2025 ASEE Annual Conference & Exposition

The exponential rise of Artificial Intelligence (AI) hardware technologies, fueled by rapid data science advancements, has reshaped the computing landscape, transforming machine learning from a theoretical pursuit into a driving force behind real-world innovation. From the early days of basic processors to today’s GPUs, TPUs, and specialized AI accelerators, hardware breakthroughs have continuously redefined the boundaries of scalability and application. Our project, funded by the NSF Improving Undergraduate STEM Education (IUSE) program, began in 2022 with an ambitious vision: to create a gamified curriculum for teaching hardware fundamentals using Field-Programmable Gate Array (FPGA) platforms. As the project evolved, we expanded to include AI Internet of Things (AIoT) applications, and most recently, we’ve sharpened our focus on intelligent embedded systems. Central to this initiative is our commitment to exposing engineering students to these cutting-edge technologies early in their higher education, helping them make empowered career choices while ensuring the workforce is prepared to keep pace with accelerating technological advancements. By adapting swiftly, our curriculum is equipping students to stay ahead and lead the next wave of innovation.

Over the past two years, the curriculum has been iteratively refined and implemented at a large public R1 university in the Southeastern US, following Design-Based Implementation Research (DBIR) principles. Grounded in equity-centered practices informed by Culturally Relevant Pedagogy (CRP) and Universal Design for Learning (UDL), the curriculum combines inquiry-based and experiential learning in a Project-Based Learning (PBL) format. This approach effectively builds students' understanding of key hardware concepts like binary numbers, Boolean logic, and sequential circuits while also integrating AI to gather data from IoT devices and solve real-world embedded systems challenges. The use of accessible FPGAs and IoT boards provides multiple entry points, offering hands-on learning that fosters self-efficacy, particularly for neurodiverse learners. This strategy ensures students gain both foundational knowledge and the confidence to navigate the rapidly evolving field of intelligent embedded systems.

This paper and poster presentation will explore the evolution of this curriculum, enriched by data collected from Fall 2023 to Fall 2024 on students' career choices, identity, interest, outcome expectations, and self-efficacy in hardware engineering, AIoT, and intelligent embedded systems. To gauge participants' perceptions, we administered both pre and post-surveys, conducted focus groups, assessed conceptual learning, and conducted interviews with 17 students in Fall 2023 and 17 students in Fall 2024. These mixed methods provided a nuanced understanding of their experiences and perspectives regarding the curriculum. Offered as an elective in the Electrical and Computer Engineering (ECE) department and open to all engineering majors, the program has attracted a diverse student body, both in terms of academic backgrounds and demographics, with each iteration showing an increase in race and gender identity diversity. These results demonstrate that the curriculum’s inclusive, hands-on approach resonates with a broad range of students, positioning them to thrive in the growing field of intelligent embedded systems. The findings carry significant implications for educational practice, highlighting the value of inclusive, experiential learning environments in attracting and retaining diverse talent within rapidly advancing technological fields.