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Trailblazers in research,
innovators in technology,
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and those who simply have a good story:
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all make up the fabric that
is George Mason University,
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where taking on the grand challenges
that face our students, graduates,
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and higher education is our
mission and our passion.
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Hosted by Mason President
Gregory Washington,
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this is the Access to Excellence podcast.
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The world is changing.
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Virginia and the nation require
institutions that can rapidly
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align the next generation
workforce with the evolving needs
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of the economy and our communities.
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More is already demanded of
this generation than any before
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them.
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We have no choice but to
prepare them for a task that is
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nothing short of saving
the world. At George Mason,
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we call it advancing 21st
century education for all.
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It's one of the key pillars of
our Grand Challenge initiative,
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and I can't think of a better person
to talk to us about it than our guest.
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Dr. Ingrid Guerra-López,
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dean of George Mason's
College of Education and Human
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Development, Dean Guerra-López,
welcome to the show.
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Thank you. It's a pleasure to
be here. Thanks for having me.
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Well, let me start high level here.
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Where does your passion
for education come from?
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So, it, it actually, I would say maybe
doesn't come quite from education,
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it comes from learning.
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I've always been really
drawn to asking questions,
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to needing to understand
how things connect,
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just overall general inquiry
and curiosity, you know,
how things fit together.
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And so learning to me is
ultimately what the promise of
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education is. Learning in itself,
it, it's intrinsically valuable.
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It expands us. It, it
deepens our judgment. Uh,
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it fuels so many other things. And
education is one of those means.
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It's one of the many pathways
through which learning can occur.
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We can learn through so
many ways: on our own,
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through reflection and experience,
uh, informally in our communities,
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through family, through our work,
vicariously by watching others,
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and through that formal educational
system. So I think it's,
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it's really important to distinguish the
education from the actual point of it,
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which is learning and growth.
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You got teachers and you
have learners, right?
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That's right.
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So, before we talk a bit about
the future in the 21st century,
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talk to me a little bit about the current
status of the education system, right?
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What are our streams, what
are our current challenges?
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And there are very few areas more maligned
in, in my opinion, than education,
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especially, especially at the
K-12 level in the country. And so,
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talk to me a little bit about
where we are currently positioned.
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Yeah, I, I do think that we do have a
deep commitment for equity and for access.
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And there's a,
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a genuine sustained effort across
states and districts to expand access.
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And whether it's through early childhood
programs or inclusive special education
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services or college
access pathways, you know,
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even support for
multilingual learners. We've
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expanded who education is for,
and that matters enormously. Now,
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the next step is really ensuring that
access translates into meaningful
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opportunity and high quality
learning experiences for everybody,
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for every learner. So I think that's
one really important strength that we,
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we have right now. I think that
there are also extraordinary, uh,
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innovation pockets across the country. Uh,
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we know that educators
are experimenting boldly,
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whether it's through problem-based
learning or competency-based progression,
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industry partnerships,
AI-assisted instruction.
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There's a lot of things that are
going well in terms of innovation.
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The challenge isn't a lack of innovation,
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it's that innovation is often localized.
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It's isolated in pockets
rather than scaled system-wide.
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So I would say that
that's really important.
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I would also highlight that the
research base is fairly strong.
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We know more than ever before,
um, how children learn.
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We know about brain development,
uh, motivation and engagement,
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effective feedback, et cetera.
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The learning sciences and human
development research base is,
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it's pretty robust.
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That's part of the work that we do
through our partnerships at the College of
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Education and Human Development.
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One of our really exciting initiatives
is a research practice partnership
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ERA•NOVA, our Educational Research
Alliance of Northern Virginia,
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where we engage with over 20 school
divisions across the region and beyond
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connecting research directly
to district level practice,
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especially this year around AI readiness.
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So you gave me a lot of the strengths,
and you talked about scalability.
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I see that as being a
challenge. Mm-hmm .
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But if we know how to do this right,
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if our research has given us
more insight than ever before,
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we, we have all of this positive,
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why do we not have better
educational outcomes,
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especially at the K-12 level?
