Research Initiation: Human-Centered AI Algorithm Design for Engineering Students' Professional Formation

About This Grant

Artificial intelligence (AI) is rapidly transforming the world, and is changing how people learn, work, and connect. From healthcare and transportation, to education and public services, AI systems are shaping how people make decisions and are influencing everyday experiences. As these technologies become more integrated into daily life, it is essential that engineers are prepared not only to build them, but also to understand and anticipate their broader societal impacts. This project will support the development of new teaching strategies that will help engineering students engage with the ethical, social, and human dimensions of AI. By designing and testing new ways of teaching that help students connect their technical education with real-world impact, the project will support the development of engineers who are thoughtful, responsible, and prepared to contribute to the public good. This work aligns with growing national efforts to strengthen the AI workforce and ensure that students and educators are prepared to thrive in a rapidly evolving digital society. In particular, it supports priorities outlined in recent federal initiatives that call for expanded education, teacher training, and ethical awareness in the field of AI. This project will also address the goals of the National Science Foundation’s Research Initiation in Engineering Formation (NSF-RIEF) program by training a faculty member new to engineering education research to build the skills and collaborations needed to study and improve how engineers are taught about AI. This project will develop, implement, and study a novel approach to AI education grounded in Human-Centered Algorithm Design (HCAD). HCAD integrates technical, ethical, and social considerations into the process of designing algorithmic systems. The project will be carried out in three phases: (1) the development of modular instructional materials suitable for integration into both introductory and advanced undergraduate engineering courses; (2) the implementation of these materials in courses at Boston College; and (3) the use of design-based research (DBR) methods to iteratively study and refine the curriculum. The research will examine how students understand and apply HCAD concepts, how their perceptions of engineering and AI evolve, and how different elements of the curriculum influence engagement. Mixed-methods data collection will include surveys, interviews, classroom observations, and analysis of student work. Findings will contribute to the growing body of knowledge on engineering education, AI instruction, and pedagogical design for integrated STEM learning. Outcomes will include publicly available curricular materials, empirical evidence on how students engage with human-centered design approaches in technical contexts such as when building AI-based algorithmic systems, and guidance for adapting the HCAD framework to other institutions with varying missions, sizes, and student populations. In addition, the project will support the PI’s growth as a scholar in engineering education research by providing mentored experience in research design, qualitative and quantitative methods, and dissemination. Through these efforts, the project aims to improve the quality and reach of AI education and help shape a generation of engineers who are equipped to design technologies that responsibly serve society. 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.