3 AI-related steps to take now, and others to consider soon
If your interpretation of “GPT” is something akin to, “Go! Please? Today!,” we can help (at least a little).
Or if you aren’t sure how in the world of ones and zeroes you are supposed to deal with generative AI in your classes, let’s talk – human to human.
We can’t solve every AI-related challenge in teaching, but we have a good sense of how you can get started.
Without doubt, the swift spread of generative AI has complicated teaching, at least in the short term. We all share the lingering physical and mental exhaustion of living through a pandemic, exacerbated by demands on instructors to adapt to new generations of students, new expectations for assessment, and new modes of teaching. The arrival of generative AI feels like one more (GIANT) thing.
We don’t have all the answers to adapting teaching and learning in this new AI era. We do know one thing, though: We must adapt, and we must adapt quickly. Use of generative AI is growing quickly, and AI assistants are being integrated into the software we and our students use every day. We can’t avoid those changes, especially as the abilities of generative AI grow. We also understand that adapting assignments and class structures takes time.
Easy first steps
No matter where you stand on the use of generative AI in your classes, you should do at least three things before the semester starts.
1. Create syllabus language about AI use
This should include guidelines on how students may use generative AI in your classes and when they should not use AI. (See Maintaining academic integrity in the AI era for advice on what to include.)
- Even better: Draft a plan with students. Add a statement to your syllabus that the class will collectively draft a plan for acceptable AI use in your class. This gives students a voice in the process, not only empowering them but providing motivation to follow the policy. It also helps them understand how use of AI will (or won't) be acceptable in your class, since they were part of developing the course plan for it.
2. Plan conversations about AI
Students should understand how generative AI tools were created, how they work, and why they must be used with caution. So plan on using class time to discuss generative AI. Don't worry about having extensive understanding of generative AI or knowing all the terminology. Just be honest with your students and encourage them to ask questions. (See our list of readings and tools for ideas on possible topics for discussion or ways to use generative AI.)
- Even better: Create an assignment that asks students to explore the ethical use of generative AI in your discipline. One way to approach this is to have students read Kathryn Conrad's Blueprint for an AI Bill of Rights for Education. How does that help frame discussions we need to have in education? Which points seem most important? You might also have students consider these types of questions: How are professionals using generative AI? What boundaries have they set? Which disciplines are most accepting of generative AI? Which are most suspicious? Why?
3. Experiment with generative AI
No one expects you to be an expert in the use of generative AI. You should have a basic understanding of how it works and what it can do, though. Many students are already using tools like ChatGPT, and you should have a sense of how they might use them with your assignments.
- How to get started. To help you get a handle on generative AI, we have created tutorials on getting started with ChatGPT, Bing Chat, Bard, and Claude. You don’t have to be a technology expert to use any of those tools. One of their most powerful attributes – and one of the most challenging from an academic standpoint – is their ease of use. For the most part, you just need to sign in and ask good questions. We have also created a guide on writing prompts for generative AI and have curated many additional resources you can draw on.
Beyond the basics
Once you have taken those initial steps, you should consider how to integrate generative AI into your assignments. Explain to students that you plan to experiment with new approaches and that there will very likely be rough spots. Better yet, bring students into the process and have them suggest options the class might try. Again, you don’t have to be an AI expert to do this. You just have to be willing to listen to students, to learn from experimentation, and to adapt when things don’t go as planned.
Evaluate all your assignments
Which are most vulnerable to generative AI and how might you adapt them so that a chatbot can’t easily complete the work? (See below for ways to do that.) Even better, how could you integrate generative AI into those assignments? If that seems too daunting, work on it a little at a time.
Create exploratory assignments
Identify an assignment in which you encourage students to use AI tools in some way. (We have curated a list of generative AI tools to consider.) This will help students better understand the workings of AI, will help you learn more about AI, and will generate ideas on how you might adapt other assignments in the future.
- Even better: Take this approach with all your assignments.
Add a reflection component to assignments
Have students complete a brief reflection on how they went about their work. How did they use generative AI and how did they adapt the output so that the work is their own? This encourages transparency, but it also helps students improve their metacognition (the understanding of their own thought processes and learning). It also helps you better understand how students approach assignments and how you might improve the process in the future.
- Consider use of AI as a method. Most research has a methods section, requiring authors to explain how they gathered and analyzed data, and how they went about arriving at their conclusions. Generative AI is really just another method for completing tasks or assignments and arriving at conclusions. As such, students should explain how they use it just as they would any other method. If you choose not to add a reflection component to assignments, you should require some sort of disclosure in a methods section or in a simple statement at the end.
Adopt authentic assignments
Authentic assignments allow students to apply their developing knowledge to real-world situations, which can improve relevance and motivation for students (Wiggins and Grant, 1998). These can take many different forms, depending on the discipline. In general, though, authentic assignments involve application of learning in ways that students are likely to encounter in their careers, that allow students to share their learning outside the class, or that allow students to engage with outside communities or to apply disciplinary thinking to other fields or to a general audience. For example:
- Students in a chemistry class create posters about how chemical interactions affect everyday life (hand-washing, auto exhaust, water purification).
- Students in a psychology class create an op-ed article in which they use the principles of psychology to add new perspectives to an event in the news.
- Students in a journalism class work with a non-profit agency to create messages about the importance of mental health for high-school students.
- Students in a physics class create a graphic explaining what caused a deep-water submarine to explode.
- Students in a biology class hold an end-of-semester festival for which students groups create displays and activities that help attendees learn about threatened species.
- Students in a film and media studies class develop video and social media messages about the importance of digital literacy.
All of those examples helped students apply their learning in new ways. Generative AI offers powerful new opportunities to expand authentic assignments and to infuse them with technological skills that students will need in careers. In each of the examples above, generative AI could be used to generate ideas, provide examples, create images and illustrations, design posters and brochures, and create drafts of materials. It could also be used to create discipline-specific case studies or create interactive scenarios in which students grapple with real-world problems. Instructors could also challenge students to create examples of how generative AI could be used in various professions. That would help students learn more about potential careers while also considering ways that technology may change a profession.