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The Inclusive Education Series: On instructional Design with James Basham · DiveIn: Diving into Special Education's Most Complex and Pressing Debates

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From the Division of Research of the Council for Exceptional Children.
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This is Dive in, the podcast where we ask difficult
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questions about the education of students with disabilities and occasionally we
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pretend we have the answers. I'm your host, Federico Vitolo,
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professor at the University of Illinois, Chicago. So, are you ready?
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Let's dive in.
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Welcome, welcome, welcome, welcome to another episode of Dive In.
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Well, we are back. In our last episode,
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we took a short trip to Washington, D.C. where I made Kuna
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Tavalin wrestle with basically every federal special education policy
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nightmare I could think of. Ossors moving to HHS
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idea, lack of oversight, lack of funding,
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autism policy, school vouchers. Who's actually in charge of what?
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I'm happy to report that Kuna is doing fine,
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at least when she's away. What happens during sleep, I can't tell you due
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to Fairpan legislation. But after our brief detour
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from Washington, we are returning to our Inclusive
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Education series. If you have been following the series, we have already had some
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fascinating and very different conversations. We begin with David
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Connor talking about inclusive education through disability studies and disability
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rights. Then Doug Fuchs challenged some of
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the arguments of for full inclusion and pushed us to think about evidence intensive instruction
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and the question of where and how students with disabilities should be taught.
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Ainsco took us around the world, reminding us that inclusion is not simply a destination,
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but an outgoing process of identifying and removing barriers to
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participation and learning. And most recently, Valentina Migliarini
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taught us an intersectional perspective, prompting us to
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think about disability alongside with race, migration, language, society, class and
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other forms of difference. So we have spent quite a bit of time
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asking big questions like what is inclusive education? Why does it matter
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where students should learn, what counts as evidence? What needs to
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change in education systems today? We're going to
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do something slightly different. We gonna get our hands dirty.
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I know you've been waiting for this. Maybe you've been looking for an
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excuse to finally try a mud sculpture. Maybe the oil in your car had
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needed changing since the 1990s when you decided to skip to listen
2:26
to the Backstreet Boys. I think for what? I've seen the stats of who
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is listening to my show and the demographics of my audience. I think you get
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the reference. Or maybe you've been thinking, today's the day
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I'm finally going to unclog the toilet myself. I tried to do that once
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while watching a movie at the same time. It did not go particularly
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well. But we're going to leave that story right there. Some stories do not belong
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to a podcast about Special education Today we move from some
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of the more conceptual and philosophical debates about inclusive education to
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a very practical question. If we want inclusive
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classrooms, how do we actually design inclusive instruction for them?
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How do we redesign learning environments from the beginning
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that anticipate that students are going to be different?
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Different backgrounds, different strengths, different ways of engaging,
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different ways of accessing information, different ways demonstrating
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what they know? In other words, instead of designing instruction for some
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imaginary average students and then scrambling afterwards when
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actual humans show up, so can we design for
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variability from the beginning? To help us wrestle with that question, my guest
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today is James or Jamie Basham. Jamie is a professor in the Department of
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Special Education at the University of Kansas, and his scholarship has focused extensively
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on universal design for learning, instructional design and technology,
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learner centered design, innovation, and the design of learning
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environments that work for a wide range of learners.
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And this is where our conversation gets practical. Because universal
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design for learning is a term that many education have here before.
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It appears in professional development, it appears in teacher preparation
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programs, it appears in policy documents, it appears on PowerPoint slides with
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very attractive diagrams. But putting three colorful boxes on a PowerPoint presentation
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does not actually make instruction universally designed. Unfortunately, I checked.
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I won't tell you what happened. So in this episode, Jamie and I wrestle with
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that and actually what it means to design instruction universally.
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What does it mean to begin with learner variability rather than treat variability
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as the problem that appears later? What does instructional design
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have to do with inclusion? And perhaps most importantly, how do we move from
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saying yes, yes, udl, multiple means of everything, I got it. To actually
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designing learning experiences in which a wide range of students can participate
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in learn and succeed. Because ultimately, if inclusive
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education is going to be more than an aspiration, a policy statement, or a very
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beautiful poster hanging in a school hallway, something has
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to happen when the classroom door closes and teaching begins.
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That is where today conversation take us. So roll up your sleeves,
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put on some clothes you don't mind getting dirty. Actually, I know you've been
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waiting for an opportunity to wear those coveralls your in laws gave you for last
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Christmas. You know the ones you open the box, hold them up, and immediately produce
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that very special reserve from gifts from your in laws. Oh wow,
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coveralls. These are so cool. While thinking when exactly I ever going to
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wear this? Well, today is the day, my friend,
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that lie becomes reality. Go and get those coveralls.
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Cut the tags off. Because today we're getting our hands dirty with universal design
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for learning and instructional design. Again, metaphorically, there will be no
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Mud. No mud at all. And for everybody's sakes, no clock toilet.
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Are you ready? Let's dive into my conversation with Jamie
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Basham. Well, thank you so
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much, Jamie, for being with us. In. Dive in. Yeah. Well,
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thanks for having me. I think it's exciting. As I was telling you
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when I got the invitation, it's a podcast I've been kind of keeping an eye
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on and listening to. So it's been great being asked to be here.
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Hey, so you're that one listener that Spotify is telling me that we have.
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That it's from cancer. That's great that we have a
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day identifier. I thought it was my mom, but no, it's you.
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Anyway, so we've been having this series on inclusive education. I really
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wanted to have you on the show because you have done a lot of work
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on instructional design, on technology, and how to bring UDL
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to inclusive environments. So I really want to hear his perspective, you know, and I've
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been starting with this question pretty much with all interviewees
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about what is inclusive education? Because I felt sometimes we're
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having debate about inclusive education, and I'm not sure we're talking about
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the same things. So the first question that I have to you is,
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how do you define inclusive education and what does
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it mean for practice? Meaning when do you see something and you say,
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okay, that's inclusive education. You know,
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I think this is a topic, obviously, right, for the time,
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unfortunately, we're still having this conversation in education, not even
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special education. When I think about inclusive education, I think about,
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you know, educational environment and education system that's
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designed to meet the needs of all learners, that provides learning
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environments, learning experiences that are meaningful and beneficial and
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equitable, let's say that word, right, for all individuals.
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So that ensures, like, belonging, participation, equitable access.
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Obviously, some sort of collaborative practice, probably.
