Looking to teach with confidence in the age of AI? Start here.
The Norton Guide to AI-Aware Teaching will equip instructors with practical strategies for teaching effectively in the age of AI. AI-aware teaching means understanding how the technology impacts course goals, assignments, and students so that instructors can adapt with confidence. The guide provides steps for how to do so—whether the instructor is embracing AI, setting firm boundaries, or finding a balance. Flexible guidance and useful applications across disciplines empower instructors to adapt their learning outcomes to be AI aware.
Practical Organization: The guide will be organized chronologically as an instructor would approach preparing for or revising a course. This organization—which progresses from planning, designing, and teaching an AI-aware course to adapting instructional practices as AI evolves—will help teachers implement new, effective strategies immediately.
Flexible Guidance: Instructors can explore flexible, varied options for adapting their teaching to address AI’s impact on student habits and learning through frameworks that make AI-aware teaching both attainable and sustainable.
A Focus on Learning Outcomes: Instructors are motivated when they think in terms of their own students and their specific learning outcomes. The guide empowers instructors to make changes that make sense for their courses through compelling research, thorough examples, and practical strategies.
Useful Applications: Through inspiring examples, the guide will support the development of AI-aware assignments, activities, assessments, and course policies.
The Norton Guide to AI-Aware Teaching will publish in Fall 2026
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Table of Contents
Introduction: What's AI-Aware Teaching?
PART I: PLANNING AN AI-AWARE COURSE
1. Evaluating your course’s learning goals
2. Meeting students where they are
3. Choosing the role of AI in your course
4. Crafting an AI policy
5. Designing an assessment approach
PART I: PLANNING AN AI-AWARE COURSE
6. Transparency in learning and teaching for generative AI
7. In-class activities
8. Large lecture classes and interactivity
9. Writing
10. Research
11. Reading
12. Exams and assessment
13. Reflections
PART III: TEACHING YOUR COURSE
14. Building trust, buy-in, and accountability
15. Talking to students about AI
16. Supporting your AI policy
17. Emphasizing student accountability
18. Using AI to enhance your teaching and assessing AI tools
PART IV: EXTENDING YOUR KNOWLEDGE
19. How does AI work?
20. Interacting with AI
21. AI for multimodal work
22. Ethical issues in AI
CONCLUSION: WORKING TOGETHER
About the Authors
Marc Watkins
Marc Watkins, MFA, directs the AI Institute for Teachers and is an Assistant Director of Academic Innovation at the University of Mississippi, where he is a Lecturer in Writing and Rhetoric. He has led research initiatives, exploring generative AI’s impact on student learning, training workshops for faculty on AI literacy, and several institution-wide AI institutes. His work with training faculty in AI literacy has been profiled in The Washington Post and he regularly writes about AI and education on his Substack, Rhetorica.
Annette Vee
Annette Vee, PhD, is Associate Professor of English at the University of Pittsburgh, where she teaches courses in writing, pedagogy, digital composition, AI, and literacy. Dr. Vee serves on various AI initiatives at the University of Pittsburgh, facilitated Pitt’s AI across the Disciplines program, and frequently gives keynotes and workshops on AI in higher education. She is the author of Coding Literacy: How Computer Programming Is Changing Writing, co-editor of TextGenEd: Teaching with Text Generation Technologies, and is working on a book that examines why and how humans have sought to automate writing across history. She writes for two Substacks: Computation & Writing and AI & How We Teach Writing.
Derek Bruff
Derek Bruff, PhD, is an associate director at the University of Virginia's Center for Teaching Excellence, where supports faculty across the disciplines in integrating generative AI in their teaching. He is the author of Intentional Tech: Principles to Guide the Use of Educational Technology in College Teaching and Teaching with Classroom Response Systems: Creating Active Learning Environments. He produces the Intentional Teaching podcast and blogs about teaching with technology at Agile Learning. Bruff has taught mathematics courses at Vanderbilt and Harvard Universities.