Welcome to Episode 123 of the Think UDL podcast: AI and Ethics with James Basham. Dr. James Basham is a Professor in the Department of Special Education in the School of Education and Human Sciences at the University of Kansas in Lawrence, Kansas. He is the founder of the Universal Design for Learning Implementation and Research Network (UDL-IRN). His research is focused on the implementation of UDL, STEM education, learner-centered design, innovation, and technology in human learning. He has received and managed over $27 million in successful research and development funding. He is well-published, has given hundreds of talks, serves on various boards for journals, companies, and organizations, and is the principal investigator on various projects including CIDDL, the Center for Innovation, Design and Digital learning.
In this episode we discuss AI and UDL in higher education, and how AI relates to competency based learning and various forms of assessment. We also discuss personalized learning and the ethics of how AI impacts the teaching and learning experience in higher ed. And finally, we also discuss Jamie’s work as the founder and principal Investigator of CIDDL.
Resources
Center for Innovation, Design, and Digital Learning
Transcript
SUMMARY KEYWORDS
UDL, AI, students, learning, people, talking, higher education, conversations, personalized learning, design, competency, environments, rubric, work, support, impact, human, learner, future
SPEAKERS
James Basham, Lillian Nave
Lillian Nave 00:02
Welcome to think UDL, the universal design for learning podcast where we hear from the people who are designing and implementing strategies with learner variability in mind. I’m your host, Lillian nave. And I’m interested in not just what you’re teaching, learning, guiding and facilitating, but how you design and implement it and why it even matters. Welcome to Episode 123 of the think UDL podcast, AI and ethics with James Basham. Dr. James Basham is a professor in the department of Special Education in the School of Education and Human Sciences at the University of Kansas, in Lawrence, Kansas. He is the founder of the Universal Design for Learning, implementation and research network or UDL dash i R N. His research is focused on the implementation of UDL, STEM education, learner centered design, innovation and technology in human learning. He has received and managed over 27 million in successful research and development funding. He’s well published and has given hundreds of talks and serves on various boards for journals, companies and organizations, and is the principal investigator on various projects including Siddal, the center for innovation, design, and digital learning. In this episode, we discuss AI and UDL in higher education, and how AI relates to competency based learning, and various forms of assessment. We also discuss personalized learning and the ethics of how AI impacts the teaching and learning experience in higher ed. And finally, we also discussed Jamie’s work as the founder and principal investigator of siddell. Thank you for listening to this conversation on the think UDL podcast. Thank you to our sponsor Texthelp, a global technology company, helping people all over the world to understand and to be understood, it has led the way in creating innovative technology for the workplace and education sectors, including K 12. right through to higher education for the last three decades. Discover their impact at text dot help forward slash learn more, that’s l earn m o r e. So I’d like to welcome Dr. James Basham that I’ve always called Jamie actually, when I see you in conferences, so I want to welcome you Jaime to the think UDL podcast today.
James Basham 03:02
Well, hey, thank you for having me, Lillian. It’s, it’s great. It’s been a long time coming. I listen to so many of them in. And it’s so it’s nice to kind of hear. Yeah,
Lillian Nave 03:11
I’ve had you on my list for I will say years. And that’s my fault, because it’s actually been like four different topics I wanted to talk to you about. So finally, we’re gonna get into kind of UDL and artificial intelligence after our most recent conference where I got to see you talk. So let me start off with my first question, which is what makes you a different kind of learner?
James Basham 03:35
Well, that’s always a great question. Right? So what makes me different, I’m different in multiple ways, and I’m guessing people who know me really well and and people work for me and with me will have lots of comments. But no, so I was actually identify with learning disability dyslexia in the mid 70s. So I’m a little bit older than some, but I was kind of one of the first kids that receive special education services under what we know is today’s idea. And that continued all the way through for fourth grade, which was technically fifth grade year for me because I did first grade twice. Okay. So, and then supposedly, I was cured, we move states and I was cured. Wow,
Lillian Nave 04:29
that’s amazing that I
James Basham 04:31
was like, the only kid that they’ve ever cured with dyslexia. So So yeah, so that’s kind of my starting point. And that that, of course, is something that stays with you. Even though you’re cured, supposedly, yeah, right. But it stays with you. And then I just went through school for fourth grade on being you know, knowing I was a different kind of, you know, actually having been identified, and then that kind of content He’s on. So the way that I associate with things and the supports I use in my day to day life are things that I’ve kind of picked up throughout the years, either during my own research on it, you know, or learning through classes and stuff, but it’s, it’s, you know, so I am definitely a different kind of learner. But as we all know, we’re all different, right? So the variability of learning is there for everyone I’m very much into, you know, I’m kind of nerdy too I’m very much into, you know, understanding the learning, learning process and stem. Steam, if you will. I’m kind of geeking out on things all the time. I’m also a big historian. I love reading biographies on historical figures, and then things like that. So I’m always nerding out over something.
Lillian Nave 05:59
And insatiable curiosity, I’ve seen at least two Yes.
James Basham 06:02
Yes. Yeah. Oh, thanks.
