7 Questions on Generative AI in Learning Design
Open LMS Adoption and Education Specialist Michael Vaughn on the challenges and possibilities of using artificial intelligence to move teaching and learning forward.
The potential for artificial intelligence tools to speed up course design could be an attractive prospect for overworked faculty and spread-thin instructional designers. Generative AI can shine, for example, in tasks such as reworking assessment question sets, writing course outlines and learning objectives, and generating subtitles for audio and video clips. The key, says Michael Vaughn, adoption and education specialist at learning platform Open LMS, is treating AI like an intern who can be guided and molded along the way, and whose work is then vetted by a human expert.
We spoke with Vaughn about how best to utilize generative AI in learning design, ethical issues to consider, and how to formulate an institution-wide policy that can guide AI use today and in the future.
The following interview has been edited for length and clarity.
Campus Technology: Could you tell us a little bit about yourself, your role at Open LMS, and your background in higher ed?
Michael Vaughn: As an adoption and education specialist at Open LMS, I work with our clients in training and development capacities. Sometimes that's onboarding, just bringing folks into the system; sometimes that's courses in our academy site; sometimes that is generating new training materials. I have a lot of leeway and freedom in what I work on, which I really appreciate. And so that's where I've been able to dedicate some time and energy toward learning a little bit more about AI, some of the tools and platforms out there, and how we might communicate responsible use of those tools to our clients.
Prior to that, I worked in instructional technology and educational technology for over 15 years. I got my start at Cuyahoga Community College in Cleveland, OH, back in the Blackboard 6 days — I think it was WebCT Vista around that time — doing support and training for folks there with the LMS. I moved over to Kent State University for a spell, where I worked on really small teams to build fully online courses alongside faculty who were serving as subject-matter experts. After that I joined Elon University, where I was an instructional technologist for the better part of a decade and co-founded the university's first makerspace. I also served on the advisory board for the REALISE grant at Radford University, which was a Howard Hughes-funded initiative to promote diversity, equity, and inclusion within the sciences.
CT: Where do you see the biggest potential for the use of technologies like generative AI in learning design?
Vaughn: Where AI really thrives is in automating tasks that can typically be cumbersome, as well as finding patterns in large sets of data that would be difficult for us to uncover quickly. The metaphor that I tend to use with folks is: If you hired someone to come to your house and build a deck, and they showed up with a screwdriver and started putting in all the screws by hand, you would probably be a little annoyed — especially if you're paying them by the hour. It's going to get the job done; it's just going to take a while. No one would look at that carpenter and say that using a drill is somehow inappropriate — it makes perfect sense that you would use a tool that does the exact same thing much faster. It's more efficient, it's a better use of time, and it allows them to focus on other things. You get your deck faster, and they get to move on to another job faster.
That's where I see AI fitting in within the world of higher education: If we're looking at tasks that are historically very time consuming, we can start to use AI and generative AI platforms to dramatically speed up how we do those things. To give a specific example, if I am teaching two sections of the same course, I don't want to have the students in one section take a quiz on Monday and then use the exact same questions for the other section on Tuesday. With generative AI, I could take that question set and use a tool like ChatGPT to reword the questions so that they require a different response, even though they're still testing the same concept or idea. Now I've taken something that historically would have taken me a really long time to do — rework an entire assessment — and achieved it in a matter of minutes through the use of a generative AI tool. And since I am the expert in the subject matter, I can assess the results that the AI is outputting to determine whether or not they're actually accurate and worthwhile.