The Educational Promise of Narrative-Based AI


Dr. Jeremy Roschelle, Executive Director of Learning Sciences Research at Digital Promise, joined the po dcast to discuss the next generation of artificial intelligence for educational storytelling and what they’re hoping to build with their $20 million grant from the National Science Foundation.

The technology is coming along to which an AI assistant can craft stories, can enhance stories, can customize stories. How can we use that to get back to a narrative center learning experience? You're listening to enrollment growth university from Helix Education, the best professional development podcast for higher education leaders looking to grow enrollment at their college or university. Whether you're looking for fresh enrollment growth techniques and strategies or tools and resources, you've come to the right place. Let's get into the show. Welcome back to enrollment growth university, a proud member of the connect Evu podcast network. I'm Eric Olsen with Helix Education and we're here today with Dr Jeremy Rochelle, executive director of learning sciences research at digital promise. Jeremy, welcome to the show. Thanks, hrek. It's great to be here. Really excited to have you here and talk with you today about the educational promise of narrative based Ai. But before we dig into that, can you give the listeners a little background on both digital promise and your role there? Sure thing, Eric. Digital Promise is a nonprofit organization that fundamentally connects educators, researchers and innovators to work together and we spend higher Ed ktwelve preschool, really lifelong learning within digital promise. Eric, I lead the learn earning sciences research group and our mission is to conduct fundamental research on the future of learning, but in a very applied way. We want to conduct research it's useful to educators everywhere. So excited about this conversation because I feel like AI and education gets thrown out a lot and often it doesn't really mean Ai. So maybe to kick us off today, can you give us just a high level overview of the current state? Where are we now in terms of AI in education? Eric, if I could draw a timeline, it would stretch back about fifty years. It's not new, but we're at a very exciting moment. So let me just talk for a second about that. Really, since the birth of AI in the late s early S, people have been imagining what could this mean for education, and we have had throughout the years some very successful applications, but they've been narrow. Those applications are in areas of learning that are more puzzle like or more logic like. Math is a classic example. Chess, of course, is a classic sort of example. We've all had early warning systems that many universities will be familiar with. That given early indicator when a student may need some additional attention to stay in rolled, stay engaged. Where we are now, though, is like a hockey stick turning upwards, and that's because the capabilities of ai are suddenly exploding. We have much more capable possibilities before us and we all see this every... in our lives. We're start we're talking to home assistance, we're talking to our watches. You know, we're used to things that complete our sentences, suggest people we ought to talk with, and so it's becoming commonplace. The underlying capabilities, number of patents, number of researchers, just expanding really wildly right now and within the next five years that's going to mean new types of applications, not in education, not just those narrow ones that we've seen for the past, you know, thirty or so years. Love that overview, Jeremy. Now can you give us a brief overview of this National Science Foundation Grant and the really exciting program that you're hoping to build with it right? Happy to do that. I am really excited in my colleagues are excited to kick off this Ai Institute the National Fund Science Foundation had a very competitive awards program and selected a series of partnerships to come together, and each partnership had to connect two things. On the one hand, fundamental and advances in AI itself and, on the other hand, and application area, in are case learning. So our focus was really unengaged learning. New Fundamentals are becoming possible. We wanted to take that opportunity to rethink engaged learning and the place we've chosen to start for that rethinking is to think about how stories throughout history have engaged learners, how we, for the whole history of humanity, have sat around campfires telling stories and that's been a primary modality of learning. But somewhere along the way, if learning became rigid, it lost the storytelling emphasis and it became something that is off putting, foreign alienating to too many of our students. So we want to look at the technology is coming along to which an AI assistant can craft stories, can enhance stories, can customize stories. How can we use that to get back to a narrative center of learning experience? All right, you're blowing my mind a little bit. I do want you to talk about this mental edged that I'm going to in my own head now, because do we think that learning and education evolved from storytelling toward standardized testing, not necessarily because we thought it was more interesting or better pedagogically, but just in order to scale it? has that been the forced evolution of education? In a nutshell? I agree with that. Eric. You know, standardized testing came up about a century in large part because the military needed to assign people to jobs in the military and they needed an efficient system.