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So there's, there's a couple of things.
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I think our educators are
represent an interesting variable,
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because on the one hand, the
resiliency of those educators are, um,
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it's a strength, right? They've
shown us that they can navigate a, a,
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a global pandemic, um, rapid
technological change, et cetera.
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But at the same time,
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we're seeing more teacher burnout and
issues with retention than ever before.
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We're asking them to be all things to
all people, instructional designers,
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and data analysts, and technology
integrators, and social workers.
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All the things without
systematically redesigning
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workload, support
structures, compensation. And
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preparation alone is not enough, right?
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You need that induction and that support
and the mentorship and the professional
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growth systems that, that
have to evolve with it.
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So that's why modernizing educator
preparation and building stronger
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support pipelines is so central. So
what I'm getting at is really that,
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that we have a structural mismatch.
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Our current system was largely optimized
for predictable career pathways and
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content transmission
and standardized pacing,
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like all of the things of the
industrial area workforce required.
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Today's economy though, requires more,
uh, adaptability and continuous learning.
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It requires comfort with a
certain level of ambiguity,
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and it also requires us to think
across different disciplines.
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So we're still organized around
seat time and subject silos,
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while the world rewards problem solvers
right across different boundaries. So,
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um, I don't know if it's a, a failure
as much as it's a structural lag.
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Structural lags unimplemented
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manifest themselves to the
broader public as failures, right?
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Yeah.
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Yeah. So let's back up for a second.
You, you hear these calls of reform,
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you hear these calls of
rethinking college education.
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Where does the call come from the loudest?
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I think it comes from, uh, different
people, from everybody, really,
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but for different reasons, right?
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So you have employers who want
graduates who can navigate
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complexity and technology and,
and, and change. Understandably,
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families want return on investment
and a good quality of life for their
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graduates. Governments want workforce
alignment and economic competitiveness,
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right? They want our educational
systems to be aligned with that.
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Students just want relevance. You,
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you go into a classroom at any level
and you hear students asking you
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like, how does this connect
to the real world? You know,
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what will I do with this? They don't
reject rigor. They reject irrelevance.
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Right?
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And then you have industries like
healthcare and technology sectors who want
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interdisciplinary thinkers,
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because those fields are evolving so
quickly that narrow specializations
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aren't enough. They want
engineers who understand ethics.
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They want healthcare
professionals who understand data.
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They want leadership who can translate
between disciplines, you know,
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and technologists who
understand human behavior.
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If I were to now ask the real
question, the big question, you know,
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we're sitting in the 21st century, right?
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We largely have a 20th
century educational framework.
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Uh, classes today aren't taught that much
differently than what they were taught
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in 1999. Uh, we,
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we had electronic means
of delivering content,
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and that was incorporated into our world.
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Fast forward,
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we have the most disruptive
technology of our generation.
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Artificial intelligence has now
moved beyond the laboratory,
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beyond the application of a few
people who are on the bleeding
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edge to really being
mainstream. Right? Right. Now,
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50% of American households
use AI in some form.
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It's about as mainstream as you can get.
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So what should 21st century education
look like at different levels?
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So from early childhood through doctoral
programs, what should it look like?
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Put your crystal ball on.
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Yes. Yes. Love to bring out my crystal
ball. So, I, I think at those, uh,
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very early years and early childhood,
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it's really critical
to cultivate curiosity,
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play-based problem solving.
And of course, you,
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you wanna integrate with early digital
literacy, right? Not just screen time,
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but digital understanding.
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So, unpack that. It sounds intriguing.
What does that actually look like?
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It's really, um, understanding
what the technology is,
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right? Where, how algorithms
work and, and again,
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at a developmentally
appropriate way, you know,
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making a distinction between, you know,
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real world connection and what you
might get out of the, the technology.
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It, it's a, it's a lot
of different things.
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They're born into a generation where, um,
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technology all around them. So
understanding what it does well,
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what it doesn't do well,
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that early discernment about
how technology can help,
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but what the limitations are as well.