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And we'll talk about probably as we get into this, into the
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podcast here, some of the paradoxes with the special education system
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and probably universal design for learning, right? So that we have a
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proactive, proactively designed environment that is thinking about the variability
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that exists within all humans and supporting
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that variability as much as we can. From the onset,
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you mentioned udl, and it has become such
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a big word around the globe. I've been doing work internationally.
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I know it's even written some Spanish legislation.
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There are people writing about udl,
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putting it in policies pretty much around the world.
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At the same time, it's being criticized
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for the lack of empirical support. It's like this buzzword
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that Become very popular. But they're critiquists, but it has very empirical support.
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How do you make sense of this? Do you agree with these criticisms?
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Well, you know, that's a kind of an interesting question.
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And I don't know if you, Elisa Lowery and I just wrote a piece that
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came out recently in Journal of Special Education Technology which,
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you know, if we look at the history of udl, it kind of emerged
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from that journal, right? It really emerged from that journal. And so in that piece
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we kind of got into kind of the history of UDL and
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why it emerged and why we both actually as young scholars
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back in the day kind of came to UDL and then also
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kind of how it emerged through time and where it is heading.
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And one of the critiques we raised that critique in there,
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that udl, by and large, it's difficult to
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conduct research on. Right. So the field as we've, in this sort
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of functionalist sort of paradigm, if we're going to get into paradigms and such,
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which, you know, I think we're all multi paradigmatic in some ways,
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but, but if we're going to look at the micro objective
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sort of perspective of doing research, it's really hard to do research on something
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like udl. Because what UDL kind of, kind of puts forth
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is the notion that if we look at the designed environment itself
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and we think about it proactively, is it actually meeting
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the needs of the diversity of learners, the variability of learners that are in it?
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And we've known for a long time that, that it's
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not. And so I think what UDL kind of promotes is
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that we need to think more holistically around
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the idea of how do we design environments designed for
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all learners? And it's hard to do research on that. It's like
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hard to do. It's the same thing. And I know our field generally has
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ties to the medical model. We can critique, we're going to maybe critique that later,
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but, but the, the, the medical model has
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the same issue, right? It's hard to do preventative care and show that preventative care
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is actually, you know, supporting something that's not broken.
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So we have that same sort of issue in udl.
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That being said, I think there is a need for rigorous
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research to take place within udl, that we need ways to identify whether
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UDL is being implemented in our environment. How do we actually go forth
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and measure it? And a lot of my work has been like how do we
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measure UDL in environments? And how do we support then
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the Notion that, you know, that just simply putting
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a. It used to be simply putting, you know, 20 years ago,
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simply putting a digital whiteboard in an environment,
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someone would say, well, that's udl. Not really, that's not udl.
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But when we think about the diversity of learners and we go forth and
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deploy it across environments and the other
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thing that makes UDL hard to measure is that environmental notion
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of it that the districts, if we look at
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school districts and educational organizations that have gone forth
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to integrate UDL into the way they practice,
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at the core of how they practice, it impacts more than just
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students with disabilities. It impacts all learners. Right. It impacts
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people, all aspects of the curricula and
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all aspects of the environment. So suddenly we don't have siloed sort of systems,
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special education, general education, that aren't talking to one another,
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they're actually talking to one another. And then people are also having discussions
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with the bus garage because we know there's some sort
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of exclusionary practice that's probably happening with the way we do busing. And so we
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think about how do we design systems that are meaningful and beneficial for
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all learners. And again, it's really hard to do research on a systems
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level sort of thing that's not just a quote unquote evidence based practice
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or a system of practices. Yeah. And I imagine even like trying to sit in
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the classroom. Like, I mean probably all our audience will know UDL
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has like three different principles. Multi moment of representation,
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action and expression and engagement. But then we have all these different,
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you know, sub guidelines, checkpoints, how they call it.
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Right. And it's like, what about if your teacher is doing. You observe the
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teacher has like 50% of those checkpoints. Do you code that?
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Is it doing udl? It's not doing udl. I mean, what percentage of those checkpoints
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you need to be seen to say, okay, we are actually measuring udl.
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Yeah. And that's something that so years ago.
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So if people don't know my history in this area,
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you know, as an Assistant Professor 20 years ago, I think thereabouts,
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you know, my dean came to me in the spring of
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my first year and said, hey, look, we got that grant award
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to help transform some schools that are not doing so well.
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And so you're going to lead this project in the summer if you want to
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keep your job to go through. And it was the
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first school under NCLB shutdown that I helped lead
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that project. And the idea was, is we were going to go through and transform
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the school, shut down the school, reopen the school to be a UDL based
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STEM school. And, and we saw drastic
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change to the environment as a whole very early on. And there's, I have publications
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on that back, you know, 2008 to 2010,
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2012, somewhere in there. So we saw drastic
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change in that environment early on. So we were seeing transform,
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transformative shifts not only to the environment, but to the way the neighborhood was
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interacting with the school, parents that were participating.
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Part of the idea of that school was that it became a community based environment.
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So we were working with the kids obviously through
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the week and then on Saturdays we were working on digital literacy for
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the neighborhood and opening like how, you know, working with the neighborhood
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in that area. So, so, but what was interesting
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is, and we made Safe harbor first year, all that kind of stuff. But what
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was interesting about our outside evaluator came in and said, so it's
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a UDL based STEM school. I understand STEM because I can kind of see they're
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doing project based learning, they're doing all these sort of STEM related activities.
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But, but how do I know UDL's taking place,
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you know, and so forth from that point forward. And that was
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2007, 2008, somewhere in there I
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kind of took on the notion of how do we measure udl? And it's
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a very difficult sort of thing to go through and measure.
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And actually a colleague of mine, Jim Gardner, who's since retired
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from the University of Oklahoma, he and I kind of took on this task back
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in the early days to say, well, yeah, Is it that 85% of
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the teachers are talking about UDL? Is it actually UDL? Is there a
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way to go forth and measure? And the idea is that
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you're going to have greater aspects of UDL alignment throughout the
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system. So just like we have variability of learners
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and we kind of acknowledge that now we have variability within a school, within an
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education system of alignment to udl. And so from
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there, without getting into
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too long of a story, but we, I helped co founded the UDL Implementation
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of Research Network, which was a global nonprofit. Yeah, it was a global
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nonprofit to kind of bring researchers and practitioners and education
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leaders together to talk about these very issues.
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And so for the, for from about
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2010 to 2019, we're, we were, we had the largest gathering in UDL
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across the globe every year, the UDL Iron Summit.
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And a big aspect of that was research. Like how do we
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do research in this area? And the idea is you could do research on smaller
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projects of implementation. And we have people
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like Kavita Rowe and others that we had on a research committee that would develop
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guidelines for measurement. And we've had
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other tools. I had a tool that came out in 2020 with Jim
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Gardner and Sean Smith on measuring this.
