Both of the above images were generated on Oct. 8, 2023, using Canva鈥檚 Magic Design tool. The image on the left was generated using the prompt 鈥淲oman using computer with graphs and charts in background.鈥� The image on the right was generated using the prompt 鈥淎bstract-style image of fantastical graphs, clouds, and shapes."
Generative AI is 鈥渁ny type of artificial intelligence (AI) that can be used to create new text, images, video, audio, code or synthetic data鈥� (Rouse, 2023). Although generative AI has existed since the 1960s, most of us only began to experience its impacts on teaching and learning firsthand in the past year (White, 2023). The advent of generative AI tools has created new challenges and opportunities for educators. It has also raised complex questions about how we can best prepare our students to work with AI responsibly and ethically in their future professional, personal, and civic lives. That is why the Center for Teaching & Learning is committed to providing all CU educators with the support and resources they need to go boldly into teaching and learning in the age of AI!
Note: This webpage focuses specifically on generative AI. To learn more about other forms of AI and their uses in teaching and learning, we recommend (2023).
Learn more about generative AI and teaching & learning:
How does generative AI work?
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In generative AI, a statistical model is trained鈥搕hat is, given the opportunity to search for and 鈥渓earn鈥� patterns鈥搃n a large data set. When prompted, it then generates (hence generative AI) novel outputs based on what is probable given the patterns detected in the training data. For example, imagine a generative AI statistical model is trained on all of the text messages you have ever sent. Would it find that the word 鈥渢hank鈥� is more likely to be followed by 鈥測ou鈥� (as in 鈥渢hank you鈥�) or 鈥渕e鈥� (as in 鈥渢hank me鈥�)? Let鈥檚 assume 鈥渢hank鈥� is more likely to be followed by 鈥測ou.鈥� Now, if you prompt it to compose a text message to let your friend know that you had a great time at coffee that morning, it will be more likely to include the phrase 鈥渢hank you鈥� than 鈥渢hank me.鈥� Learn more about from the experts at Cal Tech!听
Generative AI Tools
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The following is a list of generative AI tools with various functions for teaching, learning, and research. When exploring these tools, we encourage you to consider how generative AI may harvest and share data, copyright issues, and accessibility considerations and to note that some platforms could transition into subscription-based or pay-to-use services. This list is not exhaustive, as this new technology is part of the ever-changing digital landscape. If you have an AI tool that you have been using for teaching and learning, send us an email听and let us know!
How can I incorporate AI into my courses to support student learning?
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The U.S. Department of Education has suggested that we think of AI as 鈥渕ore like an electric bike and less like robot vacuums鈥� (2023). Drawing on this metaphor, we encourage you to think of AI as a technology that can be leveraged to support, rather than undermine, the learning process. As is the case with any technology, however, using generative AI effectively in the classroom requires forethought and intentionality. If you are interested in incorporating AI into your own courses, we recommend that you begin by reflecting on your course learning objectives. This will inform whether and how you incorporate AI into course assignments.
For example, let鈥檚 say one of your learning objectives for a writing course is for students to be able to skillfully make sentence-level grammatical choices to support their rhetorical goals (e.g., persuading a particular audience). In this context, merely having students prompt ChatGPT to write a persuasive essay would not be well-aligned with this learning objective. In contrast, asking students to revise the grammar in an essay written by ChatGPT to make it more persuasive for a particular audience would be well-aligned with this learning objective. Learn more about .
Why are AI literacy skills important, and how can we teach our students AI literacy?
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Although generative AI is a powerful tool, it has several significant limitations. Namely, generative AI sometimes 鈥渉allucinates鈥� inaccurate information, including attributing content to the wrong source or fabricated sources. It can also be used to create 鈥渄eepfakes鈥濃�搃mages, videos, or audio of a person doing or saying something that they did not actually do (e.g., see ). Furthermore, generative AI has been shown to reproduce non-inclusive language and biases, including gender, racial, anti-Muslim, disability-related, and other biases present in the data on which the statistical model was trained (e.g., Sun et al., 2023; Johnson et al., 2022; Abid et al., 2021; Whittaker et al., 2019). Lastly, generative AI raises a host of concerns around data privacy and copyrights.听
As educators, we can provide students with guidance on how to use AI responsibly and ethically, as well as opportunities to practice essential AI literacy skills. This includes skills like fact-checking, verifying AI-generated outputs, and writing effective prompts. 听听
I鈥檓 concerned about generative AI and academic dishonesty. What can I do?
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The rapid gain in popularity of generative AI tools has raised concerns among educators that some students will misuse these tools in educational settings (e.g., use a chatbot to compose an essay or get the answers to a closed-book exam). As part of equity-minded assessment, we encourage educators to be explicit and transparent regarding which uses of AI, if any, are acceptable, as well as how students should cite AI-generated content. You can include this information in the instructions for individual assignments or a more general statement in your syllabus (e.g., Guidance on crafting an AI syllabus statement,听). Furthermore, for which it is not permitted. Lastly, although we empathize with concerns around AI and academic dishonesty, it is important to recognize that and are likely to be prone to many of the same biases as generative AI. For example, emerging evidence suggests that GPT detectors are biased toward misclassifying non-native English writing as AI-generated (Liang et al., 2023). Learn more about !
Further reading & resources:
Abid, A., Farooqi, M., & Zou, J. (2021). . Proceedings of the 2021 AAAI/ACM Conference on AI, Ethics, and Society, 298-306.
Classpoint. (n.d.). .听听
Crompton, H. & Burke, D. (2023). . International Journal of Education Technology in Higher Education, 20(22).
Duke Learning Innovation. (2023, September 6).
Dalhousie Centre for Learning and Teaching. (n.d.). 听
Eaton, L. (Host). (2023, June 29). (No. 472). [Audio podcast episode]. In Teaching in Higher Ed.
Johnson, T. L., Johnson, N. N., McCurdy, D., & Olajide, M. S. (2022). . Government Information Quarterly, 39(4).
Liang, W., Yuksekgonul, M., Mao, Y., Wu, E., & Zou, J. (2023). Patterns, 4(7), 100779.
Oregon State University. (n.d.). Artificial intelligence tools: .听
Rouse, M. (2023, June 27). Techopedia.
Sun, L., Wei, M., Sun, Y., Suh, Y. J., Shen, L., & Yang, S. (2023). [Unpublished manuscript]. Department of Communication Arts, University of Wisconsin-Madison, Madison, Wisconsin.
U.S. Department of Education, Office of Educational Technology (2023).
White, M. (2023, January 7). . Medium.听
Whittaker, M., Alper, M., Bennett, C. L., Hendren, S., Kaziunas, L., Mills, M., Morris, M. R., Rankin, J., Rogers, E., Salas, M., & West, S. M. (2019). [Report]. AI Now Institute at NYU.
Zeide, E. (2019, August 26). . Educause Review.