I think that there are other things,
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right? So we, we,
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we tend to talk about technology and
technology being such a disruptor, but,
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but there are also those uniquely
human skills that are just as
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critical. Uh, and so as you think
of the progression through K 12,
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the project-based learning is really
important because it builds in that
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relevance,
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and it really does create an
environment where you have to integrate
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knowledge,
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different subject matters into a
coherent project that's tied to a,
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a real world authentic environment.
So, you know, even in stem, it,
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it needs to be applied, right? Like,
what community problem are you solving?
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Uh, and again, that AI literacy
that's appropriate at, at every level.
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And, and really critically, again,
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I would have emphasize that it's
that real world problem solving
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tied to community challenges.
That's something that, you know,
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is so integral to what, what Mason does.
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And I think that that's really critical.
As we move through undergraduate,
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again, the interdisciplinary
learning is really critical.
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Industry connected experience is one
of the things that we try to do at our
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college is, you know, engage our
students in sometimes as many as,
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as two different kinds of internships
or applied learning experiences in
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workplaces or in those kind of
environments, because it's so critical.
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The data literacy, you know,
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whether they're gonna go on to work
in a classroom or any other setting,
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we live in these highly
technology-integrated,
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uh, data-rich environments. And the, the
data literacy is, is really critical.
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And just like the technology
piece is important,
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the ethical reasoning is
important, right? It's,
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it's not just the use of technology.
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It's ethical reasoning
around technology. And,
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and we know from,
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there's a really interesting survey that
is deployed every three years by the
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World Economic Forum, and they survey
employers across the globe, um,
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every three years or so.
And, you know, those,
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the skills that they consistently
have at the top as desirable for
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global employers continues to be
those transferable skills, right?
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So adaptability, critical thinking,
communication, systems thinking.
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So that has to be embedded, uh,
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in our undergraduate curriculum all
the way through our, our graduate, um,
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stages with systems
thinking and research to
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impact pipelines. Again,
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I think one of the things that's unique
and a great strength of George Mason is
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that we really focus on
research of consequence.
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That there is an immediate
sort of transdisciplinary
approach to what we do in
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that we work closely with the community.
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We work on societal challenges
that matter to our communities.
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And so that has to be a critical
environment through which we,
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we teach at the graduate level
or at the doctoral level,
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those research skills that are,
you know, really tied in that, uh,
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problem of practice.
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But you walk in the classroom of today,
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and those young people are living in
a half virtual half real environment,
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right? They're on their phones when
they go home, they're on their iPads,
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they're on their laptops, and the like.
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They're literally interfacing with ai.
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AI is a helper for them. They're asking
it questions, they're engaged with it.
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They are already there, right?
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And so what does educating this
next generation of educators
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look like so that they can actually engage
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with young people at that level?
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Because it can't be traditional,
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it cannot be the way you and I learned,
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because the young people, aren't
they, we didn't have the tools.
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We didn't have the tools that they
had. I remember hours in stacks, right,
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in the library.
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Or I remember getting online
and spending hours with Google
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searches, and they're not
using Google searches anymore.
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They go right to the answer and to
the references in a very quick way
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just by knowing how to properly
prompt or do they, right?
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So these are the kinds of things that I'm
trying to see where we are in terms of
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educating the next generation
of educators who have to teach
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to students who have these tools.
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Yeah, no, absolutely. Right? If,
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if we're serious about preparing
students for a rapidly changing world,
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then that means we have to start
with the adults who guide them, and,
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and that's our teachers.
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So modernizing education
begins with modernizing the
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teaching profession in a lot of ways.
And, you know, today's teachers are not,
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they're not just content
experts or deliverers.
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It's a complex professional operating
and dynamic environment. So I think,
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you know, education today and for the
next, uh, generation of educators, uh,
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they're, you know,
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clearly instructional designers because
the content isn't enough and a textbook
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is not really enough.
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They're designing learning experiences
that are integrating many of those
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elements that I, I, I talked about, right?
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Whether it's project-based learning and
then technology tools in a purposeful
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way, or interdisciplinary content
applied right in real world
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problems.