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So there are ways to go forth and measure it.
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But the critique stands. And I think the critique exists because
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we just need to have, There does need to be, regardless of,
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regardless of the promise of udl. And we know that
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the variables associated with the udl, with udl,
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provide for meaningful learning. I mean, we can, we can map those back.
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I mean, you can map em back to various types of research.
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But when we look at what are the impacts of
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bringing these things together and how are they supporting meaningful
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and beneficial learning for all students? For all students.
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That's a, that's a question that has to be asked. And,
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and, and so it's an important question. And I know we don't
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have too much time, otherwise I'd get in deeper on it. No, no, no,
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but it's valid, you know, and in, in a, in a sense
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we can say the critique, it's valid, but the critique
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that you really also have empirical support at the same time,
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it's also, I think, as a justification to completely
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disengage from it. Yeah, I think that's the wrong.
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That's the concern I have. Right. I think it's pretty easy
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for, from a functionalist sort of perspective to say,
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oh, well, we can't measure this one specific practice
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and therefore, because it's not one specific practice,
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let's run from it or let's pretend that we don't need to talk about it.
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The idea that we, we, we as I think all researchers
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would agree that, that,
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that, that the variability of human, human variability is
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driven by the interaction between a
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designed environment or any environment and
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the human themself. Right. So the idea that,
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and we have plenty of research to support that, but I also think it's just
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a little bit of common sense and so
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to just kind of throw out the design environment as a whole and say,
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well, it's not important how we proactively design environments.
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It's just crazy to even think about that because the
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designed environment is at the core of how we operate. So for instance,
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I was working with a group during COVID and we were working in
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developing countries and this is when USAID had
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funding. And one of the things that we're working on
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is within design environments across the globe,
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they don't have things like ada. Right. Ada.
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As Americans, we kind of look at that. We Say, well, yeah, of course physical
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environments are going to be accessible. Yeah. And we can debate
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whether they're accessible enough in fact. Right. We have these debates,
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but in other parts, how much is reinforced. Yeah.
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And the rest of the globe that's not the case. And so when UNESCO
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and other entities implement and have taken UDL
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under their wing as a foundational sort of framework for thinking about design,
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which is incredibly important,
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some of the aspects that we were dealing with in these developing countries were
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just the opposite of some of the stuff we're dealing with now in our country,
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which is in that country. We were talking to families and individuals
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that were saying, I have access to the materials,
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I have digital access to the materials. And so we've
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accomplished that part of it. What I don't have access to is the physical
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environment. And so, and so again that
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variability outcomes, outcomes for all humans
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are driven by the environments they interact with.
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Right. And so what we knew at that point was
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that that was a larger conversation. So these individuals
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that happened, the one, one family we're working with
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had had a, some, some kids that were blind. They could, they could
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interact with the environment digitally, but they couldn't interact with, they couldn't get to
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the environment physically. And so they couldn't have that sort of collaboration,
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they couldn't have that growth and development that takes
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place in, in that sort of sphere. So, so what UDL
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and the reason we shouldn't as a, as a, and I'm going to say a
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field of special education, but education as a whole needs to embrace something
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like UDL is because what it is saying is that we need to
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look at the designed environment and UDL for the people that are
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kind of like throwing rocks at it. By the way, takes into
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account that yes, we have some practices that are evidence based or
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even high leverage practices that need to actually be used in these environments.
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It is actually calling for the use
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of what we know is proven through science to be effective in
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teaching and learning. I have a follow up with you
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because it feels very well to what I was about to ask you.
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Some scholars would argue that UDL can reduce the need for special education.
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Well, I'd argue that no, no way.
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Specialized instruction will remain essential for some students.
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How do you see the relationship between UDL and
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specialized instruction? Maybe even separate classroom?
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You know, I was talking to a FUSA who was talking about, yeah, maybe we
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can transform the classroom. That would be basically a sort
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of like Tier 1 RTI or MTSs, you know, but there is always students that
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are not going to respond to that. You always need that specialized, more intensive
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instructor at a different level, maybe at a different setting. How do you, how do
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you make sense of that relationship? Udl, Specialized intensive Special education instruction.
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You know, I think about my late colleague Tom Skurdick quite a bit.
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Oh, yeah, these kind of conversations kind of come up. And some
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of his early work and his work throughout his life and his career
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dealing with things like the paradox of the special education system.
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The idea that we as a. As special educators,
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as a special education system, our system was born.
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Was born due to the fact that we were excluded.
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That kids were being excluded. Yeah, that kids were not being included
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in the conversation or in the system's design.
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Right. So that we had individuals being excluded. So that the,
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the very idea that, that, that.
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The very idea that we're having a conversation
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about reducing the need for special education, that actually
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should be the goal. Right? The goal should actually be that
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if we had an education system that was actually designed for all learners,
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for all people from the very beginning, it was meeting the personalized,
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individualized needs of all learners,
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there wouldn't be need for special education. So I
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think that is actually should be the goal and the dream. Now, I know
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people will scream at that and say, well, you work in a department of special
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education. That's true. But yeah,
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yeah, we do. And this podcast is about special education. But,
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you know, I recall my days. I recall
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my days at my undergraduate at Eastern Illinois University under
24:36
direction of Kathleen Shank and some of the leaders at that great teacher
24:40
preparation institution. The goal very
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early on said, look, if we can meet the needs of all learners,
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that your goal as a special education teacher should be to get the kids.
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At that point where I talk about least restrictive environment, we still do in law,
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that your goal should get the kids to be able to support
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the kids in a general education setting and should be to support kids
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to not have the needs. And so UDL kind of lays into that
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and says, yes, let's proactively think about.
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And UDL coming about in the late,
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what, early 2000s. But really the late
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1999, 1990s is
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really when it started to come forth, was like we could proactively design
25:29
environments to better meet the needs of all learners. So what does it mean in
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today's time, the relationship between UDL and special education?
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UDL is about educating all kids. Special education
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should be about educating all kids. Yeah.
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We as a US System, categorize them based on
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the categories, put forth an idea. We all know that IDEA
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does not cover the variability of all human variability.
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We know that if we look at the dsm, in fact, there's many more
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sort of, you know, labels and things that we can categorize kids
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that, that aren't dealt with in under
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idea. Should we exclude kids based on
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the fact that one, they're not, they don't meet a quote unquote label
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within idea? No, we should not. We should develop an
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environment that designs for all kids and UDL gets us towards that.