Lillian Nave 06:04
Which shows? Yes, it does. And it Yeah, I certainly like I follow you on the publication sites, like, here’s another article by James fashion like, whoa, another one. He keeps on keeps on discovering and researching all of these incredible things. So, yeah,
James Basham 06:22
actually, there’s some new stuff that’s gonna be coming out. It’s pretty mind boggling, anyhow. With that amount of time, oh,
Lillian Nave 06:30
my gosh, it’ll be like four more episodes. I’ll have to schedule. Okay,
James Basham 06:34
that’s base design, we’ll
Lillian Nave 06:35
see. Oh, wow. Oh, yeah. See, that was like, originally in several years ago, when we’re talking about classroom spaces and all of that. Yeah. Okay. So focus, Lillian, here I go. So I was fortunate enough to know, recently, we’re at Virginia Tech. And you looked at the future of AI and UDL in higher education. And one of the points you made was based on a Pew Research Center analysis that mentioned about 20% of jobs in America, and the future near future may be replaced, or at least greatly assisted in their most important activities by artificial intelligence. And I wanted to ask you what you thought, what does that mean for us in higher education as we are preparing our students for that life beyond college?
James Basham 07:34
That’s such a great question. You know, and speaking of some of my research and work, I mean, it’s something I’ve been writing about AI and integrating AI into some of my thinking, and so my projects, really for last 10 years. And so if I remember putting out a publication, and supporting students with disabilities, and preparing them for the workforce, I think the publication came out and the chapter came out in 2019, or something like that. But within that chapter, the initial chapter of it went into the fact that, you know, when we have kind of a trans disciplinary or interdisciplinary sort of thought process, and we have aI coming together, some of the phylogenetic stuff going on and biosciences, that’s really going to transform things. And I wrote this whole big intro off. And it happened to be right around the same time that a scientist in China had genetically modified, you know, went against the global ban on this genetically modified to two babies, and so they wouldn’t catch the HIV virus. And at the time, I wrote it up, and it was in the chapter and I use it as kind of the soft opening for the chapter, if you will, like, you know, the, here’s the future in this, this is something as educators in higher education, and in K 12 education we have to start thinking about, and so went out for review. And the review came back and editor said, well, the reviewers really, really didn’t like the opening, they didn’t see how this you know, genetic modification stuff is related to the future. It’s not something you really have to worry about, you know, this sort of thing. And I just chuckled, but they said, Can you take that part out? We will read the rest of it, though. And it’s not related to learning because they’ve done it just related to HIV. And I said, Okay, well, so I did the modification as we as we all have to do in their edits and such. Yeah. And come to find out right around that same time, it kind of came out that you know, as a side effect of the genetic modifications, the kids are going to be learned faster. Right? So that’s the side effect, really. And so of course, I chuckled at that. Yeah. So I say that because this is something that’s been going on a long time, and I think, many of us, many of us, in higher ed and even k 12. And I know you’re focused on higher ed, but have been kind of overlooking this, what we initially started calling about 10 years ago, the fourth industrial revolution, and how AI was related to that. And but now we’re in the midst of it, and people are starting to say, oh, my gosh, we maybe should start paying attention to this stuff. And so what does it mean for us in higher education? For the students in life beyond college? Well, I mean, it’s, we can, I will obviously say it’s going to impact the classroom and the way that we’re preparing and educating and assessing students. And this is where things like Universal Design for Learning come into play. Because, you know, the biggest thing I’ve been talking about lately, with reporters, and such, as many of us have been, is the, oh, well, we have people cheating, because you’re using Chechi, TP or other things to write papers. And I kind of laugh at that. And I said, Well, that’s not a real biggest issue. The biggest issue actually, is much larger than using chat GTP. To write papers. This is really going to have what we have to recognize is that, while our initial concept are initial thoughts around, how do we use this AI in the world that we are in today, and with the same concepts of learning with the same concepts of work with the same concepts of what it means to be educated. If we’re trying to put it into that place, we’re kind of stopping way too short. Because just like the internet, and the World Wide Web, really transformed the way we engage with one another, enabled broadcasting, for instance, to take place between two individuals. A very little cost as compared to what it was, would have cost, you know, 2030 years ago. I mean, it is really transformed society, the web is transformed society. And I would argue that AI is going to have a greater impact on society than what the web has had, up to this point in society that we’re really looking at the AI is a basic infrastructure sort of thing that we have to be prepared to us in all aspects of our life. So what does it mean? What does it mean, for those of us in higher education as we prepare students for the future? It means that I think initially, like right now, every university, every school of education, every school within the university, should be having conversations around, not will AI impact us. But how will it impact us? And then how do we How will transform the human experience? And then what is our role? Yeah. In the future, and for some people, that won’t might be a step back, it may be a step forward, it may be a step to the side, I think we all have to come to terms with the fact that society is probably going to change. Not Probably, yes, society will change. Yeah, it always is. Yeah. Right. And it’s a continual right. But I think we have to have those sort of questions. So for instance, I’m going to School of Education and Human Sciences, in the department of special education. You know, we have been talking about this for a couple of years, but now it’s like coming out to larger and larger groups with across the school. And we’re having very deep sort of conversations. And around around this. Some of some of the conversations are, you know, over coffee and donuts, where we’re just kind of having informal conversations and getting to how are you using this in your classroom already? How are you using large language models, for instance, in your classroom, to larger conversations of, you know, what does the educated workforce need to look like in the future? What are things that we need to be doing now to prepare for that? How does this impact have, you know, the classes we’re teaching? How does it impact the way we’re assessing students, the way we’re educating students? And so these are really sort of deep conversations that every discipline and field across the university should be having. The idea that, you know, the idea that we’re that some people and, you know, I’ve colleagues have talked to around about this, that, you know, some people want to just say, Well, you know, I’m concerned about it, you know, impacting the way students are using it, too, right. And I don’t want them to do that. So I’m in my classroom. Right? Yeah, exactly. It’s kind of elaborate at this point. It’s kind of laughable at this point, because it, it really just, it can’t really be banned unless you go back completely, you know, paper and pencil sort of task. And then I would actually argue that puts in a lot of barriers. Yeah, that’s a lot of barriers, it makes something completely inaccessible. And it also doesn’t help prepare people for the future, that we’re going to be in a world where we have to live with various types of artificial intelligence, etc. Right. And so I think we have to really think about pretty broadly, the impacts it’s going to have on higher education. I think I think personally, I personally, I believe, things like the humanities, the arts, all these areas, obviously, we’re going to have continuous sort of growth and understanding within the sciences. But I do think the humanities and the arts, etc, are going to take a critical role in human society. As we started advancing the use of AI in in our everyday lives, because I think we’re gonna have some other crises that emerge with a human identity and how humans see themselves. Because we often see ourself in jobs, it’s gonna be a bank job, you know, we can go down the path, but I don’t know, how far do you want to go? Yeah.
