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Please feel free to contact the CTL with feedback, questions, and suggested resources around generative AI for teaching and learning.
"5 Things to Know About ChatGPT"
For a quick overview of a Generative AI tool commonly used in higher education, see this CTL resource that was initially created at the launch of ChatGPT and is updated periodically with current resources.
Course Design
The impact of generative AI tools on the way we design our teaching experiences ought to be determined before these experiences begin. Many instructors teach in hourly modules while other teach an entire class over the course of a semester. For suggestions for instructors who teach modules or units of a class, please take a look at the Assignment sections of this resource. In planning a class, there are any number of considerations to bear in mind as you signal your course-level policies to your students as well as your intentions around these tools.
As you get ready to begin your class by preparing course documents and resources, make sure that you address appropriate or inappropriate uses of generative AI tools.
- Explore generative AI tools (free/paid), how they respond to your assignment prompts, instructions and ethical concerns, and citation formats (e.g. https://ditchthattextbook.com/ai-tools/)
- Consider your assignment timelines
- Consider “flipping” parts of your class and build in time to bring parts of assignments into the classroom as physical artefacts of the assignment
- Explore non-textual assignments or components (e.g., mind maps, timelines, infographics, video) that may or may not be created by GenAI tools
- Embrace Universal Design for Learning (UDL) principles
- Incorporate more disciplinary, contextual, and reflective questions or prompts
- Consider social annotation (e.g., Perusall) to help students document their learning and processes. In a tool like Perusall, students can upload and annotate their own submissions to document their thought-processes.
>> Faculty Spotlight: As a recipient of a PAIR student-as-partners grant (Partnership in AI Research), Dr. Nina Palmo (Sociology, College of Liberal Arts) is working with a cohort of undergraduate teaching assistants to redesign her "Health and Society" course by co-creating a series of weekly essay prompts and assignments that will embrace the potential of generative AI arcoss the semester.
We believe that with the right guidance and mentorship, students in the course will learn to use AI to engage more deeply with course content, apply critical thinking skills, consider multiple perspectives, and create a polished final product.
In many ways, when closely examining your course from the perspectve of its curricular position, or, its placement within a degree pathway or major, it may be useful to embrace a more formal course design approach and identify where/when students may explore the use of generative AI tools. From small group discussion to large classes, the following concepts and course design approaches may prove useful in adapting GenAI to pedagogical approaches.
| Eight Principles for Effective Teaching | The Center for Teaching and Learning recommends adopting a research-driven, evidence-based approached to teaching and course design. Consider the role that GenAI can play in augmenting or enhancing student learning opportunities, research skills development or shared responsibility for learning. For example, while students may traditionally work in small groups for a "think-pair-share" activity, they may now work in a "think-prompt-share" activity that encourages critical reflection around prompt responses and summarization of shared engagement with a GenAi tool. |
| Bloom's Taxonomy for GenAI | Bloom's taxonomy allows instructors to align the ways in which they teach with what they expect students to accomplish. According to Morgan (2024), "while generative AI poses challenges to the traditional model of Bloom's Taxonomy, it also offers opportunities to enhance the learning process. By integrating AI into the 'create' level, we can ensure that students engage in meaningful, higher-order thinking." |
| Backwards Design | This approach is very commonly employed in instructional design settings. In essence, it entails designing learning outcomes by focusing on the assessments students are expected to complete in your class: in thinking about what students should be able to "do" rather than "know," it encourages us to be more concrete in mapping out assignments and modules of a course. At some point in this trajectory, generative AI tools may have a role to play. |
| ABC Course Design | Building on Bloom's taxonomy by embracing learning as an action more than knowledge, this approach uses visual storyboarding as a way to map out a course or curriculum and would help identify moments or opportunities for innovating with generative AI tools: "ABC enables programme and module teams rapidly to develop a storyboard visualising the learner journey based on their activities through the course of study. The method is non-prescriptive and builds from the participants’ existing practice but can be used to identify opportunities for blended learning, to review assessment and feedback and align the programme to wider institutional priorities." |
Additionally, please explore the Provost's "Your Syllabus at UT Austin" website as well as UT's Student Conduct and Academic Integrity site for additional options and resources. As you craft your syllabus statements, you may wish to adopt one of the following three models and use them as templates:
"The use of artificial intelligence tools in this class:
- …is strictly prohibited. This includes using AI to generate ideas, to outline an approach, to answer questions, to solve problems, or to create original language. All work in this course must be your own or created in group work, where allowed).