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Now, are there specific needs that a UDL
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environment may not support?
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And that's a big question around how do we measure udl?
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It kind of gets into what is udl? And I think this
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is like we go back and, you know, I remember Dave Eddyburn and Joy Zabala
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kind of arguing this at a CEC conference. But will there be need for
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specific instruction and for instance, assistive technology for.
26:56
Yeah, there's going to be need some kids. Now, I would argue
27:00
though, that it shouldn't stop at the labels that we've
27:03
given kids with disabilities. Yeah, I would argue that we need to support all learners
27:07
and we need to work towards a more personalized environment that's
27:11
personalized for every single kid. And again, I've done research in this area
27:16
of a publication, I think 2016, 2017, where we looked
27:20
at systems that were personalizing for each and every individual kid. Some kids also had
27:24
IEPs, but every kid had a personalized
27:28
learning plan. And I think if we look at, you know,
27:32
what we produce in those environments and as we get into artificial
27:36
intelligence and talk about those, the role of technology and what we're facing as we
27:40
look at the future, I think that's what we're aiming for. And so we need
27:44
to go back to some of Tom's work, Tom Skurdick's work and others and say
27:47
what if at the very beginning of time, then we
27:51
designed the education system we didn't segregate and we
27:56
didn't exclude. What if we had a system that was actually designed
28:01
for all kids at the ad hoc, racy sort of perspective? Like, what if we
28:05
took that notion and said we have a very fluid, sort of flexible system that's
28:09
designed for all kids from the very beginning? And I think that's the conversation we
28:13
need to have. The idea that,
28:17
that we, that that there, there should be a line between the two is kind
28:21
of crazy. Yeah, well, I mean, I always, always teach my future
28:25
special ed teachers in our special ed program that idea
28:30
or special education, if you want to treat them as Equal,
28:33
it was a solution to exclusion, like you say, but it was a very particular
28:37
solution to that. It was, we're excluding all these kids.
28:41
We're going to create this different system that's going to help to include. Right.
28:44
To not exclude and provide services rather than dealing with the
28:48
place that was excluding them in the first place. Right, yeah. And we
28:53
have, I would say, remain completely attached to the general education classroom.
28:57
I don't think our general education classrooms looks dramatically
29:01
different as they look in the 1970s. Maybe with some use
29:04
of technology, maybe you refute me on this, but maybe using some fast technology or
29:09
something else. But in general, our classrooms may look very
29:13
similar to what it looked 1970. So we haven't dealt with that. So it would
29:17
be interesting to see how special education actually can become part of
29:20
a movement that actually can transform the general education classroom. Other schools
29:25
have absolutely no hope on it. And that's kind of one of the henchmen getting
29:28
from people that are not very pro inclusion in the sense that there
29:33
is no way the general education classroom can do this. That's kind of the
29:37
mood. It's like they have seen for decades. They're right in the sense that they
29:41
have seen for decades of the general education classroom failing students with disabilities,
29:44
and they have no hope that that's going to change. Well, and the
29:49
concern with that is, and we've built the system, I mean,
29:53
again, citing some of Skerrik's work,
29:56
we have built institutions on the fact that there
30:01
is a difference between general education and special education.
30:04
We have developed certification structures and licensure structures
30:09
on those differences. Right. And so if
30:13
we prepare general educators to not support meaningful
30:18
and beneficial learning for all students from the very beginning, and we
30:22
say to special educators, hey, only worry about these categories
30:26
and kids on IEPs, not even
30:30
504 plans for the most part, then if that's
30:34
the system we have built and that's the system we reinforce, then yes, we're continuing
30:38
to reinforce a broken system from the very beginning.
30:41
Now, if we say to all educators, all educators,
30:46
human variability, human variability as a
30:50
whole is part of the human experience and
30:54
the designed environment and the design curricula and the
30:58
experiences within that environment directly relate to the
31:03
outcomes of what we're seeing in the environment.
31:08
And you as a educator should be trained
31:13
more as, rather than a fact, a line based factory worker where go do
31:17
these 12 things, or go do these 20 things, or go do these 30 things
31:20
and you're going to see meaningful benefit and outcomes. What if
31:24
we designed. What if we prepared educators as designers.
31:28
What if we prepared educators to look at the environment, look at the
31:32
design variables going on within their environment to say,
31:36
oh, the kids didn't do that well, the students didn't do that well last week
31:39
on that unit, or at least, you know, some portion of them, or I've
31:43
had X portion of people out last week due to illness or
31:47
you know, all these different. Or I have X number of multilingual
31:52
learners or I have, we can go into the different variables or I
31:56
have students with X disabilities. Right. But we're
32:01
really looking at what types of variability we're dealing with. Then we
32:05
can then if we teach them to think more like designers and design better
32:10
environments from the very beginning, no matter who they are as
32:14
educators, I think we're going to have better outcomes. Right. And it's going to.
32:17
And it's going to provide a system that's not as exclusionary and segregated.
32:22
Yeah, yeah. So do you see possible to
32:26
embed this kind of specialized intensive instruction,
32:31
you know, what scholars call evidence based practice,
32:34
that being tested as an intervention within a UDL framework?
32:38
I have seen very little of that. Are they totally incompatible?
32:43
Can that be part of UDL idea of providing multiple
32:48
means of support for some students to embed those intensive interventions
32:52
within the design of instruction? Yeah,
32:55
I think it can. But again the question,
32:59
if we're looking at location, if we're looking at, we're defining inclusion
33:04
just purely in like one classroom, you know,
33:08
I think it becomes a hard sort of thing, right. If we're design, if inclusion
33:13
is just one classroom at 20, you know, full time,
33:16
then it may becomes a more difficult sort of thing. But are there ways to
33:20
do co teaching, Are there ways to do like look,
33:24
we have this, we are the fourth grade pod, for instance,
33:28
you know, we have fourth grade classes and there's a POD that's sort of interactive
33:32
and there's lots of more dynamic sort of system that's kind of going on again
33:37
and it's not. And again, I want to not put forth the notion that kids
33:42
with disabilities are being pulled out to get specialized
33:46
instruction. Can specialized instruction be provided in a general.
33:51
Yes, it can be provided in general education classroom.
33:55
And can it be provided with various groups of
33:59
students also in the POD that can interconnects. Right.
