Open to: PhD students
Credit: 1, credit/no credit
Instructor: Dr Elise Mueller
Offered: Fall. Instructor consent required.
Prerequisites: None

This course is designed for advanced PhD students from all fields who want to explore how artificial intelligence (AI) can improve teaching and learning in higher education. Students will create activities that integrate generative AI, think through their AI course policies, and experiment with various generative AI tools. Course learning objectives: 

  • Identify and explore AI tools that can be used in college classes across a wide range of disciplines.
  • Create teaching materials, ranging from syllabi to single classroom activities, using AI tools.
  • Explore and discuss ethical issues with AI in higher education, including academic misconduct, privacy, data safety, bias and access equity.
  • Reflect on and document your approach to using AI in your teaching practice.

To Enroll

Students in the Certificate in College Teaching program are given priority for this class. Each term, an online form is opened for students to express interest in this and other college teaching courses being offered in the following term, and seats in the courses are distributed based on need and the appropriate fit of the student (year of study, teaching experience, etc.) The online form is typically opened in October (for spring classes) and in April (for fall classes.) Watch for CCT Annoucements emails for these links.