Collaborative Research: EducateAI: CUE-T: Designing Artificial Intelligence Curricula for All Undergrads

University Of Kentucky Research Foundation, Lexington KY

Investigators

Abstract

Artificial Intelligence (AI) is drastically changing how we approach problems and the ways we craft solutions. AI awareness and competency are critical for the next generation workforce to stay competitive in the global economy. Improved AI literacy also leads to more responsible use and adoption of AI in society. While many institutions have increased their offerings of AI and AI-related courses, it is a challenge to ensure these are scalable and relevant for students who have had limited exposure or experiences in AI. To enable all institutions to better serve all students interested in AI, this IUSE: CUE Pathways project will develop undergraduate AI curricula that is appealing and approachable for students with a range of experiences in and knowledge of AI and computing technologies. The project will also be tested at community colleges and 4-year institutions with a range of resources, personnel, and access to technology to ensure wide adoptability across institution types. To design AI curricula that can appeal to all students so that every student interested in AI can have an opportunity to take AI courses, the project identifies five principles in the design that allow for technical competency regardless of the student’s background in AI or computing in general. These five principles include a zero-background entry point, a non-programming option, a discipline-specific application, and an invitation to go deeper. The collaboration among four institutions of different types explores how to adapt programs to the needs of different institutions while still serving each institution’s student population. The project develops a comprehensive evaluation plan that can be used to evaluate these principles and the programs created using them. The project is expected to reveal new ways to provide effective AI education to the widest possible population of undergraduate students. 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.