34:02
And that we have this very fluid sort of thing. You know, if we look
34:06
at I think I 2016, one of the pieces on personalized
34:10
learning, if we look at in Journal of Special Education Technology, again,
34:13
if we look at that. So this, this school system that
34:17
I was working in, Skip Stahl, myself and others were working in at
34:22
that point in time they were redefining like so they were,
34:26
you know, under, under about
34:30
to be shut down through NCLB and others. And so they rewent
34:34
and revision this whole school system. And the idea being that, that what
34:39
they put forth was that if we personalize learning for each and every kid,
34:43
and some kids had IEPs, but all kids had personalized learning
34:47
plans and that we put forth the notion with all of our educators that human
34:52
variability is part of the human experience. It's interesting to
34:56
see what happens because when they put that forth to not only the teachers,
35:00
the teachers carry that forward to the students and you'd walk into
35:03
a classroom in one of these environments and there were like
35:07
this, the school system had, you know, specific schools we were working with had
35:11
7,000 school, 7,000 or so kids.
35:14
And from, from first grade, what we would consider first
35:18
graders on up because they didn't have grade, they didn't
35:23
have grade levels as we particularly called them. They would kind of put,
35:27
you know, five year olds with five year olds and such, but each
35:32
kid would say, this kid's at this area and this kid's
35:36
functioning, doing this and I'm doing this and he's doing that and she's doing that,
35:40
et cetera, or they're doing this and that's okay because we're all
35:45
different. And a first grader would say that to you what we would consider as
35:48
a first grader. And you get to high school when the same conversation would happen,
35:51
like kids were working with one another cooperatively,
35:54
collaboratively on project based learning experiences and they
35:59
were all contributing in different ways, just like we as adults do in projects.
36:02
Right. And that variability was built into how they thought about each
36:07
other as students. And to me that's part of designing that inclusive
36:11
environment. To me it's part of like ensuring that we as
36:15
a whole are doing that. But the teachers have to be educated to do that.
36:18
And that's kind of part of that process. And teachers would then
36:22
take in, oh, I need to provide more intensive instruction to these kids or
36:26
this kid or whatever to support growth.
36:30
And it's just part of how we design. But it's, it's, we have to
36:33
support educators as designers. Yeah, absolutely.
36:38
The training piece, the professional learning piece, the teacher
36:42
learning piece. This is essential. So I want to talk a little bit about AI
36:46
too, because I know you've been doing a lot of work with that. But before
36:48
that, before we move into that, I Want to
36:52
talk about the UDI gallons 3.0?
36:56
Yeah, I know you have your critiques on it. I mean, full disclosure, I was
37:00
on the board that helped to develop the guidelines. So what
37:06
is your take on the new guidelines? You know,
37:10
so it's interesting. So for people that are not
37:13
inside the UDL world, you probably don't know the role of the guidelines. The guidelines
37:17
are a document. They're generally relegated
37:22
to one page now. But the initial guidelines were kind of a larger document
37:27
that talked about the types of variability that may exist in an environment.
37:30
They were mapped back to research that's
37:35
been going on for decades in the field of education and learning sciences and even
37:38
neuroscience. And the idea was that as
37:44
an educator that was implementing UDL or system that was implementing udl,
37:48
you would look at the guidelines to kind of identify. Help identify
37:52
variability and help identify learning barriers within the. Within the.
37:56
Within the classroom or within the learning environment or even system
38:01
as a whole. So it could be an LEA or even a local education agency
38:05
or even a state education agency. And I've actually worked with, you know,
38:09
national governments and such ministries of education that
38:13
were doing the same thing. So. So the guidelines.
38:18
My belief is the guidelines should always be updated,
38:21
that we should always be like, we should have a
38:26
group of researchers from across the globe that
38:31
are following a process, a rigorous process for continually
38:35
updating and supporting understanding for the things that need to be built into
38:39
the guidelines. The. And the most recent
38:43
update of guidelines. And I know you were on the.
38:46
On the group. I was at that point. And to be full disclosure.
38:50
So the nonprofit that. That I started went through M
38:54
and A, so went through merger and acquisition and became part of
38:58
cast in 2019. And from 2019 through
39:02
2023ish. I think I'd have to look at the dates.
39:06
CAST bought out half my time from the University of Kansas. So I
39:10
was on the leadership team and helped lead CAST during that period, which if
39:14
most people recall that period, obviously Covid was a large part of the conversation
39:18
during that time. And at that point, I did end up
39:22
stepping away from casting and coming back to KU full time around
39:26
2023 for various reasons. But one of the reasons was
39:30
the undertaking of the way the guidelines were being updated.
39:35
And it wasn't. I think the work going on
39:39
was important. Right. The idea that we were updating the guidelines and I think
39:42
the group that was doing it was important to bring together. I think
39:46
the process for updating. We. I think. I think it wasn't
39:50
taking. Taking place in such a It wasn't taking place in a rigorous sort
39:54
of format. And I think there needed to be a lot and I thought there
39:57
needed to be a larger, more inclusive group that was globally
40:02
inclusive of researchers from across the globe that
40:06
were doing this work. And I was advocating, and I had been advocating with
40:10
cast for you know, the last 10 to 12 years that,
40:14
that, that they undertake an ongoing sort of mission to
40:18
update the guidelines that was, that was taking into consideration
40:22
kind of what we're, what we know about human variability and, and the, and its
40:26
associated process with learning. And then
40:30
so I do think does 3.0.
40:33
So where I'm at with it is I think 3.0 was
40:38
of its time and my concern with it is it became
40:42
somewhat political in notion of the things that were kind of going
40:46
on. And I think it was a critical conversation that
40:50
needed to take place. I don't necessarily believe
40:54
that the 3.0 guidelines necessarily support
40:59
more measurable outcomes associated with UDL.
41:03
I, but I think it talks to some
41:08
parts of the population, globally in fact, that see it now as
41:13
more inclusive. For sure, I definitely think that.
41:16
But I don't think it maps back to what we know is scientific
41:21
in, in its underpinnings.
41:24
And, and, and I think that's a,
41:27
I think that's, there's a number of reasons as to why that is,
41:31
to, to why that exists the way it is. But I,
41:35
but the way I kind of talk about it now as I give talks,
41:39
et cetera, is that you can look at guidelines 2
41:44
point, what are we, 2.2 or something like that, the last, the Last one before
41:47
3.0 or you can look at guidelines 3.0.
41:51
Whatever gets you to the table is important. Let's have the
41:55
conversation of the variability that exists within the environment we
41:59
know as a UDL community. And Elisa Lowry and I, again we wrote
42:02
about this most recently in a piece in journal Special Education
42:06
Technology. We also have a handbook
42:10
that came out by Edward Elgar Publishing that
42:14
talks not only about the future of UDL
42:18
and kind of gets into a little bit of the discussion of the
42:22
guidelines, also gets into the critique of research.
