There are both academic and practical reasons you may choose to incorporate generative AI assignments into your course. For example, you may believe that AI will be a skill needed in the students’ future careers in your field. Perhaps you see AI as a tool to help students deepen their understanding of and engagement with your content. You may see the introduction of AI into your classroom as a way to open a conversation about its ethical and academic implications. Integrating AI ironically allows instructors to think deeply about how to design assignments that cannot be easily generated by AI alone to deter plagiarism and cheating. If instructors fold generative AI into their courses successfully, this resource suggests students benefit from learning about AI in a way that is both academic and practical.
This guide comes from the perspective that you are open to developing AI assignments. If you are looking for guidance on how to deter students from using AI, refer to the advice from the teaching and learning center at NC State as a starting point. They suggest incorporating active learning and rewriting assignment prompts.
Note, it is critical to develop AI policies for your course along with policies for specific AI assignments.
Considerations for Developing an AI Assignment
Alignment with Your Course Goals
In the development of AI assignments, the primary consideration is whether the use of AI will help your students achieve the learning goals of the course. Ask yourself, does this assignment help student gain skills and knowledge central to your course and field? Furthermore, consider whether the assignment is engaging enough to warrant incorporating AI. Are you asking students to go above and beyond the AI-generated content? An impactful assignment will challenge students to transform, expand upon, correct, or critique the information and text generated by AI or learning about themselves in relationship to AI. Educational pedagogy expert Derek Bruff gives further insight into how to think about AI assignments as they relate to course design in his blog post about AI and writing assignments.
Guidelines for Use
If you assign AI assignments, be sure to discuss your expectations with your students. It is essential that they understand why you have decided to allow AI in the course and its role in their learning. Furthermore, students can be engaged in wider conversations about AI and its personal impact on their lives. The University of Calgary has developed a set of recommendations of how to start these conversations. One strategy is writing a code of conduct that emphasizes critical thinking and sets guardrails of proper use. You can provide a pre-written list or work with the students from scratch by posing questions about AI and learning.
For example, the class may have guidelines such as:
- We will only use AI to help our intellectual development, not replace it.
- We will be transparent in our use of AI.
- We will not submit AI generated text without attribution.
- We will follow guidelines of when AI is appropriate to use.
Detailed instructions for an AI assignment will raise the chances for a successful learning experience. Students are not familiar with the processes of the novel type of intellectual work, and thinking through the different facets of the activity will help you to execute and evaluate the assignment confidently. Consider the following questions:
- Are you allowing ample time to complete the assignment considering it is a new tool for students?
- Is it better to do the assignment together in class or out of class?
- Have you practiced using the technology together?
- How should AI be cited? Are there specific steps for showing how the original AI text is changed?
- What kind of prompts are allowed? What functions can AI be used for?
- How will you provide feedback on their use of AI?
Both you and your students should have a level playing field when it comes to understanding generative AI. You cannot count on students to understand the pitfalls and limitations of AI or even how to use the tools. There are existing resources on AI literacy developed specifically for students that can be a starting point. This library guide from the University of Arizona instructs students on AI, plus there is a companion guide for instructors as well.
There are ethical issues to using AI beyond questions of plagiarism, copyright and academic integrity that should be considered. First, to minimize threats to the privacy of your students and yourself, personal information should not be shared. To dive deeper into privacy concerns, speak with students about the implications of AI services using our data to train their tools.
Second, students may not have equal access to the internet or sufficient funds for subscriptions to AI tools. Be sure to suggest several different AI tools and confirm that students are able to access at least one tool without paying for it. Not all students may take to generative AI equally and will not have the skills to architect effective prompts for your discipline or type of assignment. You can support them by modeling prompt generation or forming groups in class in which they work together with AI.
Finally, for instructors who do allow AI for learning, there should be considerations for students who do not want to use it on ethical grounds. This could be solved by making AI assignments low-stakes or optional.
Types of Generative AI Assignments
Below are some general idea of how to incorporate AI into your course. We encourage you to seek out examples from your discipline or related to the core skills of your course. Some resources worth exploring are the curated examples by the Writing Across the Curriculum Clearinghouse at Colorado State University and a recent publication on coding and generative AI by an international group of computer science instructors.
Brainstorming Ideas and Defining Concepts
Generative AI excels at summarizing texts and summarizing content. Warning, it is not necessarily 100% correct!
- Users can ask AI to brainstorm research questions. “What are some examples of bank failures due to fractional reserve banking?” Or, “What are some of the major events of the Cold War?”
- Users can ask AI for clarification of a concepts or terms they don’t understand. “Explain fractional reserve banking in simple terms.” Or, “What are the Federalist papers and why are they important?”
- Instructors can ask for resources or ideas of how to teach students content. “Provide an explanation of fractional reserve banking which discusses the pros and cons of its use.” Or, “What are some exercises to do in the classroom to teach the lifecycle of a butterfly?”