Lillian Nave 17:10
Right. No. Well, that makes me think, first of all, really glad you said how important those humanities are going to be as a humanities person, right? My background is in art history. That, yeah, too. Even though the focus, I would say, in the last 10 years, and a lot of higher ed, and where a lot of the, honestly, the funds and the money goes to is stem, steam type of things, right. We want to have our, you know, certainly in the United States, we want to improve that, you know, I see that in our in our government funding and our national science foundation grants and things like that. But that these questions are going to emerge about well, what is the ethical use, right of AI? And, and how do our categories change? Or how, how do we understand what used to be the definition of something? And what is the definition of it now, and when you were talking about that, and really made me think of something that I learned when I was studying art history, which was really the value of art and, and the thinking about art, and what happened in the early 20th century with a movement like Dada ism, or the data movement with Marcel Duchamp, who did crazy things, like, take an already manufactured item, like a crass urinal, turn it on its side, sign it with a fake name and call it art and call it a fountain. Right? And I was so I was like, mad, actually, as a student, young student, I was like, no, no, no, no, that’s not art that you have to like, use your hands, right, you have to have a real skill, you have to write, you have to have a lot of training, you have to make it look real, you know, because I was ancient art. So everything was like Greek sculpture. And you know, like, none of this abstract stuff, I can’t handle it. But it wasn’t until a couple years later, when I was actually teaching data ism and, and like a, a course 1400 to the present, that I just really became enamored with and began to love how to shop made art available for everyone, how it’s more about the idea and how it was made. It kind of equalized in some ways the the ability to be an artist and just changed my whole perception on it. Now of course I have incredible Yeah, love for the the talent of great artists, right. That was That’s why I loved art history is like I don’t have that at all. I am not one of those artists that’s also an art historian. I just not at all, but to see how the philosophy of about art and methods and things like that made me understand this in a more complete way. And I can see that too. We’re going to have all these questions about, okay, well, if AI is encroaching, let’s say in this particular area, how much is it no longer that area? Is it no longer what we would call RT? Right? Is it no longer this or that? And we need to have those ethical conversations as well. Right.
James Basham 20:24
Yeah. I mean, I think there’s tons of conversations that we have to have. So I think there’s tons of conversations we’re gonna have to have around. What is what is humanity’s role as we move forward with this new technology? I mean, it’s like any technology, this is just a tool that, like everything else, but the impact that this tool can have, because it goes beyond what we know, is a common tool, it goes beyond, you know, hammer and screwdriver as we know it, because it’s it, or even a smartphone or any modern technology, because what it is, it’s a tool that potentially can create other tools. It’s a tool that can technically, in some form, think weather can think for itself, that’s a whole nother question. You know, so there, there’s a ton of potential for this to really be a transformative tool throughout society, and it is going to change the way we interact with one another, it’s going to change the way we, you know, conduct commerce the way we in there in, there’s so many things that impact our impact, that has the potential to impact that it is going to truly transform the human experience, both externally and internally and who we are and how we get to know ourselves. You know, what is human agency mean? What is human identity mean? All these sort of things that are somewhat predefined in societies? We currently have it, or it’s gonna change, it’s gonna change.
Lillian Nave 22:09
Yeah, there is there’s so much to that we could discuss and talk about. So I wanted to get into some specifics, I thought, because wow, I mean, we could have two or three hours on on this, and I like it. But we’ll try to stick to less than an hour. But one of the things that you brought up and I wanted to kind of go further in is that it’s talking about UDL and AI, specifically, how can they or do they inform or, and or support things like a competency competency based learning? Or specifically, like various other forms of assessment? How do you see UDL and AI working towards those, that kind of column of the UDL guidelines that assessment, action and expression and things?