42:25
So if people are looking for the Handbook of Universal Design
42:29
for Learning, Research and Practice, Elgar Handbooks
42:32
and Education, I think you can find it there. But we get into
42:37
this very notion of what needs to take place with the guidelines on a
42:40
continual basis and they need to be continually updated and there needs to almost be
42:44
like a, a UDL Congress, if you will, or some sort of mechanism that
42:50
globally looks at these issues around this piece.
42:55
The critique I have of them is when the group kind of came together to
42:59
update them, which you were part of the critique internal.
43:03
And what we knew was that while UDL wasn't meeting the needs of all students
43:06
in for instance, Baltimore County. And my
43:10
question internal to cast was, well, how do we know UDL is being implemented?
43:15
You know, how do we know it's udl? How do we know UDL is being
43:18
implemented? Because if we can't measure it, if we can't say, yes, 80% of
43:23
the classrooms are showing UDL integration
43:27
demonstrating, then you can't blame it on udl. And this goes back to
43:31
the question around science and the rigor of what
43:35
we're actually doing here. If we can't measure it, then you can't
43:39
say that UDL's not, is to blame for not meeting the needs of
43:43
all learners. And that was my critique. And, and, and it
43:47
still is my critique that if, if we know UDL wasn't
43:51
being, if we know that if UDL wasn't
43:55
meeting the quote unquote needs of all learners, do we know UDL was being implemented?
43:59
And that's, that's the very essence of, of the question.
44:03
Now again, we knew the guidelines needed
44:06
to be updated and the guidelines need to be updated continually,
44:10
but that's a hard undertaking to, you know, and I think
44:14
it relates this. And the guidelines should actually be related to not only what
44:18
we know is evidentiary research in practice,
44:23
but there needs to be basic research. I mean, UDL deals with basic
44:27
research and that needs to be at the driving force of some of this.
44:30
And unfortunately there's not a lot of funding for that sort of work to go
44:33
on, especially at the global level. And that's, and that's what's stopping it,
44:37
I think. And I think CAST is in a tough way to try and figure
44:40
out how to do that at a global level. Yeah, let me push a little
44:44
bit back because I think some of the points that we brought are,
44:48
had a, had a research base. All the idea of like language, culture and
44:52
identity as mediators for learning. I mean, that's been research on the learning sciences
44:56
for decades now. You know, that who a student is who comes
45:00
to the classroom, their identity mediates and regulates the ways that engage with
45:04
instruction to encompass that within that wide race on diversity.
45:08
I thought it was important the language part. And looking at issues
45:12
of bias too, from teachers in terms of
45:17
teachers trying to inspect their own bias towards certain race,
45:21
class, disability, language, et cetera, be able to be acknowledged
45:26
at the time to instructional sign. I think those are
45:30
research supported notions.
45:33
Yeah, I would agree. I agree with, I agree with the notion that there are
45:37
some research supported notions in there. I'm not disagreeing with that.
45:40
And you hit on quite a few of them.
45:45
The issue is, to me was at
45:49
the time, it still is. One is,
45:52
was why it came forth the way it did.
45:55
It was, you know, and again, I bring up Baltimore county because that's
46:00
kind of what was highlighted as a primary. But again, do we know UDL was
46:04
being implemented? Yes. Having learners, you know, how they're identifying
46:08
with the environment is critically important. Having, having teachers identify the
46:13
biases they bring to the table is critically important. That is all. Yeah,
46:17
that's all well and good. The, the idea, like what, what does,
46:20
what do the guidelines serve? And so like
46:24
what I was talking, even back in the day, what I was saying to the
46:28
team was, look, some of the things you're talking about are
46:32
actually more implementation sort of issues, not necessarily guideline issues.
46:36
Right. And so maybe we need a different thing
46:39
that's separate from the guidelines that talks about that implementation. And since,
46:44
you know, in that process we had developed and we were working towards. There are
46:48
now and CAST has them because my nonprofit started them
46:52
in concert with cast, which is what are the things people need to know to
46:55
implement udl. And there are actually now holistic sort of
46:59
environmental measures that move towards what does UDL look like?
47:03
And at that point in time we were looking at, and I know they've stepped
47:06
away from it now, but being able to move towards a certified environment.
47:10
Right. So that you have a bronze, silver, gold sort of environment of
47:14
udl. And there, and there have been, there's,
47:17
there was about a decade of work that went into nearly a decade of work
47:20
that went into that. And so CAST has those things now that, that can get
47:24
in and it does get into exactly what you're talking about. So. Yeah, I agree,
47:28
I agree. Well, I want to move you to another hot topic around, you know,
47:32
inclusive education. And I think there's going to be very impactful.
47:36
It's been already very impactful with visual AI and you've
47:40
been working with this, you've been doing, starting some work, dude. What do you see
47:44
the opportunities of AI to create inclusive classrooms? Where do you
47:48
see the dangers? So, yeah, and this is probably a whole
47:52
series within itself. Yeah.
47:56
You know, UDL is critically important to this conversation as well as we'll
48:00
talk about, I'm sure. But you know, my work,
48:03
I think my first publication on cognitive prosthetics was
48:07
in 2007, 2008, somewhere in there. And at
48:12
that point in time, we didn't use the word AI because editors would just throw
48:15
it out and say it doesn't exist. But AI has
48:19
been around since the 1950s. My work as a grad
48:24
student at the University of Illinois, we had some work on machine learning and even
48:28
early forms of AI back then, I think
48:32
AI is. Without trying to overhype it or
48:36
sensationalize it, is going to be one of the biggest issues humanity is dealing
48:40
with from here forward for at least the next 10 to 15 years,
48:44
you know, and beyond, I think,
48:47
as a field, and not even
48:51
special education, as educators, I think, and researchers in this area.
48:55
If you're not talking about AI, you're not looking
48:59
at the future. And you need to. I mean, there's a
49:03
book, like, a pretty general book on it, like the Coming Wave by
49:09
Solomon, will kind of talk to you about some of the implications of this.
49:13
I wrote an article, a book chapter on the fourth industrial revolution.
49:18
I think I wrote it in 2017, thereabouts. I think
49:21
it came out maybe 2019, maybe 2020 somewhere there. And within
49:26
that I had written how at
49:31
that point in time, there were some. There was a Chinese. There was
49:35
a Chinese geneticist who had used CRISPR to genetically
49:39
modify some twins, some. Some. Some babies, and he
49:43
genetically modified them to not have hiv.
49:47
And I had written this in the intro to the book
49:51
chapter. And I said, this is the future. This is what we're dealing with.