While it is possible to use generative-AI to correct an entire essay, students can prompt AI to provide limited feedback on specific aspects of their writing as part of an assignment. Prompts could be limited in scope. For example, students can ask AI to:
- Rate the clarity of an argument “How well did I explain X?” Or, “Does this writing contain all of the standard sections of a case study ?”
- Suggest alternatives “Rewrite the conclusion to better summarize the content.” Or, “What is another way to explain this idea?”
- Comment on writing mechanics “Review the sentence structure in this essay.” Or, “Check this essay for passive voice.”
- Provide advice for improvement “List the common grammar mistakes in the essay and provide an explanation of the errors.” Or, “How can I make this writing more upbeat?”
One popular assignment helps instructors show why writing for yourself is important intellectual work. Student read an AI-generated essay and grade it with a rubric. As a class the students discuss its strengths and weaknesses. As a follow-up students can submit a revised essay. In a recent Yale course, the instructor told students to ask ChatGPT to write its own version of a writing prompt and compare their writing against it.
Another approach to a collaboration is to ask AI to write a first draft of an assignment. Students then improve it by doing independent research to double-check the AI content and refining (or rejecting) the AI arguments. Students should record both the questions they asked and the generated text. Students can also be asked to write summaries describing what they learned from the AI search and what they changed. The SPACE framework is a powerful model for organizing these types of writing assignments, which details the cycle of prompting AI, evaluating its output, and rewriting AI generated content.
Arguably, the greatest strength of generative-AI tools may be its ability to write code. Computer scientists are especially concerned about assignments in entry-level programming classes. The way coding is taught may change over time due to AI, but there are a few short-term strategies that incorporate AI but demand student input.
- AI could be asked to generate small snippets of code that students integrate into a larger programming project. Students test, debug and refine the code.
- After completing a coding assignment, students prompt AI to write a different implementation of the problem and analyze which is more efficient and why.
- Instructors or students write faulty code and use ChatGPT to generate test cases and/or to fix the errors.
- Instructors take advantage of AI to generate more coding assignments and review questions for exams.
Two researchers from UC San Diego recently published the findings of a study about the attitudes of computer scientists to generative AI and possible directions for teaching coding in the future.
ChatGPT and other generative AI tools are not just conversational partners for content only. They are also able to mimic authors’ styles and generate content in many genres, often with laughable results (“Write a pop song in the style of Shakespeare”) The breadth of the kinds of writing they can mimic provides the chance for humans to use the flexibility generative AI to spark creativity in themselves. Student might ask AI to describe the life the Middle Ages from the perspective of a midwife as inspiration for another type of writing assignment such as a podcast. Generative AI can help instructor approach how they deliver content in new ways, for example introducing games into teaching. Instructors might ask AI to develop trivia questions for exam review or a game of 20 questions as an in-class activity.
Generative AI can be a coach for learning that supports both instructors and students. Students can easily get more information about what they don’t understand. AI can be an agent for adaptive learning allowing students to “pass” certain learning objectives and get additional practice on concepts and skills they haven’t mastered. By the same token, it can assist instructors who need to provide additional assistance to students and are pressed for time to find resources. Instructors can get ideas for teaching a skill or subject with activity descriptions and lesson plans. AI can generate practice problems or review questions for exam prep, which frees up time for instructors for other class prep.
There are also positive gains in equity when generative AI is used in a tutoring setting. A neurodiverse student may find conversations with a bot to be non-judgmental and less stressful when needing help. Non-native speakers can ask for word and concept definitions to level up their understanding of course content and context. The review and tutoring capabilities of AI can help all students to practice concepts and problems with feedback on their progress.
Incorporating generative-AI into education is not without peril. Students’ reliance on AI content could potentially lead to students losing skills in academic writing. There is the risk that students might mistakenly believe that AI is inherently better at developing ideas and expressing information; leaving students uncomfortable adding their own voice to writing. Without training on how to check the validity of AI content and conduct independent research, students may miss out on how to evaluate sources and compare ideas.
Like it or not, at this moment it lands on educators to design courses and assignments to mitigate these risks and to have hard and timely conversations with students. It may feel like AI is encroaching on teaching and learning, but we should remember that there are many aspects of teaching that are as important as delivering content. These are skills that only human instructors can perform, such as
- Providing real-time feedback on complex tasks
- Grading or producing subjective or substantive work
- Providing social or emotional support
- Teaching complex, interconnected concepts
- Engaging in personal interactions
The future of teaching may increasing focus on those skills that our students need to make sense of their world, engage with others productively and make connections across disciplines and concepts.
General Resources for AI Assignments
Positive Uses of ChatGPT in Higher Educational Classrooms, University of North Texas (2023)
A Teacher’s Guide to Prompt ChatGPT, Andrew Herft
AI in the Classroom, UC Riverside