Artificial Intelligence Teaching Guide
Artificial intelligence technology has become increasingly sophisticated and readily available. We believe that educators can contribute to how this important technology is understood and used. We invite you to engage thoughtfully and attentively with this teaching guide as a way to learn about and positively influence the dialogue around artificial intelligence in education.
For instructors and teaching teams
We offer this guide to all instructors and teaching teams approaching the topic of generative AI tools in education, whether for the first time or as part of your ongoing engagement with the topic, in response to practical concerns that we heard from instructors like yourself. You don't need to be an expert or have prior experience with generative AI to use this resource, though you should have some understanding of or experience with teaching and learning in higher education contexts. We intend this guide to apply to any disciplinary area or teaching modality and to help you structure the work of integrating AI tools into your teaching practice.
Goals and scope of this guide
The goal of this guide is to help you make informed and intentional decisions about how you will use AI chatbots in your teaching practice and courses as you prepare for the start of the 2023–2024 academic year.
We cannot comprehensively address the complex topic of artificial intelligence in any short guide. Many campus service providers, such as University Information Technology (UIT), Stanford Accelerator for Learning, and the Institute for Human-Centered Artificial Intelligence (HAI), have developed excellent resources that offer insight into AI in terms of technical aspects, innovative new tools, societal impacts, AI research, and so on. We have chosen to focus on the practical and pedagogical aspects of AI tools in the classroom. We will focus on generative AI chatbots in particular, but you may find the content here can also apply to other generative AI tools, such as image, media, or code generators.
Multiple instructional modules for flexibility
Each page of this guide contains one instructional module including content, practice tasks, and assessment activities. We suggest that you complete the activities and suggested readings in each section as a self-directed online lesson. We designed each module as a discrete and complete lesson that you can finish in a relatively short amount of time. You can work through the modules in any order. We encourage you to engage fully with each module, completing the recommended activities to reinforce your learning.
Each module has specific goals and objectives:
- Warming up to AI—Reflect on your emotional state and foster feelings of acceptance, curiosity, and motivation.
- Defining AI and chatbots—Define common concepts and explain how AI tools work
- Exploring the pedagogical uses of AI chatbots—Explore educational use cases, describe risks, and access and practice using chatbots.
- Analyzing the implications for your course—Describe campus AI policy guidance, evaluate and analyze your course
- Creating your course policy on AI—Draft a course policy on AI use for your syllabus
Complete the modules with your colleagues
Learning together with others can deepen the learning experience. We encourage you to organize your colleagues to complete these modules together. You may adapt, remix, or enhance these modules for your own needs, as this guide was created by Stanford Teaching Commons and is licensed under Creative Commons BY-NC-SA 4.0 (attribution, non-commercial, share-alike).
How AI was used in the creation of this guide
We did not copy and paste any language generated by AI chatbots into this guide. We used AI chatbots, primarily ChatGPT, to generate feedback on the clarity and structure of some of the writing and to clean up some text formatting. We used ChatGPT and other chatbots more extensively in the development of the module "Exploring the pedagogical uses of AI chatbots" to mimic how we thought instructors and students might use them in a course and to better understand the pedagogical potential and challenges of such tools.
Authors and acknowledgments
We are a team of support staff from different parts of the Office of the Vice Provost for Undergraduate Education (VPUE). Our team created the guide in the summer of 2023 through the collective effort of dedicated colleagues from across the university. We want to thank the following people who contributed to this resource. If you have any questions, contact us at TeachingCommons@stanford.edu.
- Kenji Ikemoto (Center for Teaching and Learning) for leading the project team and being the primary author of this guide.
- Marvin Diogenes (Program for Writing and Rhetoric) for brainstorming, editorial feedback, and sage advice on the meaning of language.
- Sarah Pickett and Kritika Yegnashankaran (CTL) for their pedagogical expertise and teacherly support.
- Carlos Seligo (CTL), Josh Weiss (GSE), and Andy Saltarelli (VPSA) for being thought partners and providing the initial inspiration for this guide.
- Laura Otero (California State University Monterey Bay) for sharing her exemplary AI in education Canvas course.
- John Mitchell (Computer Science) and Glenn Fajardo (d.school) for leading the Seminar on Generative AI and Education.
- Merve Tekgurler (History) and Patrick Young (Computer Science) for sharing their teaching experience with us.
- Anyone who recommended an article, had a random hallway conversation, or cheered us on.
Warming up to AI
A playful entry point into the topic of generative AI in education.Go to the first module