Project Profile

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.