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They have to understand how to scaffold
learning how to potentially use those
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technology tools to
differentiate instruction,
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how to potentially use those
AI tools to develop meaningful
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performance based assessments.
So that's one component of,
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you know, what they're now having to
do in this next generation. But again,
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going back to the data-rich environments
that also have to be data interpreters,
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right? We know that classrooms are
increasingly data-rich environments,
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and teachers have to be able to
interpret assessment results,
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identify learning patterns, and adjust
instruction in real times in many ways.
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So that, that data fluency, it's
not just about spreadsheets,
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it's about instructional decision making.
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The technology component, right?
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They have to be technology integrators.
It's not as an add-on. It's embedded in,
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as you were saying,
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in describing how students learn
and how they work and how they live.
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So teachers need to understand
when technology enhances learning
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and when it distracts from it, you know,
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there have been many
instances where in some cases,
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technologies were integrated in
the classroom. I'm thinking of the,
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the smart board, for example. And then
they sat there as symbols of progress,
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but there wasn't any support in many
cases provided to teachers to take
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advantage of the technology, not
only to enhance teaching practices,
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but to enhance learning outcomes
and to model for students how to use
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technology effectively. So,
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so they have to now know how to
integrate AI tools responsibly and
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how to help maintain academic
integrity while at the same
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time embracing innovation.
And, and that's a balance.
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This is where I, I want to have a,
a more lengthy discussion, right?
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Should our teachers educate our students
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in how to effectively develop
and utilize prompts so that they
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can properly interface and engage with a
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large language model.
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So AI is, is a lot of things,
right? There's a, certainly a,
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a literacy component to it, just as far
as understanding what it is. And it, it,
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it's also a tool in
that it helps them apply
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learning sciences.
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Yeah. But it, but it has a language.
And that's the thing. So, so, you know,
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I tell people all the time,
if you get on your computer,
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you give it a PDF of a paper
or of a book, and you say,
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review this book for me, and give
me, and give me your summary of it.
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I would contend to them that that
is an improper way to use AI,
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right? But it's the way in which people
engage and interact with it, right?
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But they're not really speaking
the language of how the computer,
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which AI is really giving you your
answers based on associations.
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It associates the,
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the words that you write with
specific sets of other words
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and other outcomes that it knows.
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So if you don't want it to
hallucinate or give you things
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that are really, shouldn't be part
of the question in which you ask it,
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you actually need to take care of
that in how you ask it, right? You
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need to start to focus the large
language model to a general framework,
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a general area that's involved
with the document or that,
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that you've given it. You
need to tell it who it is,
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so it knows where to pull
prerequisite information to help
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it do the identifications that are
necessary to get your answer, right.
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So one example is you have a person
do a general prompt. You give them a,
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the same book, you have them do a
general prompt where they ask it,
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summarize this for me, blah, blah,
blah. And let's say it's on physics,
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you know, it's on
electromagnetics. I'm, I'm sorry,
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I'm giving you an engineering scenario.
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It's, it's okay.
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But let's say it's on
electromagnetics and you say,
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summarize this book on electromagnetics.
That's one way, another way to say is,
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you are the foremost electromagnetics
physicists in the world.
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Your research is on blank
relative to electromagnetics.
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Take this book, summarize it.
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Give me relative feedback with
emphasis on A, D, C, D and E.
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I'm gonna get a very different set
of outcomes that I've gotten with
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just a straight summarize
this. Yeah. Right?
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And because our young people are
gonna be interfacing in dealing
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with young people who are gonna be
interfacing with this technology, to me,
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it's critical that they know how to do
it. People are gonna use it. So you,
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you better learn, they better know how
to use it in the most efficient way,
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in the most efficient
mechanism possible. Right?
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And so we're still debating
whether it's cheating or not,
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and we really should be about how do
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you best employ it to give you an
advantage over the other folk who
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are still debating whether it should even
be used or not. Right? Because to me,
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that ship is kind of sailed.
