AI as Design Accelerator with Ryan Wetzel

How can generative AI help students develop creative and critical thinking skills? Doing means treating AI as more than a super Google search.

Ryan Wetzel is manager of creative learning initiatives for Teaching and Learning with Technology at Penn State. He and his team have developed a number of structured experiences for students (and their instructors) to increase their generative AI knowhow and to use AI to help them pursue course learning goals. While the students work in teams to design board games, create hit singles, or build their personal brands, they learn about AI and about creative and collaborative design.

Episode Resources

·       Ryan Wetzel on LinkedIn, https://www.linkedin.com/in/ryanlwetzel/

·       My visit to the Dreamery, https://derekbruff.kit.com/posts/learning-with-and-about-technology 

·       Intentional Teaching Ep. 21: Design Thinking and AI with Garrett Westlake, https://intentionalteaching.buzzsprout.com/2069949/episodes/13619437-design-thinking-and-ai-with-garret-westlake 

Podcast Links:

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Find me on LinkedIn and Bluesky.

See my website for my "Agile Learning" blog and information about having me speak at your campus or conference.

Transcript

Derek Bruff (00:05):
Welcome to Intentional Teaching, a podcast aimed at educators to help them develop foundational teaching skills and explore new ideas and teaching. I'm your host, Derek Bruff. I hope this podcast helps you be more intentional in how you teach and in how you develop as a teacher over time. Back in April, 2023, I had the chance to visit Pennsylvania State University to stop by Penn State's teaching and Learning with Technology group. I got a tour of the Dreamery, a flexible and innovative learning space named after Penn State's famous Creamery. The tour was led by Ryan Wetzel, manager of Creative Learning Initiatives, and I was impressed by how Ryan and his colleagues were helping faculty and students at Penn State explore emerging multimedia technologies like virtual reality and generative artificial intelligence. A lot has happened in the world of AI since then, so I thought it was time to reach back out to Ryan and see what his team has been up to.

(01:01):
I learned that among other things, they have designed a number of AI experiences for faculty to use with their students. The idea is that an instructor would bring their class to the Dreamery or one of the other TLT learning spaces and have Ryan's team walk their class through a set of activities designed to help the students and the faculty member increase their generative AI Know-how today on the podcast, I'm excited to share an interview with Ryan about these AI focused experiences and the ways they teach, not only about ai, but also about creativity and collaborative design. Ryan, thanks for being on Intentional Teaching. I'm glad to have you on the podcast and to hear about some of the things that you're doing at Penn State.

Ryan Wetzel (01:43):
Happy to be here, Derek. Thanks for inviting me.

Derek Bruff (01:46):
So I'll start with my usual question, my usual opening question. Can you tell us about a time when you realized you wanted to be an educator?

Ryan Wetzel (01:55):
That's a great question, and I think it goes all the way back to my undergraduate years as I was trying to discover for myself what I wanted to do and what I wanted to study, and I bounced around to a couple of different degrees while I was exploring what my options were, and I always came back to options that included space for me to be creative and my natural interest in technology kind of connected with that. And I spent a lot of time finding ways to be creative with technology. And what I learned through that process is that I really enjoyed helping others be creative with technology as well. What I discovered from this is that some folks don't feel like that they are creative and that their fields of study or their areas of expertise don't allow them to be creative, but by working with them and engaging with technology, I really enjoy helping them see where creativity has an impact on the work that they do or the interests that they have. This carried through my various positions at Penn State where it's always been about empowering creativity across disciplines, and that feels rewarding,

Derek Bruff (03:11):
And I got to visit the dreamery, as you call it when I was on campus last year, and you gave me a little taste of some of the ways that you collaborate with faculty around these technologies. I'd like to focus our conversation today on generative artificial intelligence, since that's an emerging technology that is taking a lot of brain power to figure out collectively, what can we do with it? What is it good for? How is it problematic? And so I'd love to hear about some of the ways that you're helping faculty approach that technology with some creativity.

