and augmenting their current roles without replacing them. They also identified affordances and challenges around classroom integration, including resource requirements and constraints, ethical concerns, and potential immediate and long-term impacts. Drawing on these, we propose design guidelines for future deployment of LLM tools in PBL.
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