Integrating Artificial Intelligence and Policy Competencies in Computational Learning to Educate First-Year Undergraduates

About This Grant

This project aims to serve the national interest by educating a STEM workforce equipped with artificial intelligence (AI) competencies and enable us to compete globally. In response to the growing interest in AI policy, this project will help undergraduates entering the workforce be better prepared to integrate technical knowledge with AI knowledge. This project will lead to the development and implementation of AI educational modules that use policy narratives with computational exercises to educate first-year undergraduate engineering and public policy students. AI capabilities, limitations, and policy competencies will be developed as part of these modules. Specific competencies to be targeted include AI technical limitations, ethical considerations, social implications, professional responsibility, and regulatory frameworks. Assessment of student outcomes will provide insights into learning gains and advancement of competencies. The knowledge gained from this project will contribute to our understanding of AI education and will be disseminated to the STEM education community for broader usage. The integration of technical knowledge with policy in the context of AI applications will help educators cultivate better prepared professionals. The goal of this research is to advance our understanding of how policy and AI pertinent to computational competencies can positively impact student learning towards career readiness. More specifically, the project will use a narrative policy framework to elicit student and expert views and understandings of AI policy. Action research will then be used to develop educational modules for first-year public policy and engineering undergraduates. This study will evaluate the impacts of the modules on students using: 1) quantitative and qualitative analysis on student narratives, pre-post survey information, and observational field notes to determine commons shifts in thinking; and 2) comparative analysis between engineering and public policy students to determine discipline-specific differences. Learning competencies to be targeted include technical, ethical, societal, and regulatory. This project offers the potential to inform other integrative learning practices in support of cultivating better educated STEM professionals. AI competencies are essential for the next generation of STEM professionals and this project will contribute to this knowledge base. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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.