Ryan Wetzel (03:50):
It's such a big question, looking at how generative AI can positively impact the education experience, and there's a lot of space for this to be a disruptor. I think that early on, and even to today, there's still a lot of focus on possible negative impacts. And while those are very real concerns and need to be addressed and explored and challenged and maybe have policies written up and guidelines, and have a focus on how we do this safely and respectfully of the work that our students and our faculty do, I think where we are focusing is assuming that there can be positive impacts and the ways that it can help faculty and students do more of what they want to do of what they're studying, and also do it in a way that, again, through this lens of empowering creativity. And so there's a real focus on tools that are text image generators that are creating video, that are allowing them to manipulate images in a way that allow them to get at the heart of the story that they want to tell better.

(05:07):
There's also an effort in positioning it as a prototyping tool to help them get at their ideas faster. Not that the generative AI is creating those ideas for them, but it's helping them process through the brainstorming process that much faster and getting an idea of the direction that they want to go in as the work that they create and to do this, there's just so much testing that has to be involved, right? We have to put ideas out there. We are all in this together. We certainly don't have the right answers, but we're very interested in exploring how to find the right answers with our faculty and students.

Derek Bruff (05:51):
I want to come back to the brainstorming question in just a minute, but can you share a concrete example of a project that you've done with an instructor to explore this space together?

Ryan Wetzel (06:03):
Sure. One way that we're helping faculty engage with generative AI and through using it as a student is by using text to image generators to help students build a brand. And this can be a personal brand, this can be a brand around a product if that's what's relevant to the course material. But the idea is that the mechanics of building the brand, these are not necessarily graphic design students, so we don't want to spend a lot of time in the graphic design space. However, the outcomes benefit from them having built this imagery and are able to arrange this content in ways that better explore their ideas. So this is where we partner with faculty to teach the students how to use text image tools and in various lightweight graphic design tools. This could be Adobe Express, this could be Canva, and then support those students in the creation of this branding identity that they create.

(07:18):
What that does is it allows them to engage in an area that many of them, again, not being graphic design students that they thought was not available to them because they didn't have those skill sets, and we can do this quickly so we don't have to spend a lot of time learning specific pieces of software. They can do this in a class period, learn how to use the text to image generation tools, and then actually build that into their project. Is any of this sort of production ready content? No, it's not. And that's not the intention. The intention is around exploring the course content in that way and feeling like they're quickly prototyping those examples of how their research and how their interests connect in this space.

Derek Bruff (08:09):
And when you say text to image generators, you're talking about things like Midjourney or ChatGPT's image generation capability or Adobe Firefly?

Ryan Wetzel (08:18):
That's correct. Mostly it's Adobe Firefly. We are an Adobe creative campus, and so we use a lot of Adobe tools in this space, especially through Adobe Express.

Derek Bruff (08:29):
Right, so that means it's already paid for essentially for the students?

Ryan Wetzel (08:34):
Yes, that's correct.

Derek Bruff (08:36):
Right. That's one barrier to access removed, which is super helpful. So there's a prototyping effect there where they're better able to have a conversation about what they're trying to convey if they've got a visual prototype that they can talk around.

Ryan Wetzel (08:53):
Absolutely, and it also goes enhancing communication skills. So a large focus of what we do is on storytelling and crafting. A narrative is not in this case about creating a fictional narrative, but it's about being able to tell the story of your research or your course content or the job that you're looking to get after you graduate from college. Being able to represent those ideas in a coherent, linear fashion, and the ways that in which they do that changes depending on the medium that they're working in. So being able to give them tools to allow them to communicate in this visual medium if they are themselves, not graphic designers, only enhances their abilities to tell their stories in a variety of different ways. I think there are endless possibilities there for how that's going to grow. And just seeing how swiftly it's changed in two years looking at generative ai, especially these creative tools for generative ai, we can do things now that we never thought would be possible just two years ago.