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Oh, absolutely, absolutely. What you
are describing, so I mentioned earlier,
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AI is a lot of different things,
right? It can be seen as a tool,
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as a career pathway, uh,
as a disruptor. But to me,
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you're describing AI as a literacy, right?
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It's something that
students must understand.
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We teach reading and writing
because literacy empowers agency and
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AI literacy is gonna serve
a similar function. Um,
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students and educators both need to
understand how AI systems are trained,
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where bias can enter,
what hallucinations are,
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how to verify an AI generated output,
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or what ethical boundaries really
matter as you create your prompt or as
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you think about how to engage
with AI and how data privacy works
355
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as well. So without that kind
of literacy, I definitely agree.
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Like we risk creating
passive consumers of,
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of technology instead of
informed critical users.
358
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You know, we have very,
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very highly regarded education programs
here at George Mason from special ed
360
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to education leadership.
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And so what makes Mason stand
out as an education institution
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in your mind?
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Yeah, I think, um, and I mentioned
this a little bit earlier,
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I think the fact that we have such
strong ties to our community and our
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educational partners,
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we're working in real problems of
practice that our school partners see
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as, as priorities. One of the,
368
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the really exciting initiatives
that I mentioned our ERA•NOVA
369
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partnership. We're really approaching,
even AI, for example, not,
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not from a high perspective, but
working directly with our, uh,
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school division leaders to define
what readiness actually means.
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Whatever your subject matter is, it's
gonna be relevant a across the different,
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uh, content areas of teaching. So
we're asking things like, you know,
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what competencies should
teachers have in an AI enabled
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classroom? Um, and, and, you
know, responsible classroom
integration look like.
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What, what is that? How do we balance
innovation with student safety? Um,
377
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how do we actually even know
whether AI is improving learning?
378
00:23:46,585 --> 00:23:49,045
So one of the things that, um,
379
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we are doing as a result of that
collaboration is identifying very
380
00:23:54,605 --> 00:23:58,805
specifically the kind of skills that we
should be embedding across all of our
381
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educational programs across all of
our teacher preparation programs,
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whether it's in special education
or early childhood education,
383
00:24:06,726 --> 00:24:08,085
or secondary education,
384
00:24:08,355 --> 00:24:12,005
because that's just going
to be part of the job.
385
00:24:12,435 --> 00:24:15,765
I've heard some alarmist kind
of warnings that, you know,
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00:24:16,585 --> 00:24:20,605
AI is going to, uh, eliminate teachers,
and that just simply isn't true.
387
00:24:20,815 --> 00:24:25,565
We've been hearing those concerns
for a long time. We heard it,
388
00:24:25,665 --> 00:24:26,006
you know,
389
00:24:26,006 --> 00:24:29,725
with the radio and the television and
the internet and the cell phones ,
390
00:24:30,475 --> 00:24:34,165
what it's going to do is elevate
the teaching profession, right?
391
00:24:34,806 --> 00:24:39,365
Because if you look at not just the
teaching profession, but all professions,
392
00:24:39,366 --> 00:24:42,965
it is fundamentally changing
the way in which you work,
393
00:24:43,145 --> 00:24:47,605
the actual critical tasks that
are required, how well you do it.
394
00:24:47,984 --> 00:24:50,365
So it is, uh, in my
opinion, going to elevate.
395
00:24:50,366 --> 00:24:54,525
So I think that's one of the things
that's really unique about us.
396
00:24:54,675 --> 00:24:58,445
It's that integration between
research and practice. It,
397
00:24:58,905 --> 00:25:02,125
we don't just stay at
the theory of things,
398
00:25:02,345 --> 00:25:04,885
but we're using research and, uh,
399
00:25:05,125 --> 00:25:10,045
research capacity and theory to work
with our educational partners and
400
00:25:10,046 --> 00:25:13,244
the educational community to,
to address real challenges.
401
00:25:13,825 --> 00:25:17,805
So if I were to ask you
who's actually successfully
402
00:25:18,865 --> 00:25:23,484
making this change and adapting
as you've highlighted here, who,
403
00:25:23,494 --> 00:25:24,845
who's doing that at George Mason?
