Teaching at UW

Whether or not you plan to incorporate generative AI in your teaching, it is critical to establish and share your expectations for AI use with students. In this session, featuring Pajarita Charles, Ph.D. (Social Work) we will:

• Discuss AI-related expectations to incorporate in your syllabus, assignments, and assessments
• Consider how to respond if you believe AI may have been used inappropriately.

Wondering how to make your student feedback more effective, equitable, and efficient? There ARE ways to do this. Join Abby Letak, Ph.D. (Writing Across the Curriculum), as we explore research-backed principles and tangible strategies for responding to student work. We’ll also consider in a time of AI, what is the value of human feedback?

The learning support you provide to students is just as important as the content covered in class. Join Jonathan Gallimore, Ph.D. (Psychology), as he shares practical teaching strategies that allow you to understand where students may be struggling and provide the right kinds of support. You’ll leave with actionable ideas, proven techniques, and resources that work with different course formats – like large enrollment courses or flipped designs.

Learn how UW–Madison instructors have tapped teaching and learning data to improve their courses and think about their teaching through a different lens. Featuring projects and stories from the Insights to Impact (i2i) program.

Explore transdisciplinary instructional behaviors that cultivate openness, risk-taking, and inclusion – the “soft structures” that support belonging and creative development in college classrooms. Join CTLM’s John Martin, Ph.D., as he unpacks six dimensions of creativity-fostering behavior and examine teaching strategies such as encouraging autonomy, normalizing productive failure, creating spaces for risk and reflective feedback.

The way you design questions can have a powerful impact on student learning. Karen Hershberger, Assistant Teaching Professor in the Department of Pathobiological Sciences at the School of Veterinary Medicine, will share practical strategies for structuring questions that foster metacognition and self-regulated learning, helping students plan effectively, monitor their understanding, and reflect on their progress.

Amid the growing prevalence of AI, how can we equip students with discipline-specific knowledge, critical thinking skills, and a clear sense of scholarly responsibility? CTLM’s Amanda Leary, Ph.D., will share strategies for motivating and engaging students in the essential “brain work” of our courses—work that includes questioning AI-generated outputs and taking ownership of what they submit.