(10:02):
So this is moving so quickly, and I think there's some degree of empowering creativity, but also helping them process this rapid change. So working with faculty about, well, how does this impact your discipline directly? But then thinking about, okay, well, how does that change the way that we deliver these topics to students? The way that they engage with that material, those way we do that isn't immediately obvious. We have to iterate on this and continue to work within this space and find lots of partners from across a lot of different disciplines to see what those effects are.

Derek Bruff (10:41):
Yeah, and I do feel like some faculty took a look at ChatGPT in early 2023, and it didn't do anything interesting from their perspective, and so they've kind of dismissed the category of technology, perhaps not realizing how much the technology has changed over the last couple of years.

Ryan Wetzel (11:02):
I think that's very true, and I think a first impression for those that were paying attention at that time, and even sort of our first instinct speaking broadly of students and faculty and staff and anybody that may engage with this technology, our context for typing text into a window and receiving information back to us is probably Google using search engines of various kinds to find information. And I think where we're sort of stuck, and we're still making inroads on helping people think beyond this into the next step, is that we're stuck on thinking that ChatGPT and similar generative AI tools are just advanced Google searches. And that's a very limiting way to consider these tools and a lot of the new learning experiences that we're designing which work in any discipline, these learning experiences have the objective of pushing students that are experiencing this past, considering this as an advanced Google search, that it can do so much more and that they will be more capable if they explore those opportunities.

Derek Bruff (12:20):
And I would argue that up until recently, it was not a search tool. It fundamentally did not provide answers to your questions. It strung together words in creative ways maybe, but until the chatbots were linked with actual search functionality so they can go out online and find stuff, they weren't there to deliver answers. They were there to, I think, to be kind of creative partners. Actually, if I can be so bold.

Ryan Wetzel (12:53):
No, I think you can be that bold. I think that is a great way to look at it and a great way to frame it. And I think so helping them move past that kind of framing of, I'm used to typing ideas into Google and finding things and saying, well, this really isn't that becoming more so as you say, but that it really is kind of intelligent, but it's a way to synthesize ideas quickly that we haven't had in the past that unlocks different use cases for them of how to use it. And so this goes into some of the learning experiences that we've created about trying to position tools like chat GPT as a collaborator, as a creative partner in a process about thinking about it as a design accelerator. So moving these ideas quickly through the brainstorming process, and we're still learning from this as well. I think part of the fun of this is setting up this framing what feels like a bold idea of you're a team of four humans and one AI now create.

Derek Bruff (14:03):
Yeah,

Ryan Wetzel (14:05):
There's a certain boldness to that and a challenge that we don't exactly know how that's going to work out, but it is the direction that it's heading, so we should have experience in this space and build that understanding together.

Derek Bruff (14:19):
So yeah, can you share some examples of that? What does that look like so far in your learning experiences?

Ryan Wetzel (14:26):
Yeah, no, this has been so much fun to explore. First off. So we are currently exploring this idea of generative AI as a collaborator through a learning experience that we call can AI play. And it positions this experience as creating a board game. And this was created in over the last year and delivered for the first time in March, 2024 to a faculty development event that we call Make It. And it's all about bringing emerging technology to faculty to invite them to explore with us through these very uniquely designed learning experiences that give them hands-on access to the technology, but also creates pathways to explore how this could be used in the classroom. We try to design these learning experiences to be discipline agnostic so that it can fit in lots of different areas. So that gives you context for why we decided to teach people how to build board games.

