A new project, funded by the NSF Discovery Research PreK-12 program, will focus on engaging high school students in integrated computer science and engineering through hands-on experiences with microelectronics and artificial intelligence. This approach will pioneer a hardware-focused approach to AI education in K-12 classrooms.
Warren B. Nelms Institute researchers Dr. Pasha Antonenko, Dr. Swarup Bhunia, and Dr. Andrea Ramirez-Salgado are collaborating with Dr. Lauren Eutsler from the University of North Texas, and Dr. Tamzidul Hoque from the University of Kansas.
“We are co-designing the curriculum in close collaboration with high school computer science and computer engineering teachers from the three participating states,” said Dr. Ramirez-Salgado. “The project launched this spring, and as part of our initial activities, we met in January with teachers from three high schools in Texas, one in Kansas, and one in Florida.”
The participating schools are P.K. Yonge Developmental Research School in Florida, Walnut Grove High School, Little Elm High School, and Martin High School in Texas, and Shawnee Mission West High School in Kansas.
Abstract:
Society has grown to rely on smart, embedded, and interconnected systems. This has created a great need for well-qualified and motivated engineers, scientists, and technicians who can design, develop, and deploy innovative microelectronics and Artificial Intelligence (AI) technologies, which drive these systems. This project will address the need for a more robust computer science and engineering workforce, a matter of national security, by broadening access to microelectronics and AI education leveraging the cutting-edge technologies of Tiny Machine Learning and low-cost microcontroller systems in diverse Florida, Kansas, and Texas high schools. This project will leverage the partnership with the Scientist for Every Florida School network and nurture new relationships with industry partners. The goal of this project is to engage about 500 high-school students and approximately 25 teachers from under-resourced communities in the design and creative application of AI-enabled smart, embedded technologies, while supporting their engineering identity development and preparing them for the STEM jobs of tomorrow. This project will benefit society with its timely and accessible high-school curriculum that integrates Computer Science and Engineering using the rich context of microelectronics and AI. The curriculum will be accessible because it has no prerequisites for programming or hardware knowledge. Every module is centered around a real-world application of microelectronics and AI with direct implications for improving the quality of life in local communities, making learning relevant and place-based. All course materials and resources will be disseminated as open source via the platforms popular among K-12 stakeholders, broadening access and inspiring the next generation of AI practitioners.
The focus of this design-based implementation research program is to conduct a systematic inquiry into the effective conditions for designing and integrating curricula and technologies that foster engineering identity development and conceptual understanding of AI in embedded systems as an important trend in engineering. To this end, the research is informed by both qualitative research questions (How are the altruism informed activities perceived and used by students?) and quantitative questions (What are the quantifiable impacts of this approach on students? motivation and conceptions of edge AI and microelectronics?) The research plan will employ a concurrent triangulation mixed-method research design, incorporating phenomenology, comparative case studies, and mixed-effects modeling. Specifically, the researchers will conduct classroom observations, interviews with students, teachers, and parents or caregivers, surveys, and learning tests to examine the uses and effects of the proposed approach in high school classrooms. This research will contribute new data for building theories on a) altruism as a motivation framework for supporting engineering education, and b) negotiation of engineering identities when engaging students in community-relevant AI and microelectronics projects.