404
00:25:25,105 --> 00:25:27,205
You mean across our
educational programs or?
405
00:25:27,206 --> 00:25:27,595
Yeah.
406
00:25:27,595 --> 00:25:30,325
Yeah. I, I think I, like
I said, I think we're,
407
00:25:30,335 --> 00:25:33,845
we're all doing it that ERA•NOVA
that research practice partnership,
408
00:25:33,846 --> 00:25:37,405
we have faculty across many programs,
409
00:25:37,406 --> 00:25:41,845
including educational
leadership who are really
410
00:25:42,025 --> 00:25:45,805
vested in working. We have, uh, a
couple of faculty right now. We,
411
00:25:45,825 --> 00:25:47,205
we were successful in, uh,
412
00:25:47,206 --> 00:25:51,085
obtaining a global data sharing agreement
with a couple of our school divisions.
413
00:25:51,905 --> 00:25:56,205
And what we did is we prioritized
the areas of interest of those school
414
00:25:56,206 --> 00:25:56,646
partners.
415
00:25:56,646 --> 00:26:01,445
So we already have faculty
in the college testing out
416
00:26:02,265 --> 00:26:07,205
AI tools to enhance math
instruction and literacy
417
00:26:07,315 --> 00:26:11,045
instruction. And that's huge
because it, it, you know,
418
00:26:11,225 --> 00:26:14,805
it requires for the school division
to have a lot of trust in us.
419
00:26:15,505 --> 00:26:19,165
And so we're, that's just
the, the kind of, I think,
420
00:26:19,395 --> 00:26:22,405
work that we're doing in partnership
with our school divisions to,
421
00:26:22,505 --> 00:26:25,365
to modernize the teaching profession.
422
00:26:25,775 --> 00:26:30,725
These technologies are gonna solve
some significant problems for us.
423
00:26:31,325 --> 00:26:32,365
I, I do believe,
424
00:26:32,945 --> 00:26:37,205
as you highlighted that the teaching
profession isn't going away.
425
00:26:37,835 --> 00:26:42,685
What I caution is stating
that it's not going to have to
426
00:26:42,686 --> 00:26:44,205
radically change, right?
427
00:26:44,984 --> 00:26:49,244
You can interface with a
teacher who understands
428
00:26:49,875 --> 00:26:53,685
many of the great works
of Shakespeare, right?
429
00:26:54,145 --> 00:26:59,045
Or you can interface with
a bot that has read every
430
00:26:59,046 --> 00:27:03,765
great work on any subject
and can correlate it,
431
00:27:03,815 --> 00:27:04,648
right?
432
00:27:05,145 --> 00:27:09,605
And so how does that professor
engage with a student
433
00:27:09,955 --> 00:27:13,885
that has access to that tool,
right? Because in some instances,
434
00:27:14,825 --> 00:27:16,525
the, the, the, the, the tool,
435
00:27:16,665 --> 00:27:20,885
the technology actually has
a greater knowledge base
436
00:27:21,744 --> 00:27:26,525
and is able to synthesize that
knowledge base better than the
437
00:27:26,526 --> 00:27:30,685
professor. The tool
itself has the ability to
438
00:27:32,215 --> 00:27:36,125
synthesize and bring
information together. And, and,
439
00:27:36,484 --> 00:27:38,285
and for lack of a better
way of saying this,
440
00:27:38,286 --> 00:27:39,845
and almost like a human-like manner.
441
00:27:40,425 --> 00:27:45,285
So we have to teach people
how to find their place
442
00:27:46,145 --> 00:27:47,445
in that environment.
443
00:27:48,185 --> 00:27:52,005
And I think that that's
critical and non-trivial, right?
444
00:27:52,565 --> 00:27:55,405
I know we have people thinking
about this and working on this here.
445
00:27:56,225 --> 00:28:00,845
Do you have some examples of any
programs that are utilizing that?
446
00:28:01,845 --> 00:28:05,765
I guess I would kind of take
us a little further back.
