Integrating Artificial Intelligence with Smart Engineering and English Language Arts in Upper Elementary Education

该项目将培养小学高年级学生在未来的职业生涯中使用人工智能（AI）的能力。人工智能将成为影响和提高未来工作生产力的关键工具。因此，向K-12学生介绍基本的人工智能知识和技能，熟悉人工智能技术，培养学生在劳动力中具有竞争力变得越来越重要。通过这个项目，马萨诸塞州塔夫茨大学和密苏里州圣路易斯玛丽维尔大学的机器人和教育研究人员团队将与圣路易斯县的50多名教师合作，开发一个以研究为基础的教育生态系统，将人工智能概念引入高年级小学生。这个生态系统将包括一个新颖的、低成本的、支持人工智能的硬件工具集，包括传感器、执行器和微控制器等组件，供学生构建智能系统，并支持教师的专业发展。通过课后和暑期项目，该项目将吸引1000多名圣路易斯县学生参与，为学生在英语语言艺术和暑期阅读项目中阅读的虚构故事中提出的问题构建功能性人工智能解决方案。这种方法的目标是鼓励人工智能、工程和读写能力交叉的跨学科学习。教育项目测试将包括12名教师和500名来自小学高年级目标受众的学生，以及其他K-12年级的试点测试参与者。该项目旨在生成一个新的模型，向小学生介绍重要的人工智能概念，减少将计算思维融入学校课程的障碍，并为学生提供有形的、可训练的人工智能表示，供学生探索。研究人员将探讨三个主要研究问题：1)有形人工智能元素的引入如何导致小学高年级学生对人工智能概念的理解和对人工智能的态度发生变化？2)有形人工智能学习工具的不同复杂程度和多样性如何影响学生的参与度及其解决方案和设计的多样性？3)在综合工程和识字活动中引入有形人工智能元素的潜在好处和挑战是什么？项目团队将采用基于设计的研究（DBR）方法，在迭代设计和开发工具集、专业发展和活动的同时，共同产生跨学科教育和学习科学理论。该研究将包括对人工智能专业人士的访谈和调查，以开发和验证适合年级的学生对人工智能概念和态度的理解措施。该团队将使用混合方法分析方法评估研究问题，三角测量来自教师访谈的定性数据，课程和专业发展观察，学生制作的工件分析，以及基于工件的学生访谈以及来自教师和学生调查的定量数据。该项目的贡献将使人工智能教育范式转向融合课程，摆脱编码和计算需要单独教学的现状。该项目的研究结果将有助于向该领域介绍小学高年级人工智能教育面临的具体挑战。该项目的可交付成果将包括人工智能动画发明（AI2）硬件工具集、教师专业发展模型、示例活动和学生作业库，以及项目有效性的衡量标准，以及用于学习人工智能概念的有形人工智能元素的可用性和实用性。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。

This project will develop upper elementary school students’ abilities to work with Artificial intelligence (AI) in future careers. AI will be a critical tool for influencing and increasing productivity in the future of work. As such, it is increasingly important to introduce K-12 students to basic AI knowledge and skills, build familiarity with AI technologies, and train students to be competitive in the workforce. Through this project, a team of robotics and education researchers at Tufts University in Massachusetts and Maryville University in St. Louis, MO will work with over 50 teachers in St. Louis County to develop a research-informed educational ecosystem bringing AI concepts to upper elementary school students. This ecosystem will include a novel, low-cost, AI-enabled hardware toolset, including components such as sensors, actuators, and a microcontroller, for students to build smart systems, as well as support for teacher professional development. Through after-school and summer programs, the project will engage over 1000 St. Louis County students in constructing functional AI-enabled solutions to problems presented in fictional stories that the students read in English language arts and summer reading programs. The goal of the approach is to encourage transdisciplinary learning at the intersection of AI, engineering, and literacy. The education program testing will include 12 teachers and 500 students from the upper elementary target audience, with other participants in pilot testing across the K-12 grade band. The project aims to generate a new model for introducing vital AI concepts to elementary students that reduces barriers to integrating computational thinking into school curricula and provides tangible, trainable representations of AI for students to explore.Researchers will investigate three primary research questions: 1) How does the introduction of tangible artificial intelligence elements lead to changes in upper elementary students’ understanding of artificial intelligence concepts and attitudes towards artificial intelligence? 2) How do different levels of complexity and variety of tangible artificial intelligence learning tools impact students' engagement and the diversity of their solutions and designs? 3) What are the potential benefits and challenges of introducing tangible artificial intelligence elements in integrated engineering and literacy activities? The project team will apply a design-based research (DBR) approach to jointly generate interdisciplinary education and learning sciences theory alongside iteratively designing and developing the toolset, professional development, and activities. The research will include interviews and surveys with AI professionals to develop and validate grade-appropriate measures of students’ understanding of AI concepts and attitudes. The team will evaluate the research questions with a mixed-methods analytic approach, triangulating qualitative data from teacher interviews, lesson and professional development observations, student-made artifact analysis, and artifact-based student interviews with quantitative data from teacher and student surveys. The project’s contribution will shift the artificial intelligence education paradigm towards a convergent curriculum and away from the status quo of coding and computing requiring separate instruction. The project findings will help inform the field about challenges specific to AI education in upper elementary grades. The deliverables from this project will include the AI Animated Inventions (AI2) hardware toolset, a teacher professional development model, a gallery of example activities and student work, and measures of the program’s effectiveness, as well as the usability and utility of the tangible artificial intelligence elements for learning AI concepts.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.