(15:32):
It's not because we have a robust board game academic discipline here at Penn State, although that would be fun. The idea is that it gives something that is immediately recognizable. Most people have experiences with board games. Many of us have fond memories, childhood memories of playing board games. And so this is a useful visual context to explore these ideas. And so we divide everybody up into groups of four humans, and each human has a defined role. This role is important scaffolding to make sure that everybody knows where they're supposed to contribute to the overall process, but by also assigning roles. We're also carving out a space where AI can exist. And so ai, it can be ChatGPT, can be Microsoft copilot, whatever your generative AI tool of choice is, serves in the fifth role as the design accelerator. And you go through an entire brainstorming and prototyping process where you're working out what your idea might be for the board game, and you're encouraged during that brainstorming phase to make sure that everything is being typed into ChatGPT, you're keeping ChatGPT aware of the conversation. In fact, that's one human's primary role is what we call the AI whisperer. It's the person that's focused on making sure that AI has all of the information and is contributing back. So they speak for the AI in that case,

Derek Bruff (17:21):
Because one thing about generative AI is the more context you give it, the more useful its output is going to be.

Ryan Wetzel (17:28):
That's absolutely correct. As the participants enjoy going through this learning experience, they can get very excited about the brainstorming process. These are fun ideas. And so it is a constant reminder to say, okay, what does AI think about this? Part of the way that we encourage this is that the deliverable is a polished rule book that's in a shareable document. And so you can't create that at the very limited amount of time we give you to accomplish this goal. So you must be using ChatGPT to continuously update this rule book. And often where participants start is they'll be encouraged to think of two very different childhood board games that they enjoyed, and then ask the AI to mash them up and create a rule book that takes the best of both board games. And that's a starting point. They customize further by maybe incorporating ideas from their discipline or their research or a hobby that they're interested in to build that out. We provide to them a writeable surface so they can erase it and iterate, iterate on the design of their board game. We provide a lot of board game pieces so that they have dice, spinners, counters of various sorts, pretend money, everything you would expect from a board game so that they can design around that and actually have the physical pieces to prototype with.

(19:01):
And by the end, they switch, they get up and they move to somebody else's table, and they play that game and provide feedback on the various design elements, how well they've incorporated generative AI into the process, reflect on their own process as a way of thinking about, okay, if we were to do further iterations, and depending on time, sometimes there's time for two, three iterations on this to continue to interface with AI and say, okay, based on the feedback we got, here's where players get stuck. Can you help us generate solutions about how to modify the rules to make sure they don't get stuck in these ways? And by the end of it, it's a really engaging session. Everybody's having a lot of fun. Yes, they've created a prototype of a board game, but they've also now learned how to interact with generative AI in ways that are not just an advanced Google search.

(19:56):
They're asking for its opinion on should it be a or should it be B? Right, in terms of the kinds of choices that they need to make to design the rule set. And it's a skillset that's transferable. So yes, this was a board game for this particular learning experience, but take this back to your office, to your classroom and replace board game with any number of design choices, right? Creating an informational brochure on a topic, creating the outline for a video or a podcast that you want to create. There's many options that can replace the board game in this particular learning experience. And this is popular. There's been many disciplines that have been utilizing this learning experience just over the course of this semester.

Derek Bruff (20:49):
So just structurally, just to make sure I'm following, so you did this in a faculty development context, so a workshop that faculty were invited to so they could experience this process as participants, and then they're able to call upon your group to bring it into their own classroom and adapt it to whatever they're teaching. And you're saying several folks have done that since then?

Ryan Wetzel (21:12):
Yes, that's exactly right. So we tested the learning experience with them in March. We based on their feedback and how it went, we took the summer to develop it into a course sized learning experience, and now we offer it through our Dreamery location that faculty can actually bring their classroom to us, bring their class to us during a class period and have their students go through this experience. And there have been several classes this semester that have already made use of this spanning several different disciplines from within our College of Liberal Arts to the College of Science and the College of Earth and Mineral Science.

Derek Bruff (22:00):
I'm curious, did they take the board game option or do they pick a product that's different and maybe more aligned with their discipline?

Ryan Wetzel (22:11):
It's always the board game option.