447
00:28:06,355 --> 00:28:10,845
It's not about content, right?
The role of an educator.
448
00:28:11,545 --> 00:28:16,045
It requires that human judgment. We can't
compete with the knowledge generation,
449
00:28:16,145 --> 00:28:18,285
the analysis, in some
cases, the synthesis,
450
00:28:18,305 --> 00:28:20,525
but that's not the value
of an educator, right?
451
00:28:21,234 --> 00:28:25,685
It's really that human connection.
It's that mentorship, it's discernment.
452
00:28:26,515 --> 00:28:31,285
It's very subtle art of recognizing
when a student is struggling.
453
00:28:31,835 --> 00:28:33,605
It's the human connection.
454
00:28:33,905 --> 00:28:38,205
It is the helping to love to learn,
455
00:28:38,305 --> 00:28:40,765
to engage with learning
on an ongoing basis.
456
00:28:42,065 --> 00:28:47,005
That's the challenge is right now,
we're, and you know, lots of folks are,
457
00:28:47,025 --> 00:28:48,285
are talking about this. We're,
458
00:28:48,535 --> 00:28:53,365
we're educating students for a world
that we probably can't even imagine.
459
00:28:53,905 --> 00:28:55,565
No, that's right. Right? But,
460
00:28:55,585 --> 00:29:00,245
but I contend to you that we've always
educated young people for worlds that
461
00:29:00,246 --> 00:29:01,685
they could not imagine. Right?
462
00:29:02,365 --> 00:29:07,325
I remember we were educating
people in the early and mid-2000s
463
00:29:08,425 --> 00:29:13,245
for an explosion of
wireless and internet of
464
00:29:13,246 --> 00:29:18,205
things based technologies
that hit long before these
465
00:29:18,206 --> 00:29:22,125
young, we didn't know what those
technologies were gonna look like, right?
466
00:29:23,825 --> 00:29:27,725
But we graduated young people who can
interface and, and engage with them.
467
00:29:27,945 --> 00:29:32,845
And so I think you're hitting the
nail right on the head with this whole
468
00:29:32,895 --> 00:29:33,728
piece
469
00:29:34,745 --> 00:29:39,725
of leaning into that human
connectedness part, right? My,
470
00:29:40,065 --> 00:29:42,285
the best teachers, uh,
471
00:29:42,425 --> 00:29:45,405
the best teachers that I've
had throughout my career
472
00:29:47,075 --> 00:29:49,285
have been people who could do that, right?
473
00:29:49,905 --> 00:29:53,405
Who could look at you and see your
strengths in your development cycle,
474
00:29:53,545 --> 00:29:57,485
who could see your weaknesses, right?
And they didn't do that by, uh,
475
00:29:57,725 --> 00:30:01,365
a test per se. They
did this by discerning,
476
00:30:01,475 --> 00:30:05,765
they did this by watching
you engage and seeing,
477
00:30:06,745 --> 00:30:10,085
you know, it could be where you stopped
your pencil as you were writing.
478
00:30:10,305 --> 00:30:14,405
It could be the look that was on your
face as you were engaging, right?
479
00:30:14,985 --> 00:30:19,845
It could just be the feeling
that they got from engaging
480
00:30:19,955 --> 00:30:24,605
with you on a specific issue
or on a specific problem,
481
00:30:24,735 --> 00:30:29,005
right? Those pieces are, in my opinion,
482
00:30:30,085 --> 00:30:30,918
uniquely human.
483
00:30:30,945 --> 00:30:31,745
That's right.
484
00:30:31,745 --> 00:30:33,165
And we have to figure out
485
00:30:34,695 --> 00:30:39,195
how to emphasize them
and lean into the tools.
486
00:30:39,335 --> 00:30:40,168
That's right.
487
00:30:40,395 --> 00:30:41,275
You, you, you get what I mean.
488
00:30:41,715 --> 00:30:42,185
Absolutely.
489
00:30:42,185 --> 00:30:44,475
That is the solution.
That's, that is, or at least,
490
00:30:45,335 --> 00:30:47,075
that's the solution right now, .