James Basham 23:02
Yeah, so I think it makes complete sense. I, you know, before we got on, we were talking about the fact that, you know, the media and everyone’s kind of hot on this, I’ve been taught, yeah, there’s, I’ve had a number of interviews with reporters, and, and what the media likes to highlight is the fact that, you know, students are cheating. They’re using these large language models, to write papers and such. And it to me, again, that’s a minor sort of issue, it’s maybe a first step in consideration of how AI is going to transform learning. But what I kind of say to effect I just said earlier this week to a reporter, you know, if, if we’re only using a single form of measurement, in a classroom setting, or in a learning environment, that we’re really missing the boat anyhow. Yeah. So if an AI, if a large language model AI can come in and a student can use it to write a paper, then we’re probably not fully assessing the learning that’s taking place in the classroom, yeah. In a way that we should be. Now, there gonna be some argument that, you know, especially with doctoral students, for instance, well, they need to learn how to write articles and therefore writing is a critical function of what they’re going to do. Therefore, we have to assess it. And yeah, I get that. But, you know, they’ve been used, but we’ve been using, you know, spellcheck grammar check. more sophisticated, more sophisticated things, you know, in that nature for a while, an AI is only one step further than that. So it’s part of that process, and it has to be actually integrated into that process. So where do we where does UDL play a role in this discussion, it’s at the core of this discussion. It’s at the heart of this discussion. When we think about the way our modern learning environments should be designed, they should be designed with a focus on all learners. They should be designed with a base level support have multiple means. Now AI can play a role in that, yes, and we don’t need to just focus on action expression, obviously, we can go to engagement representation as well, however, on just the basics of what it means to provide, provide for assessment. It supports, it supports the notion of, we need to measure multiple means. And I can be a part of that. And actually, as we get into multimodal AI, which is forthcoming and is kind of going to be the new big thing here pretty soon. It even plays a role in that sort of discussion, we need to provide for multiple means. And in many ways, it overcomes this issue. Now, when we look about looking at multiple means, the first part of your question dealt with competency based learning. So if we get into the basics of what are we measuring? I think we start off with competency. We start off with competency, like what are the competencies we’re attempting to measure? And then we marry that with supporting multiple means for action and expression. It is, again, it’s at the base of how we how we do that work now. What I’m doing in my classes, for instance, is I’ve encouraged the students to use Hi, I’ve always provided for you know, I tried to walk the walk, right? So we support multiple beings of action expression and everything they do. Yeah. So you know, we’re going to you we do a weekly reflection, for instance, on the materials or modules that students had to go through go through the week before, before they came to class. And they are supporting multiple means of doing that, you know, you can do this in writing, you can do this by developing a visualization, you could do it through video, you can do it through audio, I mean, a graphic organizer, all these sorts of things come into play. And I encourage the students now their future teachers, so I’ve encouraged the students to try new things, explore. And, and then we use and use AI, if at all possible to do it. And then let us know you’re doing it. Because we want to know what you’d like we’re learners with you. We want to go through that learning process with you. And then what we’ve done is where you create competency based rubrics for measuring for measuring outcomes. And oftentimes, most 90 95% of time, we’re using the same rubric across all forms. Yeah, right of expression. So, you know, we can measure because we’re looking for the competence. And we’re looking, we’re measuring based on a competency. So that’s what’s in the rubric. Yeah, the medium in which they’re turning it in, or the medium in which they’re submitting, demonstrating their competency.
Lillian Nave 29:02
Not important, cool, or not as important. Yeah. Yeah. Cool. Right. And I found that just in the last year, a lot of my focus, when I’m talking about UDL has been so much on the designing by the instructor about really what the goal is and how to pinpoint it. And that’s like, so much work that we have to be doing and realizing, you know, all those barriers that we had been putting in when we’re like write a paper, even though you don’t care if it’s a paper, you really just want it out. Do you understand these five concepts? Can you explain them, whether it’s in a paper or not, depending, you know, on your field, that it’s that process, the design process of coming up with like, what would the rubric look like so that it would catch right all of that competency that could be shown in multiple forms. And so the rubric isn’t things like five pages is double spaced Times New Roman. That’s not the rubric. Right. The rubric is did you explain these three concepts? Did you give examples of how it is applied in the 21st? Century? Right, you know, and it could be, you’re making, you know, Leonardo, the AI, you know, visual tool, come up with a, you know, an image that explains or something like that. So, yeah, that’s matching or getting a rubric that gets to really what we want. And I think so much of my life, certainly before UDL, and understanding that was that construct irrelevance, and AI, I think is very helpful in that can help us take out that and kind of understand where that competency is like, what is it, we want to pinpoint? Let’s be specific, and then have the flexible means to get there AI can help with that.
James Basham 31:01
Right? I think it’s critical the design process. I mean, it’s something that, you know, initially, I think people when they kind of get into UDL, depending on where they’re coming from, if they come in from a design sort of field, or understanding, they bring that to bear right away, because it’s just innate into who they are. Yeah, I think for people that are coming from that sort of perspective, the the process of design, and, you know, when I teach it to undergraduate, pre service educators, we often focus on design thinking, because it’s pretty simple. And one would think like, oh, educators, they should be designers? Well, historically, they’re not trained designers. Historically, they’re trained as do these things in this environment, and kids will learn. And don’t think about that. But when you go start with a goal based design process, it makes so much sense. It makes so much sense. To end up in saying, Oh, well, you can have multiple means of action expression, because it really doesn’t matter. And, and actually one of the hardest things, though, for undergrad undergraduates, I’ve worked with every, you know, teach this class, every fall, we deep dive into this stuff with undergraduates. And they, it’s always hard, but they could because they want they think, you know, this should be measured this way. Well, why is that? Where’s the competency or the goal associated with needing to measure it that way? What’s what I was hosting with me?
