Teaching Commons > Teaching Guides > Technology > Artificial Intelligence
Artificial intelligence (AI) encompasses a variety of computer-based tools that source existing data to solve a problem, such as search tools that rely on algorithms to find information or language translation tools (McCarthy, 2007). Generative artificial intelligence refers to a suite of tools that source existing data to create new artifacts in response to user prompts (Goodfellow et al, 2020). For example, ChatGPT is a conversational generative AI that sources a wide range of texts to create unique responses to text prompts.
Generative AI is an emergent and rapidly evolving space. New tools, or updates to existing tools, are released frequently, but a few examples are helpful in framing out what these tools do:
Masland (2023) describes a range of ongoing responses to emerging AI technologies in higher education. In doing so, Masland encourages instructors to reflect:
As we continue learning about generative AI tools and considering our responses, these approaches will help you to acknowledge the tools with students and consider how they might impact your teaching right now:
Enforce your expectations with
a syllabus statement and other classroom policies, and remind students of
DePaul’s Academic Integrity Policy. Consider
co-creating guidelines for responsibly using AI tools.
Scaffold large projects. Consider adding reflection activities, such as process reports or
exam reflections. Provide students with credit for making their
processes and learning visible.
See how the tools respond to your assignment and activity prompts.
Review approaches to effective assignment design that might limit the possibilities of using generative AI tools. Focus your assignments on
higher order thinking tasks and give students opportunities to showcase their unique interests and perspectives. Consider alternative assessments, such as
social annotation and multimodal projects, like podcasts.
“Curated Readings and Podcasts About AI” to guide some of your discussion. Consider how your field or discipline impacts the conversation.
The following texts represent some of the recent conversations about generative AI. DePaul Driehaus College of Business Online Learning Director James Moore also maintains
a curated list of texts that address AI.
Roose provides an overview of how ChatGPT works as an A.I. chatbot, including some screenshots that demonstrate the interface.
This alarmist piece is referenced in many of the other articles. Eliciting panic can be effective! Useful to read as part of the initial discourse.
Bogost demonstrates some limitations of ChatGPT and argues “ChatGPT isn’t a step along the path to an artificial general intelligence that understands all human knowledge and texts; it’s merely an instrument for playing with all that knowledge and all those texts.”
Tony Wan discusses the emerging field of AI tools in use for education beyond ChatGPT, including platforms that can help with online language learning, and more collaborative approaches to using AI technology in education.
McMurtie provides a near-immediate, yet thoughtful, academically-framed response to the release of ChatGPT: adjusting learning processes, incorporating generative AI in curricula, and rethinking assessment.
Warner argues ChatGPT has created an opportunity to examine how we value learning and how we create experiences that help students learn.
Eleven academics share their advice for approaching ChatGPT. Suggestions include “Think a Few Years Out,” “Invite Students Into the Conversation,” and “Experiment. Don’t Panic.”
This detailed walkthrough of how Grobe incorporated ChatGPT into his course shows the affordances and limitations of the tool.
Ethan Mollick focuses on the importance of learning to use AI correctly, by learning to collaborate with it as opposed to expecting it to do the work for you.
A brief look at the trustworthiness of the content produced by generative AI.
Professors at the University of Minnesota Law School used ChatGPT to generate answers on a small set of blindly graded exams. ChatGPT performed, on average, at a C+ level. The professors describe their methods and results and discuss the implications for law education.
Terwiesch, an operations management professor, asked ChatGPT several final exam questions. She found that it performed well at general questions, made pretty glaring math errors, and couldn’t move towards more complex analytical responses. It got a B/B+ on the exam.
Klein’s conversation with Altman from 2021 is pretty broad, but it’s helpful to hear from the founder of OpenAI (the source of ChatGPT and Dall-E) to understand his operating principles.
Thompson and Thompson offer a wide-angle-lens conversation that situates generative AI in potential technological, economical, and societal impacts.
Events for opportunities to learn more about AI. Email email@example.com to suggest additions to this guide.