RAPID: DRL AI: A Career-Driven AI Educational Program in Smart Manufacturing for Underserved High-school Students in the Alabama Black Belt Region

人工智能(AI)与先进制造业的融合在智能制造领域具有革命性的生产力和创造新的就业机会的潜力。由于大多数K-12教育工作者和学校缺乏向学生传授智能制造人工智能技能的知识和经验，迫切需要调查“教什么”和“如何教”人工智能，以便为未来的劳动力培养必要的人工智能技能。该项目将启动一个适合高中生年龄的、以职业为导向的AI教育计划，并对其效果进行评估。教育研究人员将开发特定于制造业的人工智能学习模块，向高中生传授熔丝制造(FFF)，这是最容易获得的添加剂制造(AM)过程，将配备自动实时过程监控、分析和通信。来自黑带地区和阿拉巴马州农村低收入地区的50名高中生将被招募参加为期一周的夏令营。这些地区52.2%的非裔美国人是非洲裔美国人，家庭年收入中位数为27,130美元。这个智能制造中的人工智能教育项目将采用基于项目的学习，以激发不同学生对职业的更广泛兴趣。我们收到这份建议书是为了回应尊敬的同事来信(DCL)：“在正规和非正式环境下，快速加速K-12教育中人工智能的研究(NSF 23-097)”，并由学生和教师创新技术体验(ITEST)计划资助，该计划支持一些项目，这些项目建立对实践、计划要素、背景和过程的理解，有助于提高学生对科学、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。该项目的目标是调查智能制造背景下与年龄相适应的人工智能学习和包容性教学。研究计划包括：(1)识别高中生智能制造所需的人工智能知识和技能；(2)试验基于项目的学习(PBL)教学法，为学生探索智能制造做好准备，并为教师提供人工智能和智能制造方面的专业培训；(3)采用混合方法设计，结合定性访谈和工作表数据以及定量的事后知识评估，评估拟议的人工智能教育干预措施的效果。除了50名服务不足的学生外，还将招募10名高中教师在学生夏令营前接受为期3天的强化专业培训，并将为夏令营活动提供便利。这些教师还将制定教案，以便在各自的学校继续进行人工智能教育干预。由此产生的成果包括人工智能学习模块和以智能制造为中心的PBL教学法。开发这种人工智能干预的实验过程可以适用于其他针对服务不足的高中的人工智能教育努力。对拟议的人工智能教育干预的有效性所获得的见解将为在不同的K-12人工智能教育项目中推进适龄、面向未来职业和公平的人工智能教育提供宝贵的经验教训。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

The integration of artificial intelligence (AI) into advanced manufacturing has promising potential to revolutionize productivity and generate new jobs in smart manufacturing. There is an urgent need to investigate "what to teach" and "how to teach" AI in order to prepare future workforce with the necessary AI skills, as most K-12 educators and schools lack the knowledge and experience to teach students AI skills for smart manufacturing. This project will initiate an age-appropriate career-driven AI educational program for high-school students and evaluate its effectiveness. Education researchers will develop manufacturing specific AI learning modules to teach high school students about Fused Filament Fabrication (FFF), the most accessible additive manufacturing (AM) process, that will be equipped with automatic real-time process monitoring, analysis and communication. Fifty rising high-school students from underserved school districts across the Black Belt region and rural low-income areas of Alabama, where 52.2% are African Americans and the median household annual income is $27,130, will be recruited to participate in a one-week summer camp. This AI in smart manufacturing education program will employ project-based learning to stimulate broader career interest among a diverse range of students. The 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 goal of the project is investigating age-appropriate equitable AI learning and inclusive teaching in the context of smart manufacturing. The research plan includes: (1) identify AI knowledge and skills required in smart manufacturing for high-school students; (2) experiment with project-based learning (PBL) pedagogy to prepare students to explore smart manufacturing and provide professional training in AI and smart manufacturing for teachers; (3) use a mixed method design with qualitative interview and worksheet data as well as quantitative pre-post knowledge assessment to evaluate the effectiveness of the proposed AI educational intervention. In addition to the fifty underserved students, ten high-school teachers will be recruited to receive a three-day intensive professional training before the student summer camp and will facilitate the summer camp activities. These teachers will also develop a lesson plan for continuing the AI educational intervention at their respective schools. The resulting deliverables include the AI learning modules and the smart manufacturing centered PBL pedagogy. The experimental process in developing this AI intervention can be adapted for other AI educational efforts for underserved high schools. The insights gained on the effectiveness of the proposed AI educational intervention will provide valuable lessons for advancing age-appropriate, future career-oriented, and equitable AI education across different K-12 AI educational programs.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.