Lillian Nave 32:43
Yeah.
James Basham 32:47
Judiciary’s always their model, it’s their tradition, their model that they had. And I think one of the things that AI is going to help us in doing is it kind of puts the old models aside. Because that’s an interesting sort of cow. Okay, so now let’s bring AI to the table. Should we measure learning the same way? Oh, no, we can’t do that any longer. You know, and so, so it’s always interesting, because one of the things we’ve talked about the UDL community for a long time, around, for instance, accessibility, and UDL, is it the chicken egg sort of argument, right? A Trojan horse? Is is, is is accessibility, the Trojan horse for UDL, or as UDL the Trojan horse for accessibility? You know, that’s all it’s kind of been a kind of an inside sort of conversation at the summit and other sorts of venues, you know, we end up geeking out over such conversation. I, it’s interesting to me where ai, ai plays a role in that, because everyone’s taught let’s talk about the use of AI in schools. Okay, well, again, if we don’t, if we have an environment, designed at the very foundation, at the very foundation, with all learners in mind, fundamentally designed with the focus on all learners, using things like UDL, then adding AI to its it is going to cause a huge, huge disruption. Yeah. Right. A bigger disruption than it would with AI. Yeah. already instituted.
Lillian Nave 34:25
Yeah. Like, when I think about, like, how we might grade or assess, right, this learning. It used to be a skill, I would say, like, it used to be a skill to say, alright, well, you need to write 500 words on this versus 1000 words, right? That would be something that could show your understanding of something and, and maybe, maybe show twice your understanding of it’s twice as many words maybe, but now we can easily in put something into API and say, make this 500 make this 1000 words, make this a 20 page paper make this a Elizabethton sonnet form, right, make this a poem, and I’m just talking about the language ones rather than any of the other ones. And so yeah, so it was, it just seemed like our assessment was focused on a really small area. And now we have such an almost an unlimited, just a great amount of outputs that we can look for in our students. And that we want. I mean, think of, I think of all the jobs that did not exist when I was in college, you know, social media coordinator that didn’t exist, right. All of the, the jobs that so many of our young students coming out of college are really adept at to because they’ve been, they’ve been much more in tune to more of a digital world than at least I was growing up, I’m not going to say they’re digital natives or anything, because everybody’s different. But that there’s just so much more, and we in higher ed, often lean on that tradition, we’ve already talked about that we’re very close into, well, it takes a long time to change our our ways of doing things and and how we get accredited. And you know, all of these other things, that if we’re going to add AI, like you said, it’s like, no, we kind of have to redesign, just not just saying, Okay, well, we’re gonna add AI in here. And so the first thing, as you said, people do is say, No, we’re not going to use AI, that’s, it’s gonna mess everything up. And instead of just what we’re going to add ai, ai, I think we need to break it down and redesign with that AI from the beginning, we’ve just got to include and have our students knowing how to use it, that they’re not afraid. And it’s not automatically cheating, that it’s now something because it is. It’s everywhere. I use it every day all the time. I mean,
James Basham 36:59
I think I was talking to one of my historian colleagues here. And, you know, we’re equating it to the printing press. I mean, that’s been one of the conversations, like what sort of impact is AI going to have on society and learning? Well, what sort of impacted the printing press of society and learning or written word, if you want to even go back further? Right, I think that’s where we’re at. I think, and so to think it’s gonna fundamentally, fundamentally shift the way humans learn. Yes, it will. Now, do we have to embed from the very beginning, the way we think about the learning process and the way students demonstrate their understanding? The way students engage within the environment? And yeah, we have to that should be, we all need, we need to question all that. And the reality is, is those of us who have been kind of in this UDL area for a long time, we’ve kind of thought, hey, we need to redesign education system. Yeah, you know, PK, PK, 12, and Pk, k, 21, and so on. And really, across all environments, be it higher ed, K, 12, corporate, whatever it is. And many of us have been involved in that process. We’ve kind of been thinking about this for a while. So if you haven’t started that process, haven’t started that process, then you probably should start and AI should be part of that conversation.
Lillian Nave 38:41
Yeah, that kind of leads me into the next part that you brought up, that I wanted to ask you about, well, that you brought up before, that made me say, I got to ask him this question when I interview him. And that’s about personalized learning. So which is to me not the same as the way we’ve always done it. We had a particularly static environment. So I wanted to ask you about the relationship that you see between AI and Udo, and personalized learning in higher education? And also, could you just give me in our listeners your definition of personalized learning as well?