Derek Bruff (22:13):
They go for the board game. I am curious about kind of the brainstorming piece. And so I think I saw this on Bluesky this morning actually, which was someone arguing that if I'm going to write an essay, and they were thinking about the pure writing context, not multimedia. If I'm going to write an essay, I can have ChatGPT brainstorm some stuff for me or write a first draft. But that beginning part is hard for a lot of people, but also super useful in helping them find their own ideas. And so how would you respond to someone who's worried about this kind of learning experience where the AI is doing the hard part for students when the students need to be doing that hard part, they need to be coming up with the ideas or doing the evaluation?

Ryan Wetzel (23:06):
That's a great question. I think to some of it, it depends on the individual learner and where they need the most support at the time. We're certainly not advocating for, I'm certainly not advocating for generative AI to do that work for them, especially if that's the point of the assignment. I think it depends on what the specific learning objectives are and what they're supposed to get out of it. This is where maybe we get into some of the discussion around AI literacy and also guidelines about how to use AI appropriately. And that may change depending on the focus of the assignment or the focus of the objective. And I think depending on how you prompt generative ai, how you engage with it in a conversation about brainstorming is important and relevant here. If your question is, I need to write a paper on X topic, give me three main points for this topic, that's probably not making the best use of it.

(24:18):
Yes, you're going to get information back, but it's doing a lot of that heavy lifting for you. But if instead you're asking it, I need to do a paper on X topic and here are the three areas of focus that I want to have, could you help me come up with examples of how to make a compelling argument around this? Then it's giving you options and you're still making decisions about which options to pursue, cleaning up that language, writing it entirely brand new in your own voice, and probably doing further research because as we discussed, it's not always the best research partner, but it can at least get you started. It maybe get you over the points where people often get stuck during the brainstorming process. So it's definitely not something that can exist in a vacuum. I think it needs guidelines put around it. It needs best practices to be identified,

Derek Bruff (25:17):
And I really liked your framing of it is it's giving you choices, right? You don't have to accept those choices. I've talked to faculty who they're developing a rubric for an assignment and they go back and forth with ai and could they make the rubric on their own? Yes. Could they just have ChatGPT produce a rubric that would be serviceable? Yes. The faculty member I'm thinking of said the final rubric was stronger because it had a lot of her ideas and a few options from ChatGPT that enhanced her ideas. And so she ended up with a higher quality product at the end of it, in part because she knew her own process and she knew where she could get input and help there.

Ryan Wetzel (25:59):
And I really think that that's in the short to medium term where we will see the most practical use of generative AI in this space because I use it much in the same way where I'll type out my initial ideas of whatever the project might be and then essentially run it through kind of a generative AI filter. I'll say, clean this up or edit for brevity. Let's try to distill down these ideas a little bit and then give me three ideas around trying to create a conclusion from these statements or something like that. And then you iterate on those ideas and it just helps refine my thinking because everything I've given it is from me, and then I am just spending time making that product better. So I completely agree with using it as an editor, essentially. It's an editor that will always respond to you as quickly as you want it to.

Derek Bruff (26:57):
Yeah. Can you say a little bit more about the idea of the AI as a fifth group member? Have you, so I've been intrigued by this, at least one platform I know of that kind of bills itself as Slack with chat GPT.

(27:13):
So you would have a, because most of the AI tools out there are meant to be used by an individual user, and they can go back and forth with the chat bot, this product called Boodlebox. I don't know if you've tried it, and I haven't played with it much, but it's a kind of collaborative discussion space, so you can have multiple humans discussing and also a chat bot that's in that space. And I feel like that's a kind of funda, fundamentally different way to interact with ai, but I don't know any of the implications of that. I haven't been able to see that. And I'm wondering, as you look at the group dynamics in these learning experiences, are you starting to observe different relationships with the ai?