- …shall be permitted on a limited basis. You will be informed as to the assignments for which AI may be utilized. You are also welcome to seek my prior-approval to use AI writing tools on any assignment. In either instance, AI writing tools should be used with caution and proper citation, as the use of AI should be properly attributed. Using AI writing tools without my permission or authorization, or failing to properly cite AI even where permitted, shall constitute a violation of UT Austin’s Institutional Rules on academic integrity.
- …is permitted for students who wish to use them, provided the content generated by AI is properly cited.
If you are considering the use of AI writing tools but are unsure if you are allowed or the extent to which they may be utilized appropriately, please ask."
For additional suggested syllabi statements, please visit our webpage that contains a range of different statements that you may use and adapt. For more extensive, in-depth suggestions, please visit Lance Eaton's "Syllabus Policies for AI Generative Tools" page.
Introducing students to your policies around generative AI use can help you manage expectations and start the semester strong.
- Be clear on what you want your students to know and be able to do or demonstrate by the end of the course and why that knowledge is valuable to their lives. (See this resource on learning outcome design in the Course Clarity Project resources at UT-Austin for assistance in developing learning outcomes for your course.) Help students see that the ways you are assessing their learning are key to understanding what they are gaining from the course and where they may need extra coaching and support.
- Talk to your students about how relying heavily on this tool may interfere with achieving the learning outcomes you hope they will achieve in this course (e.g., problem solving, developing an authentic writing voice, etc.).
- In particular, “If you can explain to students the value of writing, and convince them that you are genuinely interested in their ideas, they are less likely to reach for the workaround.”
- Have an open discussion with your students about the ethical implications of ChatGPT and the value of authentic learning for students’ lifelong development as learners. This may include having conversations around digital literacy and bias in research and scholarship, as AI writing tools like ChatGPT are limited to the public source material they have access to on the internet. Don’t feel you have to have all of the answers, as this is a continually evolving issue.
One way to help encourage students to make better decisions about using tools such as ChatGPT is to design your class such that students can focus on a deep understanding of knowledge and skills rather than simply trying to achieve a particular score on an test or essay. The following tips for encouraging deep understanding include the following:
- Offering flexible evaluation design: consider providing opportunities for students to revise and redo specific portions of assignments;
- Focusing feedback on process and effort: offer feedback oriented toward student effort and their learning processes rather than on high grades and performance relative to others. When possible offer elaborative feedback rather than feedback based simply on correctness.
- Building a sense of belonging: discuss, emphasize, and model that making errors and mistakes is part of everyone's learning processes rather than something that only poor performers or people who "don't get it" do.
- Introducing all the components of your assignments early as student use of the AI tools in a way that is not allowed by your policies can be the result of inadequate communication and/or deadlines that do not correspond to the complexity of the assignment(s)
- Offering clear pathways for student discussion and Q&A so as to allow for a more transparent engagement and willingness to work with your students
References
40 AI tools for the classroom. (n.d.) Ditch That Textbook. https://ditchthattextbook.com/ai-tools/
Eight Principles of Effective Teaching (Rev. 2021). Center for Teaching and Learning. University of Texas at Austin. https://utexas.app.box.com/s/qc47fqg1c9n2nx4fbnj5zimv181aq03o
Backward design. (n.d.). Derek Bok Center, Harvard University. https://bokcenter.harvard.edu/backward-design
CAST (2018). Universal Design for Learning Guidelines version 2.2. Retrieved from http://udlguidelines.cast.org
Eaton, L. Syllabi policies for AI generative tools. (n.d.). Google Docs. https://docs.google.com/document/d/1RMVwzjc1o0Mi8Blw_-JUTcXv02b2WRH86vw7mi16W3U/edit#heading=h.1cykjn2vg2wx
Essentials of Learning. (n.d.) Center for Teaching and Learning. University of Texas at Austin. https://ctl.utexas.edu/instructional-strategies/essentials-learning
Flipped Classroom. (n.d.) Center for Teaching and Learning. University of Texas at Austin. https://ctl.utexas.edu/instructional-strategies/flipped-classroom
Morgan, D. (2024, June 24). Bloom's Generative Taxonomy. Mindjoy blog. https://blog.mindjoy.com/blooms-generative-taxonomy/
Raba, A. (2017). The Influence of Think-Pair-Share (TPS) on Improving Students’ Oral Communication Skills in EFL Classrooms. Creative Education, 8, 12-23.
University of Texas at Austin - Provost’s Office. (Rev. 2024). Developing learning outcomes for your course - Office of the Executive Vice President and Provost. Office of the Executive Vice President and Provost. https://provost.utexas.edu/the-office/academic-affairs/developing-learning-outcomes/
GenAI CTL Workshops
