I pulled together my notes from the last 9 months of doing sessions on Generative AI and compiled them yesterday. Shout out to Nick Baker for adding some things, editing some things and overall making it more nicely to readish.
Every time I approach this issue I keep thinking that so much more and probably a lot less should be said. Every time I meet with a group of faculty or teachers on this issue we go through a few phases
- Boredom, kinda, as I explain what generative AI is.
- A bit of ‘yeah, this doesn’t apply to me, my courses…’
- A demonstration where I take their actual assignments and complete them in 30 seconds using generative AI
- And then, hope. Hope when they realize that the only solution is good teaching.
That is in no way meant to reflect a statement about all faculty or teachers. I only really get the ones who care about teaching and their students.
Anyway… this is what I’ve been telling them.
Generative AI has already changed education. Whether we realise it or not, every student has been forced to make a decision about whether they are going to use AI to generate text, videos or images. Of particular importance to those of us in the teaching profession, we have lost our ability to make students write their own texts when we are not watching them. Regardless of your position on the inclusion of generative AI in the classroom, this is likely to have a profound impact on your classroom.
The following checklist is emergent. We will continue to add to it as situations develop and new approaches emerge.
Dave Cormier and the Office of Open Learning, UWindsor.
Have I included my own stance regarding Generative AI in my syllabus?
There is no agreed upon way for people to be handing these systems right now. So, whether you’re talking about Chegg or ChatGPT, be clear in your syllabus how you expect students to use it (or not). This will not, on its own, stop people from doing things, but it will at least make it clear for someone who wants to do the right thing.
- Tell them what you would like them to do
- Give them tools that you think are appropriate
- Find ways to incorporate ethical usage of these tools into your classroom teaching practice
- Syllabi Policies for Generative AI
- What Should a Syllabus Statement on AI look like?
- Should you ad an AI Policy to Your Syllabus?
Have I explained what counts as engagement in my course and explained why I want students to do the work that I am asking them to do? Have I added an explanation to each of my readings/assessments explaining to students why it’s important and how it is connected to the learning outcomes?
One of the ways of addressing students’ illegitimate usage of Generative AI tools is to explain to them why you want them to do the work laid out in your syllabus. We have, historically, forced students to do their homework by awarding them grades for completion. If students are doing their work to ‘complete’ it, instead of being driven by actual interest, they are going to be far more likely to find ways to complete their work without having to learn anything.
- Encourage students to find ways to be interested in the work in the classroom
- Share your own reasons for finding the material interesting
- Find ways to highlight examples of students performing in an engaged manner
Have I considered why I was using the take home assessments affected by generative AI (e.g. right answer questions, long form text like essays)? Can I replace them with new approaches that serve the same purpose?
There are many good arguments out there for the writing of essays and other long-form writing tasks. They promote deeper thinking, give students more space to construct critical arguments, and have strong disciplinary connections in some cases. They are a common means of demonstrating the student’s developing set of research skills. In the past, we were often able to assume with reasonable confidence that essays and extended writing were a sound way to be assured that students were developing those skills. It has always been possible to pay someone else to write your essay, though and with the new tools available, and the relatively inexpensive rates available at essay mills, there is no longer any guarantee that any student is doing these things.
- Consider using point form responses submitted in class
- Consider deconstructing the essay (an argument assignment, a research assignment) that never leads to a completed essay
- How writing should be taught?
- 6 Tenets of Postplagiarism: Writing in the Age of Artificial Intelligence
Are there places where I am trying to ‘cover’ content that I can remove and allow for deeper work on more important topics?
There are many reasons that can lead to us needing to ‘cover’ certain kinds of material in a classroom. It could be that we are mandated by accreditation bodies, it could be that there is a course deeper in the degree that is counting on us to develop some foundational knowledge or skills. But this is not always the case. Many of us inherit the courses we teach and don’t entirely understand why a given topic is included in the course. Teaching less, and teaching more deliberately, allows us the time to delve into the nuances of a topic.
Have I provided enough time to allow my students to unlearn old ways of doing things before they can take on the new ones that I’m presenting?
The abilities that come with generative AI will likely lead to some changes in your course. It is critical that students get time to learn these new processes, so that they know what it means to be successful in your course. Skills that may have been valued when they were in high school may no longer be as important, and the changes made by one faculty member may not work in your class. Give students time to make those adaptations so they have their best chance at success.
Have I made ethical decisions about student data such that the assignments and activities in my class don’t require students to give away their own personal identification or their work to outside companies?
Each of the digital tools that we use in our classroom take different amounts of personal information and intellectual property from students. We can inquire of our IT departments for information regarding the usage of student data in our institutions. The guideline is simple: treat our student’s data the way we want our own data treated.
Have I reviewed how my field is being affected by the web and AI generation? If it’s significant, have I included this in my course?
Generative AI is going to have vastly different impacts by field. Reach out to your colleagues across your respective fields and get a sense of how AI is impacting their day-to-day work. Many disciplines have started to collect and share ideas within their communities of practice. Some professional associations have also provided their guidance. There is much still to learn as the use and capabilities of these tools evolves.
Have I incorporated new best practices for finding/evaluating knowledge in my field that take AI generated content/marketed content into account? (e.g. Prompt engineering exercises)
As our knowledge work is increasingly mediated by algorithms like search engines and text generators, it’s vital that we learn how to best find, sort and evaluate information from these systems. While there are certainly common good practice approaches that apply across fields, some approaches (e.g. using curated databases) are going to be discipline specific. Incorporating activities that help learners use, manipulate and trick the algorithms to bring back the results they need, and of which they can be confident of reliability, are essential to developing 21st century literacies.
Given the abundance of information available, good and bad, often the most important literacy any student needs is to be able to sift through information to find what is most true or most useful. Building those activities into our courses might be the most important thing we can do to help students in their futures.
- SIFT – A guide to evaluating information found online
- Does it matter if we call it prompt engineering
Have I confirmed that the changes I’ve made to my syllabus have not created an unfair amount of work for me or my students?
Anytime we rework our syllabus, there is a chance that we add more work than we had in our previous versions, sometimes without noticing. Make sure to consider the total number of hours that all of the planned activities (class time, labs, assignments, group work, independent research, reading, watching content, quizzes etc.) in our syllabus imposes on our students, and be careful to explain your work expectations to your students. Be mindful that students have many other classes, often with the same requirements as yours, as well as commitments outside of university. The more we load students with busy work, the less time they have to do the things that most of us value most – deeply engaging with the topics of our courses and demonstrating that engagement through our assessment tasks.
- How Much Work Should My Course Be For Me And My Students?
- UOttawa Student Course Workload Estimator (based on Rice University’s courseload estimator)
- UBC Student Course Time Estimator
- Adapting your syllabus to AI
Have I considered the accessibility implications of the digital tools I am using? Do they have the potential to improve or reduce accessibility?
Every tool comes with its own affordances. Think your way through the classroom advantages and disadvantages to any tool you are going to use. Has the tool been formally assessed for accessibility by the University? Have you talked to OOL or CTL about it? Have you tried checking it with an online accessibility checker such as WAVE or AccessiBe? Does it require new computers to run it? Does it require a login? Does it have visual elements that disadvantage some students? Do all images used have alternative text? Does it require high speed internet? Does it work the same way on a mobile device such as a phone or tablet? How does it interact with screen readers or text to speech tools? Does it require high levels of physical dexterity? Can it be controlled from a keyboard only? What is the cost of the tool and who is expected to pay for it? These and many more questions should inform any decision to use a technology in our teaching.