So the problem was very much a scale problem that drove standardized attesting. How do we take this mass of people we're bringing into a particular occupation and assign them to the right roles? It wasn't necessarily for the betterment of their learning that the standardized assessments were developed, but once developed they were quite useful at scale, and so you could see the education system start to tilt towards being organized around those assessments. I think we've lost we know. I don't just think we know, we've lost a lot of learners by going too far down that road. And you know, no one starts out with their own child sitting on the SOFA, opening a book and saying Hey, I'd like you to take this multiple choice test. We know as parents we start with stories, but it's also true the best CEOS. I know you're laughing, but read the Harvard Business Review about cultures and huge companies the best CEOS or storytellers. Yeah, Jeremy, that's so fascinating because I think to your point in terms of the learners that this evolution of education works for isn't fully inclusive. anecdotally, we've seen that online education today seems to work best for a very, very self motivated students when they do not have that benefit of of of storytelling. Is that partially what your research is hoping to solve, for to develop adaptation specifically through storytelling, to keep more students moving and engaged in the learning process? Yeah, absolutely. You know, one of the things that's coming along on the foundation side of AI, and it's scary but it's also promising, is the ability to synthesize things synthae size, maybe the narrative for how a sports game might play out. You know, it's take a few sentences that someone started and create a complete paragraph that follows the thoughts they started and sounds vaguely like a human may have written it. You know, it assistant that can track where you're going in a more narrative sense and play along towards that. So what we're seeing in terms of student engagement is students are engaged in part when they feel they belong. That's a very powerful human thing, belonging, and stories or something that make us feel we belong or can make us feel like we don't belong if they feel like they're not welcoming our identity, our personality. For instructors trying to teach hundreds or thousands of students, they don't have the time to make slightly different, variant story experiences for all their students to be part of. But imagine in that we are recontextualizing, for example, a science lab experience to be really about trying to discover something that's that's fundamental to a problem. You know, maybe there's a...

...disease spreading. That's something we're familiar with right now and people have to address some of the scientific basis in different communities, and so that story about disease spreading. They need to vary a little bit with different groups of students to let them follow what they are really interested in while still keeping some of the curricular emphasis that is the goal of the course, and so problem based learning, work, learning in teams, learning through collaborations. There's intrinsically a sense of culture and socialization and story. It intrinsically is very motivating students to be part of that and what we're looking in at, instead of breaking that come back to a very instructor driven, one size fits all narrative, to try to keep that going a little bit longer stick with where the students want to take the learning experience. Jeremy, you mentioned being at the the beginning of this hockey stick curve that you're starting to see become more and more visible. What's the easy ask for AI? What do you think ai will be, for sure pretty great at in five, ten years, versus the much harder and long term mission you're helping to start solve for? Yeah, that's a that's a fascinating question. You know, we've seen a lot of basically machine learning type applications already and I think that'll continue. What these applications do is look for patterns or associations between two things, and so I do think one thing that's going to become a lot easier is kind of a course recommendations where you may have an AB alternative. Should I start with a discussion or should I start with the presentation? Should the discussion be like this or be like that? I think we have so much data gathering in platforms that you may see instructors get some pretty sensible recommendations from a course we're planning assistant, for example. That seems very it seems very feasible and attractable to me. I just want paint for you what the difference is between that and what we're trying to do, given this twenty million dollars, to try to do something exciting. Yeah, and really, Really Eric. The difference is pretty straightforward. Most of that kind of work is recommending between two things that pretty much already exist or are just very routine, and you're just want to know is it better to do more of a or more be, or do a first or be first? Or is a or be better for a particular student? But the a's and B's are the same things. Yeah, what we're trying to to hear is create a kind of experience, this narrative centered experience. That is very rarely done now because it's too hard to expensive. If you know to do it any kind of scale has been too hard and so the only... you see it is a massively talented faculty members who can weave their students into a into a story. But you're not every faculty member is going to have that talent, and so we're trying to break through to that. Really is an experience that cannot be created today, cannot be assigned a or B. It's just a different type of learning experience. Can You alpos picture what that looks like? I think the the sequential base testing is something that's easy for me to wrap my head around. We think that a, you know, hour and twenty long learning session with my class could covered these ten things. And what sequential order are learning outcomes maximize? We a be multivariate test and find out that one I can get my head around. What's an example of what this looks like when finished? WHAT DOES AI base storytelling look like? What what a class look like for one student versus another? Yes, Eric, I have an example. I like to use that. I think it certainly would fit high school, maybe middle school. We know already that inquiry based science is really important to translate students. Science isn't just facts, it's a process. US With a certain quality, and so I like to imagine a group of students being engaged with the basic outline that a month from now we are going on a trip to Mars together and we're going there for a scientific project where we want to collect some data on the Martian soil, and we need to plan this out. What instruments are we going to bring? Where are we going to collect our samples? How are we going to analyze them? And you know, we may have some different interests about what we want to really look at on Mars, just different science, different questions we may want to look out. But this whole course together, maybe there's a hundred students together. We're going to be in small groups. We're all going on this big ship to Mars in a month. So let's figure out what you want to do when you get there and let's spend a month of our class time learning about the fundamental physics or chemistry or whatever it is that we need to know, what the scientific instrumentation is, learning that data is, sampling plans, planning at our analysis, and then, you know, month from today mission starts. We're going to get on that rock tip. We're going to go on this of course now simulated mission to Mars and we're going to do it. We're going to collect our data, we're going to come back to class and talk about what we what we found when we got to Mars. So to me that's a kind of experience that we cannot we can see how exciting it would be. We can't produce it right now today. Would just be too expensive to pull off. Maybe in a museum you could do it today, but doing it in routine online learning to complicated. So that's the kind of thing we hope in five years we've really made some progress towards. And when? What's the difference between I want to sign up... job for that class? Sounds amazing. I want to join that class myself. What's the difference between finding that Master Storyteller instructure to develop that sequential story versus relying on Ai to help develop what that narrative actually is? Well, I think they'll be a blending of those two. I think I always really when I think about learning theory or instructions, a sign. I always want to iterate between sounds, research principles and what the bay best instructures do. And we want to be really human centered. I think the way to make this understand the feasibility of this for ai is that's the customizations, it's the variations that really will be too much for anyone structure to do or to manage. But that little bit, it's just what you and I do in conversation. We don't follow a script we made ahead of time. We listen to each other where a little responsive, we take it a little bit different direction. And today instructors, you know even tomorrow structures under the time to do all that. But I think that's what we're looking at, is within something that's based on sound wisdom from practice, practice of great instructors, based on sound learning theory. We know this is the right overall experience. How can we bring an AI'd make it feasible to to that right at scale? It's fascinating and so again trying to translate to myself, the layman, is it still helpful for me to think about it? Is there is still that sequential experimentation happening, but within a story you can't just take chapter for and put it in front of chapter one without synthesizing and creating new transitions and and is that the missing piece of being able to utilize AI within a story? Yeah, absolutely, and then also, you know, bringing it to students in experiential format that that sort of fits to for example, a voice assistant instead of a new text to read, perhaps some imagery that may weave in some of their own drawings and so forth. But contextualize that and, you know, just to make it make this feel realistic, but not just realistic, to get the learning relevant resource in the right place. So I know for me it would be very exciting if I was part of a scientific mission and I had made some plans in my notebook if now some of that's notebook pay ages were automatically coming together in an image. For me that looked like it was part of this this rocket ship that we're getting on, and I would really feel it. Sometimes these cues really que you that it's real, and it's just that feeling of it being real what a students complain about about...

