University of Wisconsin–Madison

Promoting academic integrity

How can instructors promote academic integrity amid the growing prevalence of generative AI?

It’s understandable to have questions and concerns about how generative AI might enable academic misconduct.

Consider these approaches:

Photo of an instructor kneeling down and speaking with a group of students seated at a table working on an engineering kit.

Proactive strategies

  • Clearly communicate your expectations for use of generative AI to students through your syllabus and again at key points in your course, such as when an assignment is coming up. It’s especially helpful to explain the reasoning behind your approach and how it connects to what you’re hoping students learn in your course. View sample syllabus language.
  • Engage students in activities and conversation around the potential advantages and limitations of generative AI. See these activity ideas from the L&S Instructional Design Collaborative.
  • Familiarize yourself and your students with this Generative AI research guide from University Libraries and this student guidance for generative AI from the Office of Student Conduct and Community Standards (OSCCS).

Responding to potential AI-related academic misconduct

  • UW-Madison’s guiding principles for generative AI in teaching discourage using so-called AI detection tools due to their unreliability and risk of false accusations.
  • If you have reason to suspect a student hasn’t followed the expectations you’ve shared for use of generative AI, begin as you would with any other case of potential academic misconduct: by meeting with the student. The Office of Student Conduct and Community Standards (OSCCS) offers suggestions on how to prepare for and have that conversation. OSCCS also offers a more comprehensive overview of the academic misconduct process.

For more help

Please contact CTLM if you have additional questions or would like direct support.