Assessment and Assignment Guidance in the GAI Era

CATL is often asked questions about how to approach assessments in the wake of easy access to generative artificial intelligence (GAI). We hope to crowd-source suggestions and examples from our own instructors so that we can build a repository of work from the UWGB community in Canvas. Please take our GAI Assignment Repository survey if you have any ideas or assignment samples that you are willing to contribute. We will collect results and share them once we have a critical mass. In the meantime, please feel free to use these resources from other institutions or professional organizations.

Deterring the Use of GAI

One of the most frequent concerns expressed by instructors is that students will simply use GAI to complete their assignments. It makes very good sense to type your own assignment prompt into Copilot or another GAI tool to see if it can complete the assessment – and modify the assignment if it can. Although these are not perfect strategies, multiple authors have suggested the following mitigation strategies:

  • Be very clear with students about your GAI policy and talk with them about the reasons for it and for completing their work independently. Carleton College has an interesting site aimed at a student audience about GAI use and evolving understandings of academic integrity that you could use to frame a discussion with your class.
  • Use shorter, more frequent assessments that build on each other to reduce the motivation to use GAI that can come with a small number of high-stakes/point assignments.
  • Scaffold your assignments such that each one builds on another.
  • Create assessments that involve integration of material from class (which GAI does not have access to) with other sources.
  • Require some element of reflection on the learning experience or completing the assignment.
  • Ask students to submit outlines, drafts, or save their document history in Word or Google Docs to show the evolution of a paper or project.
  • Consider the use of oral presentations, including question and answer, as a method for demonstrating understanding.
  • Employ in-class writing assignments such as Minute Papers for face-to-face courses.

The Office of Digital Learning at UN-Reno has created a more detailed document with strategies for re-designing assessments in the GAI era.

Teaching About the Use and Ethics of GAI

Some instructors are seeking strategies for teaching students about GAI and how to use it, as well as about related issues, such as the ethics of use. Instructors from the University of Central Florida collected more than 60 assignments related to GAI, including the teaching of prompt engineering. The New School has a shorter, more direct page of instructions for prompt creation. Co-Intelligence author Dr. Ethan Mollick and collaborator Dr. Lilach Mollick have created an extensive paper that outlines seven complex ways to use GAI in education, and they include sample prompts and a discussion of the potential risks of their ideas. Finally, as just one example of teaching about the ethics of AI use, consider this assignment designed, in part, to teach about cultural bias in GAI.

Creating Assessments that Make Use of GAI

Finally, there are instructors looking for creative assignments that use GAI as an intentional tool in an assessment to facilitate student learning. Numerous universities and organizations have assembled collections of such assignments, including the following:

Remember, we hope to create a collection of examples from UWGB instructors. Please complete our survey today to share your contribution with your colleagues!

Sample Assignments for Different Approaches to GAI Use

In a previous CATL article, we recommended using the traffic light model to guide students on the appropriate use of generative AI (GAI) in assignments and course activities. Assuming you’ve already included a policy on GAI in your syllabus, it’s also important to provide clear instructions in your assignment descriptions. Below are some examples of assignment descriptions, using the traffic light approach and graphic. Instructors will vary on whether they want to use that visual or simply explain in words. If you choose to use the stoplight visuals, please be sure to provide an accompanying description of what that means for your specific assignment. While tailored to specific subjects, these samples share common strategies.

Consider the following general suggestions when designing your assignments:

  • Be clear and specific about GAI use in your syllabi and assignments. Clearly outline when and how GAI can be used for assignments and activities. Avoid ambiguity so students know exactly what’s expected. For example, if brainstorming is allowed but not writing, specify that distinction.
  • Include GAI usage disclaimers in assignment directions. Regularly remind students by adding a GAI disclaimer at the beginning of assignment instructions. This will make them accustomed to looking for guidance on AI use before starting their work.
  • Explain the rational for AI use or nonuse. Help students understand the reasoning behind when GAI can or cannot be used. This can reinforce the learning objectives and clarify the purposes behind your guidelines.
  • Clarify the criteria for evaluating AI collaboration. Specify how assignments will be graded concerning AI use. If students need to acknowledge or cite their AI usage, provide specific instructions on how they should do so.
  • Define which AI tools students can use. Should students stick to Microsoft Copilot (available to them with their UWGB account, so they don’t have to provide personal information to a third party or pay a subscription fee) or can they use others like ChatGPT?
  • Use the TILT framework. Leading with transparent design for assignments and activities helps students clearly understand the purpose, tasks, and assessment criteria. This framework can also help instructors clarify how GAI should be used and assessed in assignments.