49:54
And this is related to the Fourth Industrial Revolution and artificial intelligence and what
49:58
we're seeing. And the editor got back to me and said, this has nothing to
50:02
do with education. This has nothing to do with. And I
50:06
was floored. I was like, oh, my God. This has everything to do
50:10
with education. And it is directly related
50:14
to AI, by the way, as an outcome of those
50:18
babies being modified. A side effect of the babies not being able to
50:22
catch HIV meant that they were able to learn faster and
50:26
retain information more. So I think what we're dealing
50:30
with. And so this is all interlinked to AI. When most people think about AI,
50:34
they think about ChatGPT, they think about Gemini,
50:39
or if they're really into it, maybe they think about something like Claude.
50:44
But AI as a whole is a pretty broad range
50:48
of technology systems.
50:51
And at the center for Innovation, Design and Digital Learning, which I lead,
50:55
which is Funded by the US Department of Education, CIDDLE CIDDDL.org
51:00
we look at the as AI as the simulation
51:04
of human Intelligence by machines. And the reality is we've all been using
51:07
it for decades. It's built in. If you woke up today and looked into your
51:11
phone and it opened up, you're using AI. So it's
51:15
integrated into many of the products and product systems we're using today. It's been in
51:19
the piece that I wrote, the pieces that I did, the research I did on
51:22
personalized lear. We use machine based algorithms, learning algorithms
51:26
to support personalized learning in those environments. This is
51:29
the. When we think about inclusion, when we think
51:33
about exclusion, when we think about designing environments
51:37
for learning in the future, we have to have a conversation around AI. This is
51:41
the largest thing that we are going to be dealing with as humans for
51:45
decades to come. And it's happened rapidly. You know,
51:49
so when most people think like, you know, when most people think
51:53
that, you know, November 30,
51:56
2022 started the AI revolution with the release of,
52:00
you know, OpenAI's chat GPT 3.5. It was 3.5,
52:04
it wasn't 1.0. Yeah, you know,
52:07
you're, this has been going on for a while and
52:11
you know, you just have to spend a little bit of time in the,
52:14
in the field of AI to understand the implications of this,
52:18
that we've created a technology and it's been the goal since the 1950s
52:22
by the way, that is agentic in nature, that has
52:28
some autonomous sort of capabilities and
52:31
can operate in various sort of forms.
52:35
And so from producing so large language models in
52:39
the way that it has consumed and can produce language,
52:43
it's using predictive algorithms to do it. It's mathematics, but it runs,
52:48
it runs in the same way, the neural networks are running the
52:52
same way we think the human brain works because we don't quite know how the
52:54
human brain works. So it's using this business, doing this at massive scale.
52:59
So I think when we think about accessible environments,
53:04
when we think about inclusion, AI is the core of how
53:08
we have to, at the core of this conversation. And there's
53:13
just tons of conversation going on around, around the ethics of this.
53:17
What are the guidelines around implementation? You know, from talking,
53:21
you know, and we spent a lot of our time talking, I spent a lot
53:23
of my time talking to, you know, state, state boards of education and task
53:27
force across the globe on this very issue. Yeah,
53:31
and it seems it's a very controversial debate in the sense like there are
53:35
partners that do not want anything to do with AI at early ages.
53:39
So first grade there's been just a big movement I know in LA county you
53:44
know, Miami's also going pretty forward with pretty aggressive AI agenda.
53:48
LA caught it, Parents were opposed to it. So there is,
53:53
there is not a consensus that this needs to be in the classroom.
53:56
But one. Go ahead. No,
54:00
yeah, keep going, because I'm there with you. Yeah,
54:03
no, and I think at some point, you know, we're going to have to.
54:06
I don't know what's the age when it's appropriate. But there are some dangers.
54:10
Right. Because if students are using bots all the time to do
54:14
tasks, they're never going to learn to do tasks. Right. It's like, to me,
54:18
it's similar to when calculators came about. We did have calculators, but they didn't allow
54:23
me to have a calculator until my sixth, seventh grade, until I really knew how
54:26
to multiply, add and subtract. And there are some things with AI
54:30
that I'm assuming they're going to be similar. It's like critical
54:33
thinking, analyzing, synthesizing. You got to learn to do it then. Then, okay,
54:37
you can use the machine. Yeah. So this. So first of all,
54:41
there's not. AI in itself
54:45
is a huge controversy, right. Outside of, even outside of education.
54:49
I think that there are huge implications to
54:53
the way we educate students. So I have a DOC student,
54:58
Yaron Song, and I just published a piece on cognitive law floating
55:02
in the age of Artificial Intelligence in ldq.
55:05
So if people are looking for conversation around this,
55:08
it drastically changes the way we have to educate kids.
55:13
So if we get into. And I know this isn't a podcast on AI,
55:17
but if we get into containment is an issue.
55:21
So there's never been a technology that's
55:25
one had as much growth and adoption across the globe
55:29
by humans in, across,
55:32
across the ages of humanity as AI.
55:36
So AI has been adopted and it shows immense
55:40
amount of growth. And again, this was, if you go back to the fourth industrial
55:44
revolution stuff that came out in 2015, 2016, this was
55:48
all predicted, by the way. It's not like it wasn't like, this is new.
55:51
Like I wrote about this back then. So.
55:55
So these are huge, huge issues.
55:59
And we need to develop a technologically literate society.
56:02
And we haven't done a real good job at that. Information literacy, digital literacy,
56:07
AI literacy, they all intermingle. And part of the reason that we're in
56:11
the spot we're in right now, politically and within the discussions
56:15
we're having now is because we didn't do our due diligence when we were calling
56:19
for it 20 years ago. And we need to do a lot of due diligence.
56:23
Now, AI, the issue that we have with AI, one of the issues is
56:27
that regardless of what we do in our schools, regardless of whether
56:32
we're educating people to be literate in this area or not, AI is
56:36
going to be part of society, part of the workforce going forward.
56:40
And what people aren't understanding about the
56:44
growth of AI and the development of AI, it's happening at an
56:48
exponential level. So we're seeing these AI models double in
56:53
size and somewhat in ability, depending on how you measure it,
56:58
every four to seven months. Yeah, it's rapid.
57:02
It's happening in a way that humans just can't fathom.
57:05
And so this is a huge conversation that needs to take place. And again,
57:10
I was just, actually just this week talking to Trey Vasquez
57:14
and I were talking to a local task force on this very issue.
57:18
And the. You're right, the task force is split on. Yeah,
57:22
AI needs to be embedded in everything, and AI doesn't belong in our schools.