Ryan Wetzel (27:54):
I think when positioning it as a fifth group member, what we're doing is we're trying to help the participants think of it as more than just a tool. So at sort of its most basic level is that let's not frame this as a tool. Let's frame this as somebody else sitting next to you. And we've even kind of jokingly said, well, what if we set up a table with five seats but only ever put four people in it, and then you would address your question to AI in that empty seat? And I think this will get better as the voice technology for generative AI gets better. I think chat, GPT is certainly getting better in that context, but in sort of the context of the group projects, it's not quite there yet. And I think to your point, I have not used that product either, but I'm very curious now to follow up on it, and I think it does change the dynamic because it looks different when it's responding to different voices, I would imagine. And it's not voices as in sort of vocalizing, but different voices in terms of different ways to articulate thoughts and different ways to organize information. And so what does that look like when it's synthesizing maybe four different voices at the same time and providing answers back? That would be fascinating to look at in more depth.

Derek Bruff (29:23):
Yeah. One, someone mentioned this, I forget where, but the idea would be to have each group member draft something independently, give those drafts to the AI and ask the AI to synthesize in some fashion. And so that's something that I've seen in design thinking spaces where there's a lot of independent ideation, and then there's a kind of convergence phase where you try to put those ideas together. And so I can imagine a human doing that, but I can also imagine an AI filling that kind of synthesis role, and that seems very different than what I usually see in terms of uses of chat GPT and copilot.

Ryan Wetzel (30:06):
I would agree with that, and I think that synthesis role is kind of the next way that we're thinking about positioning this for students is getting really comfortable with those synthesis options and using that in their toolkit, and we will see what comes next. I don't think it stops there, but I think that's currently where we're sitting in terms of the landscape of incorporating this broadly across disciplines.

Derek Bruff (30:35):
Okay. So do you have another learning experience that your team is cooking up?

Ryan Wetzel (30:40):
We do. We have one new learning experience that's still very early stages for this. We call this the AI Artist lab, and this actually comes out of an area that we're building called the AI Arcade, and the idea is we wanted to create a space where we could get lots of feedback from our faculty and students on the kinds of AI tools that they want to use that are not your chat, GBT and your Microsoft copilot that help them create multimedia artifacts, but we know a couple of things. We know that these tools come and go very quickly as this is a very fast moving space, and we know that so many of them are based on subscription models, and so that can be a detriment for asking students to participate and use them for any sort of class assignments. So what we're doing is we're setting up the I arcade, which spotlights different applications maybe over the course of a month, and invites students and faculty to come in and use them and provide feedback and tell us where any of these tools are relevant to their discipline or relevant to the work that they're doing.

(31:54):
And we keep an eye on this, and we are the facilitators essentially of their access to these tools and the learning experience component of the a i arcade is called the AI Artist Lab, and this is where they need to create across several multimedia tools. In this case, they're creating, because the creation of music is so much fun right now, they're creating a hit single based on any sort of content they want. Usually it's class related, it has something to do with their course content, and then you extend it from there. What is a marketing campaign for that hit single look like? Right

Derek Bruff (32:32):
Hit single about Latin American politics?

Ryan Wetzel (32:34):
Sure, yeah.

Derek Bruff (32:35):
The Cambrian era?

Ryan Wetzel (32:37):
Yeah, that's right. That's right. Any and all of those things and mash them together if you want to.

(32:44):
And so when you can create any of those artifacts quickly, then you're exploring this course content from different ways, and then you're creating an album cover to go with it. You're creating what do the tour t-shirts look like, but you're not wasting time. It can feel like, well, that feels sort of frivolous, but when you can do that in minutes, you're measuring that in minutes and not hours, then you're getting to the discussion portion of, okay, where can we go with this? What can we do with this? How does that help you re-envision your course content and your connection to it and helps the students be creative in different ways for that, where they could just write another reflection paper, but this is just another form of reflection.

Derek Bruff (33:30):
I love it. I love it, and I love that you've called it an arcade, that it's that playful attitude. It moves us away from the AI as answer bot and into the AI as a creative tool of some sort.

