Engineering Education in the Age of AI

A faculty development course for engineering educators navigating the rapid integration of AI into their disciplines and their classrooms. The course covers the foundations of machine learning and generative AI, the pedagogical challenges that widespread student AI use has introduced, and practical strategies for assignment design, assessment, and academic integrity. It also equips faculty to use AI tools effectively in their own teaching practice, and helps them integrate responsible engineering directly into technical courses.

Each module opens with a brief knowledge-building component and moves into facilitated collaborative work in discipline-aligned cohorts. Modules stand alone, so faculty can take the full course or the modules most relevant to them, with flexible synchronous and asynchronous participation designed for the full range of instructors, including adjunct faculty and online instructors. Every module ends with a concrete deliverable, ready to use in your own course:

1. Foundations of AI for Engineering Faculty → a disciplinary AI landscape note
2. Academic Integrity, Learning Loss, and Policy Design → a course AI policy package
3. AI in Your Own Teaching Practice → a documented prompt workflow
4. Redesigning Assignments and Assessment → a redesigned assignment package
5. Integrating Responsible Engineering into Technical Courses (opt-in; with the NSF-funded ER2 workshop) → a responsible-engineering teaching artifact