...higher education that seems so detaxed from reality. So what can we do to make this feel like this is a real experience and you're learning in a real I think a little bit can go a long way. Jeremy, I'm not sure I can wait five years to see what your team builds. This is too exciting, but for those of us who have to stand on the sidelines and cheering you on. But but want to start thinking better about ai today. Any next steps? Advice for institutions who are looking to leverage where I ai U is today and and prepare for where AI is going to improve their students learning outcomes? Where should they start? Yeah, great questions. You know, there are some nice readings out there that just summarize the state of the art of where AI is. That's one thing. It's just to understand what the technologies are. Ability to do naturalistic input, like voice, like making sense of a sketch, abilities to sense patterns, abilities to synthesize constructive action or text. So, anyway, some reading about what the capabilities are. I think it's important to compliment that with some readings about human center Edai. Sometimes it's called responsible ai, sometimes called Ethical II. We have issues of bias, because there are a lot of challenges with this technology as well, and so tracking some of that, those issues and becoming aware of that is super important. Starting to think about policies and safeguards and really how they'll be informed consumers of anything that might become available and don't just take promises for granted. Going down that path a little bit more. Something I think is important is just developing some ability to look under the hood or have someone on your team who can, because there are superficial promises being made out there that something has ai and it's good, and sometimes what's in it is really trivial and the team doesn't really the team that built that thing really hasn't gone particularly deep so as it kick the tires process. So, anyway, those are the three things I'd say. You know, read about these fundamentals that are exploding and open your eyes that, think about the ethics and think about how you're going to build a team that has enough capability to really kick the tires. Jeremy, thanks so much peer time today. What's the best place for listeners to reach out of that they have any follow up questions? Yeah, I would be happy to engage listeners by writing to me at my email address. It's j Rochelle at Digital Promise Dotorg, J r Os ch Elle at digital promise that Org, and you can also pretty easily find me on linked and if that's easier for you. Jeremy, thanks so much for joining us... Best of luck to you and your team. We're all counting on you. It's been a pleasure hope to see you on our rocket ship error. Attracting today's new post traditional learners means adopting new enrollment strategies. Helix educations data driven, enterprise wide approach to enrollment growth is uniquely helping colleges and universities thrive in this new education landscape, and Helix has just published the second edition of their enrollment growth playbook with fifty percent brand new content on how institutions can solve today's most pressing enrollment growth challenges, downloaded today for free at Helix Educationcom. Playbook. You've been listening to enrollment growth university from Helix Education. To ensure that you never miss an episode, subscribe to the shown itunes or your favorite podcast player. Thank you so much for listening. Until next time,.

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