Collaborative Research: STEM Learning Embedded in a Machine-in-the-LoopCollaborative Story Writing Game

培养“21世纪技能”，如协作、沟通、批判性思维和创造力（4c），对于学生们跟上未来不断变化的劳动力市场变得越来越重要。有效和高效地教授4c需要将其与核心内容知识领域深度交织，因为领域知识的获取可以促进学生这些软技能的发展。在这个项目中，研究人员通过开发一个协作写作游戏，将4C技能发展与STEM教育结合起来，在这个游戏中，多名学生一起围绕嵌入式STEM教育元素编写故事。作为一项关键创新，研究人员将在这个协作写作游戏中嵌入自然语言处理和基于人工智能（AI）的工具，以自动检查事实、反馈、知识追踪和叙述故事弧建议，这将促进学生向精通的方向发展，同时减少教师的工作量。总体而言，该项目有可能提高学生对STEM学习活动的参与度，并改善学习成果。该项目将以合作故事写作平台StoriumEdu为基础，因此直接受益于其2000个K-12教室的用户群，超过27,000名学生，并可能通过传播团队的研究成果而使更多的学生受益。这个项目的主要技术目标是用基于人工智能的工具来增强科学写作指导。为了实现这些目标，该项目将开发自动提供写作辅助和反馈的新技术，这些工具将通过StoriumEdu平台部署到K-12教室，以评估其有效性。一个核心的技术挑战是通过建立用于事实核查的机器学习模型来评估学生写作的真实性。该团队建议设计检索增强神经网络，可以定位学生写的文本中表现出科学误解的跨度。然后，这些段落将与教科书或在线文章中的相关段落联系起来，使学生能够轻松地纠正错误。在开发了事实核查方法之后，该团队还将专注于知识追踪，这可以根据学生掌握或仍在努力学习的概念来衡量学生的进步。知识追踪模型将根据科学素养专家的反馈进行开发。这些模型的输出通知了这个项目的最后一个方面，其目的是产生与概念误解相关的叙事进展。这将允许学生更强烈地参与到他们尚未掌握的概念中，从而最大限度地发挥写作平台的教学潜力。总体而言，本项目的研究贡献将新颖的NLP方法与教育进度跟踪和反馈系统相结合，以改善STEM学习。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

Developing “21st century skills” such as collaboration, communication, critical thinking, and creativity (the 4Cs) has become increasingly important for students to keep up with the ever-evolving labor market of the future. Teaching the 4Cs effectively and efficiently requires deeply intertwining them with core content knowledge areas, since the acquisition of domain knowledge can bolster students’ development of these soft skills. In this project, the investigators take a step towards combining 4C skill development with STEM education by developing a collaborative writing game in which multiple students work together to craft a narrative around embedded STEM education elements. As a key innovation, the investigators will embed this collaborative writing game with natural language processing and artificial intelligence (AI)-based tools to automate fact-checking, feedback, knowledge tracing, and narrative story arc suggestions, which will facilitate students’ progress toward mastery while reducing teacher workload. Overall, this project has the potential to increase student engagement in STEM learning activities and improve learning outcomes. The project will be grounded in StoriumEdu, a collaborative story writing platform, therefore directly benefiting its user base of 2,000 K-12 classrooms with over 27,000 students and potentially an even larger number of students through the dissemination of the team’s research findings. This major technical goals of this project are intended to augment scientific writing instruction with AI-based tools. To achieve these goals, the project will develop novel technologies that automatically provide writing assistance and feedback, and these tools will be deployed into K-12 classrooms via the StoriumEdu platform in order to evaluate their effectiveness. A core technical challenge is to assess the factuality of student writing by building machine learning models for fact-checking. The team proposes to design retrieval-augmented neural networks that can localize spans within student-written text that exhibit scientific misunderstandings. These spans will then be connected with relevant passages from textbooks or online articles to enable students to easily correct their errors. After developing fact-checking methods, the team will also focus on knowledge tracing, which allows measuring student progress over time in terms of which concepts they have mastered or are still struggling with. The knowledge tracing models will be developed with feedback from scientific literacy experts. The output of these models informs the final aspect of this project, which aims to generate narrative progressions associated with conceptual misunderstandings. This will allow students to engage more strongly with concepts that they have yet to master, which maximizes the writing platform’s pedagogical potential. Taken as a whole, this project’s research contributions synthesize novel NLP methods with educational progress tracking and feedback systems in an effort to improve STEM learning.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.