Location: Freeman Commons, Humphrey School 205
Scott Simkins introduces a course design framework for integrating generative AI into economics teaching, drawing on his work redesigning an Intermediate Macroeconomic Theory course. Open to the public.
This talk discusses instructor and student views about generative AI in coursework, changing employer demand for AI-related skills, and the role of expertise in augmenting worker performance. It introduces an adapted version of Dee Fink’s Taxonomy of Significant Learning as a course design framework for integrating generative AI into economics courses. The adapted framework emphasizes four interacting dimensions: building disciplinary expertise, developing responsible generative AI skills, caring about learning, and creating human connections. The discussion illustrates how this framework has been used to revise an Intermediate Macroeconomic Theory course, including a variety of course examples, and covers broader issues instructors should consider as they revise courses to address teaching and learning processes disrupted by GenAI.
Speaker biography:
Scott Simkins is an Associate Professor in the Department of Economics at North Carolina A&T State University. He has led multiple National Science Foundation projects exploring the use and diffusion of evidence-based teaching innovations in economics. His research focuses primarily on cross-disciplinary pedagogical innovation and systemic change in teaching and learning.