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!

How Will Generative AI Change My Course? (GAI Checklist)

With the growing prevalence of generative AI applications and the ongoing discussions surrounding their integration in higher education, it can be overwhelming to contemplate their impact on your courses, learning materials, and field. As we navigate these new technologies, it is crucial to reflect on how generative AI can either hinder or enhance your teaching methods. CATL has created a checklist designed to help instructors consider how generative artificial intelligence (GAI) products may affect your courses and learning materials (syllabi, learning outcomes, and assessment).

Each step provides guidance on how to make strategic course adaptations and set course expectations that address these tools. As you go through the checklist, you may find yourself revisiting previous steps as you reconsider your course specifics and understanding of GAI.

Checklist for Assessing the Impact of Generative AI on your Course

View an abridged, printable version of the checklist to work through on your own.

Step One: Experiment with Generative AI

  • Experiment with GAI tools. Test Copilot (available to UWGB faculty, staff, and students) by inputting your own assignment prompts and assessing its performance in completing your assignments.
  • Research the potential benefits, concerns, and use cases regarding generative AI to gain a sense of the potential applications and misuses of this technology.

Step Two: Review Your Learning Outcomes

  • Reflect on your course learning outcomes. A good place to start is by reviewing this resource on AI and Bloom’s Taxonomy which considers AI capabilities for each learning level. Which outcomes lend themselves well to the use of generative AI and which outcomes emphasize your students’ distinctive human skills? Keep this in mind as you move on to steps three and four, as the way students demonstrate achieved learning outcomes may need to be revised.

Step Three: Assess the Extent of GAI Use in Class

  • Assess to what extent your course or discipline will be influenced by AI advancements. Are experts in your discipline already collaborating with GAI tools? Will current or future careers in your field work closely with these technologies? If so, consider what that means about your responsibility to prepare students for using generative AI effectively and ethically.
  • Determine the extent of usage appropriate for your course. Will you allow students to use GAI all the time or not at all? If students can use it, is it appropriate only for certain assignments/activities with guidance and permission from the instructor? If students can use GAI, how and when should they cite their use of these technologies (MLA, APA, Chicago)? Be specific and clear with your students.
  • Revisit your learning outcomes (step two). After assessing the impact of advancements in generative AI on your discipline and determining how the technology will be used (or not used) in your course, return to your learning outcomes and reassess if they align with course changes/additions you may have identified in this step.

Step Four: Review Your Assignments/Assessments

  • Evaluate your assignments to determine how AI can be integrated to support learning outcomes. The previous steps asked you to consider the relevance of AI to your field and its potential impact on students’ future careers. How are professionals in your discipline using AI, and how might you include AI-related skills in your course? What types of skills will students need to develop independently of AI, such as creativity, interpersonal skills, judgement, metacognitive reflection, and contextual reasoning? Can using AI for some parts of an assignment free up students’ time to focus more on the parts that develop these skills?
  • View, again, this resource on AI capabilities versus distinctive human skills as they relate to the levels of Bloom’s Taxonomy.
  • Define AI’s role in your course assignments and activities. Like step three, you’ll want to be clear with your students on how AI may be used for specific course activities. Articulate which parts of an assignment students can use AI assistance for and which parts students need to complete without AI. If AI use doesn’t benefit an assignment, explain to your students why it’s excluded and how the assignment work will develop relevant skills that AI can’t assist with. If you find AI is beneficial, consider how you will support your students’ usage for tasks like editing, organizing information, brainstorming, and formatting. In your assignment instructions, explain how students should cite or otherwise disclose their use of AI.
  • Apply the TILT framework to your assignments to help students understand the value of the work and the criteria for success.

Step Five: Update Your Syllabus

  • Add a syllabus statement outlining the guidelines you’ve determined pertaining to generative AI in your course. You can refer to our syllabus snippets for examples of generative AI-related syllabi statements.
  • Include your revised or new learning outcomes in your syllabus and consider how you will emphasize the importance of those course outcomes for students’ career/skill development.
  • Address and discuss your guidelines and expectations for generative AI usage with students on day one of class and put them in your syllabus. Inviting your students to provide feedback on course AI guidelines can help increase their understanding and buy-in.

Step Six: Seek Support and Resources

  • Engage with your colleagues to exchange experiences and practices for incorporating or navigating generative AI.
  • Stay informed about advancements and applications of generative AI technology.

Checklist for Assessing the Impact of Generative AI on Your Course © 2024 by Center for the Advancement of Teaching and Learning is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

Want More Resources?

Visit the CATL blog, The Cowbell, for more resources related to generative AI in higher education.

Need Help?

CATL is available to offer assistance and support at every step of the checklist presented above. Contact CATL for a consultation or by email at CATL@uwgb.edu if you have questions, concerns, or perhaps are apprehensive to go through this checklist.