James Basham 39:19
Yeah, I don’t have a written out front of that. So the informal sort of definition of personalized learning is, is learning a learning environment learning experience that’s designed for each individual learner, right. So in that includes taking into consideration variables, such as, obviously, engagement, obviously, the way information is being represented, obviously, the ways in which the students are demonstrating expressing their understanding. But it also can mean things like and things that we don’t often talk about in the UDL community on a date Today is things like the pacing of the instruction, right? It could mean. And so it can go further than just a normal UDL based environment and get into get into more things like the pacing of instruction. I mean, it’s an example. So the relationship among within with UDL in personalized learning has been around for a long time. And in fact, back let’s see, 1015 years ago now, the University of Kansas caste, founders a UDL. And NAS D, which is the National unfreedom Association of State special education directors had a center on online learning and students with disabilities. Within that National Center, which was supported by the Office of Special Education Programs and the US Department of Education, we had a number of projects that studied personalized learning environments within that work. Within that work, that were looking at places across the country, and spent two years pretty in depth with one location, there was a K 12 environment in that developed a competency based personalized learning environment for about 7500 students that was UDL based. But what we found out in that work, and kind of the work going on since then, is that much of the much of the the environments that we consider personalized, right, the environments that we consider to be more personalized learning environments, have UDL alignment to them. And it’s, again goes back to that same conversation we just had, which is that UDL is at the base that the very foundation of how we design effective learning environments for all students. So once you set the foundation, and it’s a stable foundation, based on you do, then we can do kind of, we can kind of do the add ons, if you will, we can personalize it. Right, or we can have a non personalized environment as well. But in these personalized environments that were really designed for each student, and so some of the variables of these environments, some of the variables or the environments is each individual student had had a personalized learning plan. Now be it that it was a K K 12 environments that we were studying, some of the students also have individualized educational programs or IPS. Right, that doesn’t exist in higher education. But right, each student had these these, you know, learning plans, and each learning plan would be a student would sit down with it with an adult, each week, roughly every week, to sit down and figure out where they were at in their learning plan. And then students took different pathways that were competency based pathways based on UDL to, to support those learning outcomes. So what does this mean in higher education? I think the what we would what personalized learning would mean for higher education is that, again, students would come in and kind of conceptualize a individualized learning plan. Now, some of those people that would come in and support the individualized learning plan would be going into fields or professions that had maybe certification to them, etc. Yeah. And so again, we’re going to be looking at more competency based sort of certifications, etc. And, and we can get into a whole bunch of conversation around what this could mean, from credentialing, micro credentialing to just competency based credentials, to various sorts of forms, that students could come to demonstrate their knowledge of demonstrate their ability to complete. And it can again, it takes away the notion in some ways, like similar to what it did in in the K 12 settings where it shifted time and place, etc. What do we do in higher education is the same. Because what you could suddenly do is you can imagine that some people, some students in your classes learn faster than others. Some learn little slower than others. But what if students weren’t made to sit through the whole thing or sit at the same pace? Yeah, how would that transformed the way we taught the way we did things. Well, conceptually, people could couldn’t say, yeah, why learn a bit a little bit slower? Or a little bit faster here? This is where I have lots of variability. And it made conceptual sense. But it didn’t make any functional sense, because we had no way to make that happen. We it was, it was nearly impossible, especially in higher education. Right, so truly personalized learning. But what if, now, Lillian, rather than just you as an individual, right, you had literally an agency that would go out and help support students.
Lillian Nave 45:43
rights work? Yeah. And
James Basham 45:45
all your students as a benefit to come into your university had access to a Lilia, it allowed Billy an agent. I know it’s a tough one, say it 10 times over.
Lillian Nave 45:57
Can’t do it.
James Basham 46:01
But they had access to an agent that was made of you and can provide them feedback and guidance and support. And we already see some of this coming out. For instance, there’s, you know, apps out there right now that him I just got a notification for one of my apps on my phone just last night, that I can now, you know, communicate with my PDFs, I can talk to them. Really? Yeah. And there’s books out there that, you know, there’s apps out there right now where you’re reading a book. And rather than asking a teacher question, you can ask the book a question about the book. And essentially, what they’ve done is they’ve, you know, use large language models to support some form of some level of artificial intelligence, you can argue as to whether how intelligent it is, but some form of artificial intelligence into these things. And therefore, you can ask questions and have dialogue with books or with PDFs. And it’s the first step towards that. Yeah, now, I can certainly talk to Lillian anytime I want to as a student. And I can kind of personalize that experience and UDL and competency based sort of pathways, make it feasible for that to take place, make it feasible for that to take place. But now we go back to the first question that we talked about, which is how, you know, how’s this column going to transform etc. This is where the humanities and the human experience matter. And because I think one of the things we can very quickly get to, or people can very easily visualize, while people are only interacting with these AIs all the time. They can do things more readily, more quickly, etc, etc. It kind of throws away the need for human interaction, well, that’s where we have to, we have to kind of put the balls down, right, we have to say, human to human interaction is going to be still important. And we have to design sort of experiences and how is it going to transform the education system? Well, we may still have this very personalized sort of experience. But I think what we have to do as folks in higher education, is really think about the ethics as you kind of brought up earlier, the the need for human interaction. We need to think about, you know, all these sorts of things. These are the bigger sort of questions we have to have. And but getting to the primary point of the question, personalized learning, competency based learning, UDL, they all go hand in hand, and then we add AI to that, to that, you know, architectural sort of underpinning, you have a lot of great potential there. And I think it makes it more feasible than it’s ever made it where we’ve used AI just slightly in the past on these some of these. Studies have used it, it’s in kind of in the plan, but I think what AI is going to do to this sort of personalized learning competency based learning, UDL sort of experience is it allows it to make it more feasible for more people. In some ways, it can make it more easier and accessible. Easier to access for more people. Yeah. Because you could in some ways provide for that. Well,
Lillian Nave 49:37
you were talking about having like Lillian agents like a little AI, right? That would be so helpful for especially, I mean, even just the one thing you brought up like pacing, the fact that most colleges have a 15 week, long semester and you’re taking four or five classes right in those 15 weeks. That’s not optimal for everybody. Anyway, Um, and I know there are some universities that go on trimesters or quarters, or, you know, or two, nine week sessions of two classes, right, or something like that. And but the thing is, everybody at that school is on whatever that schedule is, right? And it’s just the way we’ve always done it. And why do we have summers off? You know, mostly because we had farmers that would have to, you know, take time off in the summer, right. And it’s just created this a little bit arcane system, that now if we have AI, that we could, somebody could move up the pace for some things like for the knowledge acquisition, yeah, we can do that. But if somebody’s in week two, and somebody else in the same classes in week six, but we need to have a discussion in here about different perspectives from each one, that’s not necessarily going to work, because we’re in like, two different time areas of the class. So having, you know, one part of it maybe is in that pacing, and I can give, oh, you’ve already made it into this year, you can work on this for the next week. But we’re also going to come together and have this perspective sharing or whatever we need, so that we all are hearing from each other at a different time. It would just be, you know, a different design of the class rather than we’re all going at the same pace. And we all hit this thing at at the same time, and I could see how we could run things differently, you know, especially if somebody has a different background already in the material than somebody else, because they’re in a different point in the course, I mean, we could use that to our advantage, too. I could certainly see. But there
James Basham 51:42
could be agents that do that. Right. I mean, the idea you get of other agent, student agents as well. I mean, so it’s really, yeah, I mean, it goes, it goes both ways. And so there’s, I mean, it really does open up whole new sort of avenues and conversations around the education of students.
