AI Instructional Resources
At STLI, we recognize that Generative AI (GenAI) presents both significant challenges and exciting opportunities for teaching and learning in higher education. As William & Mary’s teaching center and academic innovation hub, we aim to provide thoughtful, practical resources to help you navigate this evolving landscape.
Whether you’re rethinking old assignments, creating new ones, clearly communicating your course’s GenAI policies to students, or facing other unique instructional dilemmas, we provide the resources linked below to support your efforts to tackle these complex questions.
As always, we’re happy to meet with you to discuss questions, ideas, or specific challenges as you explore the role of GenAI in your teaching.
Designing for Learners: Generative AI
The Designing for Learners: Generative AI is a free short course that provides actionable strategies for mitigating the use of GenAI and/or effectively integrating it in your class. The course guides you through understanding the fundamentals of GenAI, considering its ethical implications, leveraging it for teaching and learning, examining sample assignments, and constructing a GenAI Teaching Plan. W&M instructors email academy@wm.edu for a free enrollment link.
Instructor AI Policy Communication Guidelines
The Instructor AI Policy Communication Guidelines provides guidelines for communicating GenAI policies and practices within William & Mary courses. It provides step-by-step instructions as well as syllabus statement models that can be adopted or adapted by individual instructors.
Departmental AI Policy Recommendations
The Departmental AI Policy Recommendations provides recommendations for departments to create GenAI policies or guidelines, to promote consistency across the department. Although the permissible use of GenAI is often context-situated within individual courses, departments might find it useful to craft general guidance as a starting point for instructors.
Evaluating AI Outputs Using Lateral Reading Strategies
The Evaluating AI Outputs Using Lateral Reading Strategies is a resource which instructors may adopt or adapt that guides students through a process for documenting how they verified the accuracy and reliability of information from GenAI outputs by reading across sources, rather than relying on a single source.
Approaches to Teaching with GenAI - STLI Teaching Resource
Approaches to Teaching with GenAI is STLI’s Teaching Resource on teaching and learning in the era of GenAI. This one page resource provides a summary of some of the most prominent concerns for instructors with guidance and links to further reading and resources.
"Why Students Cheat": Assessment Design and GenAI
“Why Students Cheat”: Assessment Design and GenAI is a resource inspired by James Lang’s (2013) Cheating Lessons. Use this resource to consider assessment design approaches for guarding against unsanctioned GenAI use. Assessment approaches include those that require the application and evaluation of knowledge, critical thinking, and reflection, leveraging the human abilities of thinking and discernment.
GenAI Communication Entry Points
GenAI Communication Entry Points provides concrete suggestions for addressing GenAI use with your students openly and effectively. The guide is divided into three levels of discussion and application: entry, intermediate, and advanced.
STLI AI Identifiers
STLI AI Indetifiers are an example of transparent communication regarding AI use in creative outputs, resource creation, and other generative activities. Visit our GenAI statement page to learn more about our approach and utilize our identifiers through Creative Commons licensing.
Have additional questions?
Connect with Pablo Yañez, Senior Data, Technology, & Innovation Program Manager
Pablo is responsible for innovative digital tools, programming, and teaching practices related to science labs and large classes. As a geologist with research and teaching experience, Pablo is interested in teaching and learning in the science fields.