Sample Assignment Instructions on AI Use

Red Light Approach: No GAI Use Permitted Assignment Example

The example below is for a writing emphasis course and the assignment purpose is to evaluate students’ own writing. For this assignment, GAI tools are not allowed. The instructor includes an explanation of this description to further clarify the assignment’s purpose.

Yellow Light Approach: GAI Use Permitted for Specific Tasks/Tools Examples

The yellow-light approach can be hard to define depending on what you want students to practice and develop for a given assignment. We’ve provided two samples below that each take a slightly different approach, but all clearly label what tools and for what tasks AI can be used and why.

Green Light Approach: All GAI Use Permitted

Instructors may choose to take a green light approach to AI for all assignments or allow AI use for selected assignments. The example below takes a low-stakes approach, permitting full AI use to encourage experimentation. Even with this method, instructors should provide clear assignment expectations.

Learn More

Explore even more CATL resources related to AI in education.

Dr. C. Edward Watson to Present at UW-Green Bay: Teaching with Artificial Intelligence (Aug 29, 2:00 p.m)

Preparing Students for Life Beyond College: Embracing AI as Essential Learning

UW-Green Bay is excited to welcome Dr. C. Edward Watson, Vice President for Digital Innovation at the American Association of Colleges and Universities and co-author of “Teaching with AI: A practical guide to a new area of human learning.” Mark your calendars as we kick off a new fall semester together with Dr. Watson’s presentation and read on to learn more about the presentation topic! This event is for UWGB faculty and staff. If you did not receive an Outlook invitation for this presentation, please send an email to CATL, and we will get you added to the event!

  • When: Thursday, August 29, 2024, at 2:00 p.m.
  • Where: Virtual presentation hosted in Zoom

Preparing Students for Life Beyond College: Embracing AI as Essential Learning

Generative AI tools have had an astonishingly quick impact on the ways we learn, work, think, and create. While higher education’s initial response was to develop strategies to diminish AI’s influence in the classroom, many would now argue that AI competencies and literacies must be embraced as essential learning for most colleges and universities. These responses and realities create a challenging tension that higher education must work to resolve. Drawing from the presenter’s new book, Teaching with AI: A Practical Guide to a New Era of Human Learning (Johns Hopkins University Press, 2024), this presentation and discussion will detail the challenges and opportunities that have emerged for higher education. The core focus of this keynote will be on concrete approaches and strategies higher education can adopt, both within the classroom and across larger curricular structures, to best prepare students for the life that awaits them after graduation.

Presenter Bio

Photo of Eddie Watson

C. Edward Watson, Ph.D., is the Vice President for Digital Innovation at the American Association of Colleges and Universities (AAC&U). He is also the founding director of AAC&U’s Institute on AI, Pedagogy, and the Curriculum. Prior to joining AAC&U, Dr. Watson was the Director of the Center for Teaching and Learning at the University of Georgia (UGA) where he led university efforts associated with faculty development, TA development, learning technologies, and the Scholarship of Teaching and Learning. He continues to serve as a Fellow in the Louise McBee Institute of Higher Education at UGA and recently stepped down after more than a decade as the Executive Editor of the International Journal of Teaching and Learning in Higher Education. His most recent book is Teaching with AI: A Practical Guide to a New Era of Human Learning (Johns Hopkins University Press, 2024). Dr. Watson has been quoted in the New York Times, Chronicle of Higher Education, Inside Higher Ed, Campus Technology, EdSurge, EdTech, Consumer Reports, UK Financial Times, and University Business Magazine and by the AP, CNN and NPR regarding current teaching and learning issues and trends in higher education.

UWGB Free Access to Teaching with AI

UWGB faculty and staff can get free unlimited access to the text Teaching with AI through the UWGB library!

