RAPID: DRL AI: Constructing Understandings of Generative AI and Machine Learning with High School Youth

RAPID：DRL AI：与高中生一起构建对生成式 AI 和机器学习的理解

• 批准号: 2335926
• 负责人: Antero Garcia
• 金额: $ 20万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-12-01 至 2024-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2335926&HistoricalAwards=false
• 关键词: RAPID; DRL; AI; Constructing; Understandings; RAPID; DRL; AI; Constructing; Understandings

This project explores how high school youth communicate with AI tools and assesses how they learn to use AI tools in context. Though students are using these tools widely, inciting much public discourse, very little is known about how, why, and when they use AI tools, or what they understand about the tools. Through curricular exploration, this study evaluates how historically marginalized high school youth of color interact with AI tools to write papers, write program code, or study for science tests. This proposal was received in response to the Dear Colleague Letter (DCL): Rapidly Accelerating Research on Artificial Intelligence in K-12 Education in Formal and Informal Settings (NSF 23-097) and funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers.Through a one-year study, researchers will pilot generative AI activities in classrooms and out-of-school clubs; collect quantitative data, logs, video data, screen recordings, and artifactual data; and analyze those data to find mechanistic explanations and generalizable models of how students are interacting with and learning AI content. Offering a foundational perspective for AI-related learning and augmentation, this study is a crucial and time-sensitive first step, required before scalable interventions and curriculum development. The research questions guiding the study are (1) How do students and teachers learn to communicate with generative AI? (2) How do learners demonstrate their understanding of AI and predict AI responses in order to yield desired results? and (3) How do students compare AI to their own cognitive strategies? The project has multiple potential transformative outcomes including a model for how students and teachers understand generative AI; a curriculum for teaching students and teachers how to use generative AI ethically and meaningfully; and new possibilities for using generative AI in education. Research findings, instructional materials and teacher professional development guidelines will be shared with and distributed to the research and practitioner communities.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.

该项目探讨了高中青年如何与AI工具沟通，并评估他们如何在上下文中使用AI工具。尽管学生正在广泛使用这些工具，煽动公众的讨论，但对如何，为什么以及何时使用AI工具或他们对工具的理解知之甚少。通过课程探索，这项研究评估了历史上边缘化的高中青年与AI工具相互作用，以编写论文，编写程序代码或研究科学测试。 This proposal was received in response to the Dear Colleague Letter (DCL): Rapidly Accelerating Research on Artificial Intelligence in K-12 Education in Formal and Informal Settings (NSF 23-097) and funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and数学（STEM）以及信息与通信技术（ICT）职业。通过一年的研究，研究人员将在教室和学校外俱乐部进行生成AI活动；收集定量数据，日志，视频数据，屏幕记录和人为数据；并分析这些数据，以查找学生如何与学生进行互动和学习AI内容的机械解释和可推广模型。这项研究提供了与AI相关的学习和增强的基础观点，是至关重要的，时间敏感的第一步，在可扩展干预和课程开发之前需要进行。指导研究的研究问题是（1）学生和老师如何学会与生成AI进行交流？ （2）学习者如何展示他们对AI的理解并预测AI响应以产生预期的结果？ （3）学生如何将AI与自己的认知策略进行比较？该项目具有多种潜在的变革性结果，包括学生和教师如何理解生成性AI的模型；一种教学课程，用于教学学生和老师如何在道德和有意义上使用生成的AI；以及在教育中使用生成AI的新可能性。研究结果，教学材料和教师专业发展指南将与研究和从业人员社区共享并分发给研究和分发。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响审查标准，认为值得通过评估来获得支持。