Lillian Nave 52:04
Yeah. Yeah. One of the conversations I’ve been having a lot with colleagues lately, is the idea of what is college for, like, what are we getting out of college? Or what does the student want out of college? And I think, you ask different students, you’ll get different answers, you ask different legislators, you’ll get different answers. But, but I’ve, I like the, the idea of that students are getting knowledge, right, they need to learn something, they’re also getting a credential, something they can take to an employer, I have a diploma or I have a badge, or I know how to use Excel. Or I can do statistics, right, some sort of credential that says they’re useful in some way. And then the other thing is the experience. So and, and not everybody wants the same experience. There are some who want to go away and be on a college campus and be at a big rah, rah football school, right or something. And so that could be the the overall experience, but also thinking about a classroom experience. You know, I want to be in a classroom where we’re discussing ideas and having a seminar kind of thing. Or it could also be online, like I learned much better when I can have my time to do it asynchronously, I can kind of plan my day, also a returning student, somebody who has a full time job, right, different experiences that go along with the credential, and with the knowledge that we have to get. And I can definitely see how the addition of AI into how we can design those different things is going to provide personalized learning, I’d say or help us to, to provide that for more right.
James Basham 53:51
Yeah, definitely. I mean, I definitely think it’s going to be able to enhance our ability to personalize learning process. I, you know, again, I we’ve, we have seen some success at this with in K 12, some k 12. Settings. However, there’s lots of variability, I guess. It’s probably not it’s an and how it’s designed. And it’s not always designed in the most efficient and appropriate manner. I mean, so the idea of, for instance, that in K 12 settings, I mean, what we’ve seen in some of the Personalized learning is students sitting in front of computers, yeah, all day, every day. And I would argue that that’s not actually the purpose of the reason that kids should be coming to school as they sit in front of computer right. I mean, it should be more of an interactive, again, multiple means. The ability to you know, engage to and to take out you know, take action express this with our understanding is critical the human experience as as we go forward. is going to be an important piece of the puzzle that we need to make sure we that we do not forget. And don’t forget that that piece because it’s critical that we, that humanity, as it is, kind of stays at the center of the discussion.
Lillian Nave 55:18
Yeah. Yeah, absolutely. And as we started out talking about, it’s because we value learner variability, because we value that people are different. That’s how we need to design, whatever our learning environment is. Yeah. So I’m actually going to squish down the last two questions, because I think they’re related. And we’ve sort of been dancing around them already. But in your talk that I got to see you give which I appreciate it, you ask the audience a couple questions. And I’m going to throw one of those questions back at you. That to give some more ideas, but also leads into subtle that you have at University of Kansas. So you asked how might AI impact teaching and learning experience in your specific field? And you are preparing teachers and special education? And kind of following that? Can you have created the siddell at University of Kansas, which is the center for innovation, design and digital learning? And thought maybe you could talk about how that might impact teaching and learning in your field? And what’s on the horizon for you?