My Resistance (and Maybe Yours): Help Me Explore Generative AI

Article by Tara DaPra, CATL Instructional Development Consultant & Associate Teaching Professor of English & Writing Foundations

I went to the OPID conference in April to learn from colleagues across the Universities of Wisconsin who know much more than I do about Generative AI. I was looking for answers, for insight, and maybe for a sense that it’s all going to be okay.

I picked up a few small ideas. One group of presenters disclosed that AI had revised their PowerPoint slides for concision, something that, let’s be honest, most presentations could benefit from. Bryan Kopp, an English professor at UW-La Crosse, opened his presentation “AI & Social Inequity” by plainly stating that discussions of AI are discussions of power. He went on to describe his senior seminar that explored these social dynamics and offered the reassurance that we can figure this thing out with our students.

I also heard a lot of noise: AI is changing everything! Students are already using it! Other students are scared, so you have to give them permission. But don’t make them use it, which means after learning how to teach it, and teaching them how to use it, you must also create an alternate assessment. And you have to use it, too! But you can’t use it to grade or write LORs or in any way compromise FERPA. Most of all, don’t wait! You’re already sooo behind!

In sum: AI is everywhere. It’s in your car, inside the house, in your pocket. And (I think?) it’s coming for your refrigerator and your grocery shopping.

I left the conference with a familiar ache behind my right shoulder blade. This is the place where stress lives in my body, the place of “you really must” and “have to.” And my body is resisting.

I am not an early adopter. I let the first gen of any new tech tool come and go, waiting for the bugs to be worked out, to see if it will survive the Hype Cycle. This year, my syllabus policy on AI essentially read, “I don’t know how to use this thing, so please just don’t.” Though, in my defense, the fact that I even had a policy on Generative AI might actually make me an early adopter, since a recent national survey of provosts found only 20% were at the helm of institutions with formal, published policy on the use of AI.

So I still don’t have very many answers, but I am remembering to breathe through my resistance, which has helped me develop a few questions: How can I break down this big scary thing into smaller pieces? How might I approach these tools with a sense of play? How can I experiment in the classroom with students? How can I help them understand the limitations of AI and the essential nature of their human brains, their human voices?

To those ends, I’d like to hear from you. Send me your anxieties, your moral outrage, your wildest hopes and dreams. What have you been puzzling over this year? Have you found small ways to use Generative AI in your teaching or writing? Have your ethical questions shifted or deepened? And should I worry that maybe, in about two hundred years, AI is going to destroy us all?

This summer and next year, CATL will publish additional materials and blog posts exploring Generative AI. CATL has already covered some of the “whats,” and will continue to do so, as AI changes rapidly. But, just as we understand that to motivate students, we must also talk about “the why,” we must make space for these questions ourselves. In the meantime, as I explore these questions, I’m leaning into human companionship, as members of my unit (Applied Writing & English) will read Co-Intelligence: Living and Working with AI by Ethan Mollick. We’re off contract this summer, so it’s not required, but, you know, we have to figure this out. So if we must, let’s at least do it over dinner.

A colorful, geometric, and somewhat abstract illustration featuring buildings and streets covered with arrows, numbers, and the text "AI"

Generative AI and Assessments Workshop (June 28, July 18, Aug. 8, & Aug. 30, 2023)

Please join CATL for a virtual summer workshop focused on creating assessments in the age of generative AI (e.g., ChatGPT)! CATL facilitators will work with instructors to review their learning objectives, discuss the implications of emerging AI products, and brainstorm creative, high-quality, aligned, and feasible strategies for adapting course materials and assessments.

To participate in this virtual workshop, CATL asks that instructors bring a course syllabus with learning outcomes, ideas for at least two assessments for that course, and a willingness to engage in a reflective process that includes thinking about how generative AI technologies might impact those course materials. This workshop, “Generative AI and Assessments,” will occur three times throughout the summer months with more offerings to come in the fall. While registration is not required to attend, we encourage you to register today to receive a calendar reminder for the timeslot that works best for you!

Workshop Dates and Times:

All sessions are fully virtual and will meet via Microsoft Teams. Each workshop will be the same so please only sign up for one timeslot.

If you need accommodation for this virtual event, please contact CATL at CATL@uwgb.edu.

Register