57:26
The problem is, is we spend a lot of time teaching people
57:30
and I'm going to hold up a pen right now. Right. We spend a lot
57:33
of time teaching people how to use a pen or a pencil. Right. And how
57:36
to use it appropriately. From here's how you hold it to here's the type,
57:39
here's what writing looks like, too. Here's how you take effective notes.
57:43
And we spend no time. And I'm holding up my iPhone. We spend
57:47
no time teaching people how to use an iPhone. And so what we're doing right
57:50
now is we're banning phones in schools. This very powerful technology,
57:54
we're banning them in schools, which, by the way, if you actually look
57:58
at the data, not actually react to corollary sort of things,
58:03
the bans aren't actually producing anything. In fact, it's producing some negative outcomes.
58:07
And we cover that on CITL's website. But. But if you
58:11
look at the data telling people to, like teaching
58:15
people how to use pens and pencils, that's critically important. But avoiding and
58:19
putting our heads in the sand and taking powerful technology like, like mobile
58:22
devices or like AI and not preparing them for that is
58:26
terrifying. Absolutely terrifying.
58:29
And when I say preparing people, we need to prepare educators, we need to prepare
58:33
future students, we need to prepare communities, parents need to be educated
58:37
in this area. And we just keep avoiding it. And to
58:42
me, it's like running into a
58:46
brick wall all the time.
58:49
It's definitely a concern. So I have a final question.
58:53
But before, I don't know if you can Be brief with it. In what ways
58:56
do you think AI can be inclusive and in what ways you can see that
59:00
has the danger to be inclusive, exclusionary. So there's
59:05
a couple ways. I mean, so inclusive. What we know is AI can
59:09
provide greater means of accessibility, so we
59:12
could just look at like little applications and it's not. And I, and I
59:16
don't like talking about AI and tools, but to be brief. So Be My Eyes
59:20
is an application that's been around for a long time. Think of it like Zoom
59:24
for people with visual impairments. That or and combined with Uber.
59:28
Right. So someone with a visual impairment has their phone and they're
59:32
at a place they need to be able to see kind of what's going on
59:34
around them. They use Be My Eyes and historically what they would do is
59:38
they would call out and someone would get on and kind of interpret kind of
59:42
what's going on around them. It'd be very human based. Be My Eyes
59:47
most recently partnered with OpenAI and now has AI
59:51
based systems. So these AI systems are multimodal, meaning if. Meaning they
59:55
can interpret multiple things in the environment. Not only the way we type, but obviously
59:59
human language and the way we talk, but also they can look
1:00:03
at the visual scene in front of them so they can interact with the world
1:00:05
visually. So Be My Eyes partnered with them and now
1:00:09
it has been enabled within their app so
1:00:13
that people who are blind can actually see the environment, not rely on
1:00:17
another human to actually go throughout the world.
1:00:21
Now, is it absolutely perfect? No, but it never was.
1:00:25
And so we can. That's a different conversation. But that's just one example
1:00:29
for the way it could be make more accessible, inclusive sort of environments.
1:00:32
How can it exclude. These models are
1:00:36
based on the same biases that we were just talking about earlier. These models
1:00:40
have been trained on human data. So if the biases are embedded in
1:00:44
human data, they're embedded in these models. And so when we work on,
1:00:47
when we work in AI literacy, when we educate people on AI
1:00:51
literacy, we need to educate people on the biases that exist and
1:00:55
to look out for those biases in these models. And then we need to think
1:00:59
about how do we proactively design environments going back to UDL for
1:01:04
how do we embed this into the conversation? So when we work with school
1:01:08
districts or states or even ministries of education and talk about
1:01:11
guidelines, guidelines, guardrails for, for AI
1:01:15
adoption, UDL is part of that conversation. And the idea
1:01:19
of designing for all people from the very beginning needs to be part
1:01:23
of that conversation. Because if we do not do that. There are going to be
1:01:27
huge impacts. There's already, we know there's going to be huge impacts by AI.
1:01:30
This is a deep dive and I've, you know, and I can go on and
1:01:34
on about it, but, but, you know, I think this is a major conversation the
1:01:38
field needs to be having, and unfortunately, not everyone's having it. Yeah,
1:01:42
absolutely. All right, this is the last question. And we do this to every interviewee
1:01:46
as well. It's about hoping. It's about dreaming. You know, there's,
1:01:50
there's not a lot of, there's some, some upsetting stuff going on lately.
1:01:55
For example, we learned that the Office of Special Education Services,
1:01:58
we was moved at the Department of Health
1:02:03
and Human Services. You know, there's all these different things. So help us dream
1:02:08
and hope for the future. What, looking into 10 to five years, what changes
1:02:12
would you like to see the most in the educations of students with disabilities?
1:02:15
You know, I'm going to go back to, I'm going to, you know,
1:02:19
I'm going to go back to Skirtic's work. You know, my hope,
1:02:22
my hope and dream is that we move
1:02:27
out of this, you know, technocratic bureaucracy sort of system that
1:02:31
is categorizing kids and classifying kids and excluding
1:02:36
kids and having separate systems. I would like to see five
1:02:40
to 10 years that we have a system that is not reactionary,
1:02:44
but that is proactive and is able to then react
1:02:49
to the needs of kids in a dynamic and
1:02:53
timely manner. So it's not reactionary in that we
1:02:57
are creating these separate systems, but then we have one system that's designed for
1:03:02
all humans, that deals with the variability of all humans.
1:03:05
Now, can that happen in five to 10 years?
1:03:08
I don't know. Yeah, maybe with AI. Yeah,
1:03:13
maybe with AI. And that is the concern is like,
1:03:16
what's the role of AI in all this and how does it get interpreted?
1:03:20
And again, we don't have time to deal with that conversation today, but if
1:03:25
we want to talk about that another time, it's definitely something I spend a lot
1:03:28
of time talking about these days. Yeah. Well, thank you. So first I'm
1:03:32
going to say cheers and, and, and I'll say hi to Tom Scary,
1:03:35
whatever his app or whatever, whatever his soul
1:03:40
is. Yeah, I send a big cheers to him. Hey, I influenced a
1:03:44
lot of people, including you and me, so cheers to him.
1:03:47
And thank you so much, Jamie, for being with us.
1:03:50
Yeah. And thanks for, thanks for having me and, and good luck with the podcast.
1:03:54
Thank you.
1:03:59
Thank you for listening to Dive. I hope you learned
1:04:03
from this episode as much as I did. Please help us to spread
1:04:07
the word about the show. See you next time.