Core Principles for Undergraduate Teaching and Learning
Spring 2025
Robert Ghrist, Associate Dean of Undergraduate Education, School of Engineering and Applied Science
Diana Robertson, Vice Dean and Director, Wharton Undergraduate Division
Julie Sochalski, Associate Dean for Academic Programs, School of Nursing
Peter T. Struck, Stephen A. Levin Family Dean of the College of Arts and Sciences
Beth A. Winkelstein, Deputy Provost
The rapidly evolving nature of AI calls for creativity and innovative thinking as we reflect on how we teach, learn, and conduct research as members of a scholarly community. This imminent inflection point regarding the incorporation of AI in higher education provides an opportune moment to reinforce our shared commitment as Undergraduate Deans to discovery and opportunity as articulated in the University Values and renew our commitment to core principles for undergraduate teaching and learning.
Core Principles
Principle 1: Student learning is the highest priority in teaching. Accordingly, instructors are responsible for incorporating the best available tools into their pedagogical approach to enhance student learning. The University’s responsibility is to provide opportunities for instructors to learn how to utilize these tools.
Principle 2: Instructors determine course policies and procedures, consistent with overall University policies, and are responsible for communicating those course policies clearly to students. Policies may change from one course to another based on course content, expected learning outcomes, and overall course goals.
Principle 3: Students are responsible for knowing and abiding by the Code of Academic Integrity and all course and University policies.
Principle 4: It is incumbent on instructors to provide clear and specific expectations for how generative AI may or may not be used in their course, including expectations around the use of generative AI in coursework, group work, collaboration, and assignments.
Principle 5: Instructors are responsible for crafting course assignments and evaluations that effectively facilitate or assess desired student learning outcomes, taking into account course policies about the tools students may use.
For guidance on incorporating generative AI into your teaching, the Center for Excellence in Teaching, Learning, and Innovation provides resources and workshops for instructors: https://cetli.upenn.edu/resources/generative-ai-your-teaching/.