Ryan Wetzel (33:43):
Exactly. And where we can pull on these metaphors that we all have some amount of connection to. Maybe I'm dating myself a little bit by relying on arcades, but I think to your point that it's recognized as a fun place where experimentation can happen and where technology happens. It's a blending of where technology and creativity come together, and so if that can be a common reference point for somebody to say, okay, I know what happens at Arcade, so this is probably what happens at an AI arcade, and then we cater to those expectations and they can just that much more quickly get into that technology and explore it in a way that's meaningful for them. I think that's just a useful metaphor to use, and we do that in a lot of our different learning experiences and the way that we position our learning spaces.

Derek Bruff (34:42):
Yeah, back in my old podcast leading lines, it was all about educational technology. The current podcast is a little broader in scope, but we would generally end by asking our guests, what would you want to see from educational technology in higher ed in say, five years from now? Five years seems like a long time to predict generative ai, but if you could call some shots now, what would you want this space to look like three to five years from now?

Ryan Wetzel (35:11):
I think one area that I want to see develop more is this idea of generative AI as personal tutor for students, and I think this gets into, at least with what the tools that we have now, building some competency around creating custom gpt and really focusing on the kinds of training material that it can draw from so that you have less of a risk of hallucinations and incorrect information getting in there, but you're still taking advantage of everything. We just spent this podcast talking about using AI as a collaborator and a creative partner, but using just the material that's relevant to the course content or to the student, and what does that look like for a student that enters into college and has this personal tutor from the beginning, and it has their course content and it understands how they learn and where they get stuck and how that information needs to be presented. I think there's a lot of opportunity there that then is about helping them tackle bigger problems because they have this tool that's customized to their learning. I think that's an area that we're going to move into pretty quickly, and maybe even in three years, we see an entire onboarding process for you to have this personal tutor with you helping you solve those problems.

Derek Bruff (36:39):
Wow. So I've learned a little bit about the current versions of those, which tend to be kind of a course specific learning assistant of some sort where you train it on course materials, but I hadn't thought about a companion for your entire educational experience that would be with you from course to course and into co-curricular activities as well. That does feel like a little sci-fi, but again, given where we've been in the last two years, who knows, right?

Ryan Wetzel (37:09):
I think we have to consider all possibilities and just be open to where that may take us, and also be willing to reinterpret how we teach, what does education look like, and how we make sure that we're still providing that value to our students to enhance the way that they engage with the world. I think the scope is that big for this, and it's exciting to be a part of it.

Derek Bruff (37:36):
Yeah. Well, that's a great place to end it, Ryan, thank you so much for coming on the podcast and giving us a little glimpse into your creative place base right now. Yeah, thanks for being here.

Ryan Wetzel (37:46):
Thank you so much, Derek. It was a pleasure.

Derek Bruff (37:51):
That was Ryan Wetzel, manager of Creative Learning Technologies for teaching and Learning with technology at Penn State. Thanks to Ryan for taking the time to come on the podcast and letting us know what creative work he and his team have been doing lately. I'm going to keep thinking about the roles that generative AI might serve in group projects. What if a student group gave their AI assistant a particular cognitive move to make, like playing devil's advocate or drawing creative connections from the current work to other realms, or maybe students generate ideas in response to some question and categorize those ideas into four or five buckets, and then ask the AI to come up with extra ideas that don't fit in those buckets. If you've been experimenting with AI in student groups along these lines, I would love to hear about it. Also, I want to point out Ryan's comment about AI serving as an editor, presenting you with options to choose from as you develop your ideas.

(38:42):
On the next episode of Intentional Teaching, I have a guest who is an actual book editor who has a lot to say about using AI in this way. Stay tuned. Intentional Teaching is sponsored by UPCEA, the Online and Professional Education Association. In the show notes, you'll find a link to the UPCEA website where you can find out about their research, networking opportunities and professional development offerings. This episode of Intentional Teaching was produced and edited by me, Derek Bruff. See the show notes for links to my website, the Intentional Teaching Newsletter, and my Patreon, where you can help support the show for just a few bucks a month. If you found this or any episode of Intentional Teaching useful, would you consider sharing it with a colleague? That would mean a lot. As always, thanks for listening.