James Basham 56:37
Yeah, well, thank you. Yes, siddell Center for Innovation design and digital learning. Ci ddl.org, is a federally federally funded National Technical Assistance Center, housed out of the University of Kansas in partnership with caste, and the University of Central Florida, as well as the material group. So our center is focused on really helping support the integration and use of technologies, specifically educational technology, within higher education, and special education, early childhood related service, personnel preparation. So our our primary audience in that group is, is our higher education faculty members, although we also have a large contingency of folks that follow us from the K 12 sector as well. But primarily higher education is our focus in that group. And so the big question you asked me, which is, you know, how might I impact the field, I mean, it’s something that we are dealing with every day, it’s subtle and thinking about, and we put out a number of documents on how AI is impacting and is, is and will impact the education of all learners and how it’s how it’s impacting those of us who practice in higher education in supporting pre service educators related service personnel or early childhood folks. And it even future training future faculty members, because that’s actually another group of ours that we focus on. So we’ve put some things together, so people can go to siddell cddl.org, to look at some of that, but initially and off the top of the things that we need to talk about. And we are often thinking about, I mean, like we said earlier, one of the biggest questions we get is how do we get these? How do we get to identify and and how do we get these students to stop using AI to write the papers? And we’re like, oh, that’s not our biggest problem right now. Yeah. But I think how it’s gonna affect the teaching and learning experience, specific within our field, and within special education, is that we have to prepare educators, future educators, and future leaders in the field, to understand the impact of AI within their own teaching and learning process, and then we have to have those deeper conversations around the ethics of that we have to have conversations around, you know, how to appropriately use a AI just like any other tool in their own teaching and learning process as they’re going through it as future educators, or future related service providers. Whether it’s supporting students through things like new forms of assistive technology, or using supporting better access and accessibility for students with disabilities. So in special ed, we’re having this sort of meaningful conversation where I kind of plays a role. And then and then we are kind of getting into the future sort of conversation of what are things that we need to talk about related to human interaction. One of the largest things we’re starting to see in the AI field is that humans love interacting with API’s, even from a social sort of perspective, like an agent. And we talked about agents a few minutes ago, but, you know, what’s it mean, if someone just interacts with the agent continually and doesn’t really interact with other humans? Is that a problem? Well, what’s the role of an educator in our field to help facilitate human to human contact, things like that. So we have to kind of get into these conversations with people we’re starting to, we’re starting that thought process we have right now. And in fact, for that is coming together, we have an AI blueprint that’s coming together that is going to be rolling out, I’m guessing in February, we’re kind of getting the right you know, crossing the T’s and dotting the eyes. But we have a national kind of workgroup that’s been putting together a number of this document in a number of areas, from ethics to research to teaching and learning. And that’ll be rolling out of the civil center, hopefully, again, hopefully, like I said, in February. And it’s, it’s we’re seeing it kind of as a living document where we’re trying to where we got these groups of people together from across the country, to kind of put two cents together on these things and where we’re at, in, you know, spring of 2024, knowing that it could change again in six to eight months, 10 months. Yeah. And the idea is that we hopefully be able to update that. So that’s, those are things that we’re thinking about and things that we’re shifting and thinking about for the future. But settle is a great, I think, arena and for people in Special Education and Early Childhood related services to that, but probably all, anyone from any field can also join in and come join the fun.
Lillian Nave 1:02:05
Yeah, it’s, it’s a lot of fun to think about, that’s for sure.
James Basham 1:02:09
Well, and the idea is like taking it and looking at across disciplines, right. So it’s not just taking what is going on in education. But what do we know again, about things going on me humanities, where AI researchers doing what it’s? And how’s that? What’s research telling us? It’s coming? It’s coming down the pike, and then how do we change? How do we how do we think about how does that play a role in the way we design more effective environments? Hopefully, with UDL at the center, yes, environments. At the foundation, because environments, because the human should be at the center. But but
Lillian Nave 1:02:47
Right, exactly, right. We, I mean, I think the whole thread this, the three line or plumb line of our whole conversation is that human centeredness, the human matters, that, that honoring and valuing the variability of that learner, and then creating and designing a flexible environment. And now that we have this other amazing tool, besides the knowledge about UDL, and that flexibility, having the AI to really, it seems accelerate the ability to create all those flexibilities. I mean, when I first started with UDL, the, the problem I would get when talking to people is Oh, that’s so much work. Well. Now, I could put into an AI and say, Can you UDL this assignment and, and give me five different ways that students could actually perform this. And so now the work is cut down. immeasurably to right. Yeah. So yeah, there’s so much that we can do. And I really appreciate this conversation, because you really brought in the overall ethics and the thinking and the philosophy really, that we have to be putting in the forefront before we just start, which is something I do just start oh, let’s play with this. And let’s just add it on before running back to say, how are we going to lay these foundations so James, I just want to thank you so much for your time in explaining your thinking and how long you’ve actually been doing this and, and so much that you’ve done for our UDL community. I just want to thank you so much for your time and thoughts today to be on the think UDL podcast. Well,
James Basham 1:04:33
thanks for having me. And, you know, I think it’s great podcast. I was pleased to be here and
Lillian Nave 1:04:44
you can follow the think UDL podcast on Facebook, Twitter and Instagram to find out when new episodes will be released. And also see transcripts and additional materials at the think udl.org website. Thank you again to our sponsor Texthelp Texthelp is focused on helping all people learn, understand and communicate through the use of digital education and accessibility tools. Texthelp and its people are working towards a world where difference disability and language are no longer barriers to learning and succeeding, with over 50 million users worldwide. The Texthelp suite of products includes read and write, equate to an orbit note. They work alongside existing platforms such as Microsoft Office and G Suite and enable them to be integrated quickly into any classroom or workspace with ease. Texthelp has changed the lives of millions worldwide and strives to impact the literacy and understanding of 1 billion people by 2030. Visit tech start help forward slash learn more, that’s l earn m o r e to unlock unlimited learner potential. The music on the podcast was performed by the Oddyssey quartet comprised of Rex Shepherd, David Pate, Bill Folwell and Jose Coches and I am your host, Lillian Nave. Thank you for joining us on The think UDL podcast
