RAPID: DRL AI: Understanding Perceptions and Use of AI in K-12 Education Using a Nationally Representative Sample

RAPID：DRL AI：使用全国代表性样本了解 K-12 教育中 AI 的认知和使用

• 批准号: 2334172
• 负责人: Candice Odgers
• 金额: $ 19.95万
• 依托单位: University of California-Irvine
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2024-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2334172&HistoricalAwards=false
• 关键词: RAPID; DRL; AI; Understanding; Perceptions

Schoolchildren are exposed to hundreds of digital tools each year, many of which are already driven by AI technologies. Parents and teachers must consider how to incorporate these learning tools into their daily lives at a rapid pace. Yet, very little is known about the current use and perceptions of AI among these key stakeholders. This time-sensitive RAPID project will identify the opportunities and challenges that arise for parents, teachers, and youth regarding the use of these AI-driven technologies in K-12 education. Specifically, it will identify risks of generative AI in educational settings and explore opportunities for supporting future design and engagement, including supports for teacher training and regulation in educational contexts. Findings will have theoretical and practical relevance for education, child development, technology design, and policy. Results will also support policymakers as they work to establish guidelines and regulations to protect youth’s privacy, safety, and well-being in the context of AI interactions. Ideally, this work will inform how AI might be used to close versus widen existing disparities and learning gaps in youth. 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.The study employs a large stratified random sample of parents, teachers, and youth across age, gender, socio-economic status, and geographical location. The probability-based nationally representative sample will be drawn from the NORC AmeriSpeak panel. The survey includes both open and close-ended questions that focus on use, perception, and trust in AI systems. Questions will probe how youth engage with generative AI as well as more traditional forms of AI in education, such as personalized and adaptive learning. An embedded experimental manipulation within the survey will test how participants evaluate AI-powered versus non-AI powered educational platforms with respect to usefulness, expertise, and trust. Qualitative interviews augment the survey findings, relying on remote participation to ensure broad geographic representation in a very short time window. Research materials will be made available as part of an online toolkit, enabling multiple investigators to use them across their studies and pool the data for future analyses through an open science approach. This large-scale mixed methods study will generate knowledge to directly inform policy guidelines regarding youth’s safety, privacy, and well-being in AI interactions. It is also positioned to help build design guidelines for AI product developers that prioritize child well-being, learning, and development.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.

学生每年都会接触到数百种数字化工具，其中许多已经由人工智能技术驱动。家长和教师必须考虑如何将这些学习工具快速融入他们的日常生活。然而，人们对这些关键利益相关者目前对人工智能的使用和看法知之甚少。这个时间敏感的RAPID项目将确定在K-12教育中使用这些人工智能驱动的技术为家长，教师和青少年带来的机遇和挑战。具体而言，它将确定教育环境中生成人工智能的风险，并探索支持未来设计和参与的机会，包括支持教育环境中的教师培训和监管。调查结果将对教育，儿童发展，技术设计和政策具有理论和实践意义。研究结果还将支持政策制定者制定指导方针和法规，以在人工智能互动的背景下保护青少年的隐私、安全和福祉。理想情况下，这项工作将告知如何使用人工智能来缩小与扩大青年人现有的差距和学习差距。本提案是对亲爱的同事信（DCL）的回应：在正式和非正式环境中快速加速人工智能在K-12教育中的研究（NSF 23-097），并由学生和教师创新技术经验（ITEST）计划资助，该计划支持建立对实践，计划要素，背景和过程有助于增加学生对科学、技术、工程和数学（STEM）以及信息和通信技术（ICT）职业的知识和兴趣。这项研究采用了一个大型分层随机样本，包括家长、教师和不同年龄的青年，性别、社会经济地位和地理位置。基于概率的全国代表性样本将从NORC AmeriSpeak小组中抽取。该调查包括开放式和封闭式问题，重点关注人工智能系统的使用，感知和信任。问题将探讨青年如何参与生成AI以及教育中更传统的AI形式，例如个性化和自适应学习。调查中的嵌入式实验操作将测试参与者如何评估人工智能驱动的教育平台与非人工智能驱动的教育平台在有用性，专业知识和信任方面的差异。定性访谈扩大了调查结果，依靠远程参与，以确保在很短的时间内具有广泛的地域代表性。研究材料将作为在线工具包的一部分提供，使多名研究人员能够在其研究中使用这些材料，并通过开放科学方法汇集数据，供未来分析使用。这项大规模的混合方法研究将产生知识，直接为人工智能互动中青少年的安全、隐私和福祉提供政策指导。该奖项反映了NSF的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。