Generative Artificial Intelligence in the Classroom

Artificial Intelligence is quickly changing our understanding of teaching, learning, and working. This page is an evolving resource for those curious about AI in the higher ed context.  

What is Generative AI?

AI in the Classroom: Resources


The Generative AI in Teaching and Learning Task Force

In spring 2023, the university convened a Generative AI in Teaching and Learning Task Force in the Provost’s Office. Learn more about the work of the task force. The Gen-AI Task Force website includes guidance for faculty and students, the Task Force's report, and resources from the Center for Teaching Excellence. 

AI in LDT's LTi Projects

A&S Learning Design & Technology is supporting the work of Prof. Marc Santuguini (ECON) exploring applications of ChatGPT in his Economics courses. 

AI Collections in CTE's Teaching Hub

This gallery of collections is designed to support you in navigating the generative AI landscape in higher education, from what generative AI is and how you can learn more about it to what using it could look like within and across disciplines.

AI, Accessibility, and Equity 

Consider these reflections on the potential of AI to impact access, inclusion, and equity in higher education. 

AI, Assignments, and Assessments

Consider these resources related to assignment design: 

AI and academic integrity: early thoughts

Consider this graphical representation of possible AI applications to a student project. Which might we consider ‘cheating’? Which might be acceptable? Which are relevant to our students’ future? Which would you use in your own work? 

title reads “it’s time to rethink “plagiarism” and “cheating”. A continuum from ‘bot-created’ to ’student-created’ organizes six statements:  student plugged prompt into Aim copied response and submitted it to teacher. 

ChatGPT, Chatbots and Artificial Intelligence in Education - Ditch That Textbook

Graphic description for screen readers

From the top (bot-created) to the bottom (student-created):

  • student plugged prompt into AI copied response and submitted it to teacher.
  • AI created a response. Student read, edited, adjusted, and submitted.
  • Student created multiple AI responses, used the best parts, edited, and submitted.
  • Student wrote main ideas. AI generated a draft and offered feedback to improve.
  • Student consulted internet/AI for ideas, then wrote and submitted.
  • Student wrote all assignment content without consulting AI or the internet. 

Three questions are posed next to the continuum

*Which of these would you consider “cheating”?

Which of these is relevant to our students’ future? 

Which of these would you use in your work as an adult. 

Graphic logo “Ditch That Textbook” Graphic by Matt Miller @jmattmiller


AI-Detection Tools in Higher Ed

AI-detection tools are marketed to educators in various settings. These tools have considerable drawbacks, including reliability (can indicate ‘false positives’ in work that is not AI generated) and relevance (a step behind AI tool), as well as expense. Alternative approaches to course activities and assignments can engage students in learning, reduce mistrust, and create equity among students. Consider alternative assessment ideas from the K P Cross Academy Techniques Archive - The K. Patricia Cross Academy ( and the Center for Teaching Excellence Teaching Hub UVA Teaching Hub (

Resources on Academic Integrity and AI


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