491
00:30:47,435 --> 00:30:49,115
Right? That that's right. We,
because don't be because we.
492
00:30:49,275 --> 00:30:49,956
Don't know what the
future's gonna look like.
493
00:30:49,956 --> 00:30:51,875
That's right. We, we don't know
what the new thing will be.
494
00:30:52,295 --> 00:30:55,955
And so regardless of the
change and the, regardless of,
495
00:30:56,415 --> 00:30:58,235
of the tools that come along, right?
496
00:30:58,265 --> 00:31:02,675
What we're really trying
to promote is adaptability.
497
00:31:03,375 --> 00:31:07,195
And again, change is always, it,
it's only accelerating, right?
498
00:31:07,196 --> 00:31:10,635
So we don't have the luxury of
looking away and saying, well,
499
00:31:10,636 --> 00:31:12,875
I don't like technology and
I don't like the AI thing,
500
00:31:12,876 --> 00:31:16,075
or whatever the technology might be. And
just say, well, I'm not gonna engage.
501
00:31:16,695 --> 00:31:18,195
The world has moved on, right?
502
00:31:18,375 --> 00:31:22,355
So I think one of the critical things
that is gonna be really important for
503
00:31:22,795 --> 00:31:23,295
educators and,
504
00:31:23,295 --> 00:31:28,035
and educational systems
is to promote the ability
505
00:31:28,095 --> 00:31:32,075
for students to engage
in lifelong learning and
506
00:31:32,315 --> 00:31:36,835
adaptability 'cause that is always
going to be a constant requirement.
507
00:31:37,095 --> 00:31:42,075
So let me ask you this, because
you, you clearly are, uh,
508
00:31:42,135 --> 00:31:46,915
as an educator, you're gonna have
to deal with humanist on the,
509
00:31:47,055 --> 00:31:51,755
the ethical values of what you teach
and what you don't teach, right?
510
00:31:52,095 --> 00:31:57,075
And so how can classical liberal
arts education evolve to meet the
511
00:31:57,076 --> 00:32:02,035
needs of these 21st century students
and workers and employees and employers,
512
00:32:02,036 --> 00:32:02,535
right?
513
00:32:02,535 --> 00:32:07,315
How do we evolve the classical liberal
arts framework in order to meet that
514
00:32:07,385 --> 00:32:08,218
need?
515
00:32:09,065 --> 00:32:12,475
Yeah. I, I think, you know,
it's just as important as it's,
516
00:32:12,475 --> 00:32:16,035
as it has always been.
Um, I think, you know,
517
00:32:16,135 --> 00:32:20,995
we want to, um, leverage,
you know, the logic,
518
00:32:21,255 --> 00:32:26,235
the logical reasoning that comes
from, from philosophy and, you know,
519
00:32:26,335 --> 00:32:30,435
the history, uh, patterns
right across history.
520
00:32:31,215 --> 00:32:34,235
So I, I think they're just
as relevant as before,
521
00:32:34,295 --> 00:32:38,355
but I think like everything else,
it has to evolve and we have to do,
522
00:32:39,365 --> 00:32:43,365
uh, a better job of applying
those insights, right? Like to me,
523
00:32:43,366 --> 00:32:44,525
liberal arts as,
524
00:32:44,545 --> 00:32:49,405
as someone who navigated philosophy
and English and psychology, uh,
525
00:32:49,406 --> 00:32:50,365
in my undergrad,
526
00:32:50,845 --> 00:32:55,365
I have found those skills
to be so critical to
527
00:32:55,375 --> 00:32:57,845
everything I do. And so I,
528
00:32:58,125 --> 00:33:02,125
I think it's just making sure that we're
taking it a step further and that we
529
00:33:02,126 --> 00:33:05,885
are using the liberal arts
in a way that's applied,
530
00:33:05,985 --> 00:33:10,805
and that is clearly relevant. I, I
think it's relevant, but as educators,
531
00:33:10,845 --> 00:33:14,685
I think we need to do a better job of,
of making that connection. But, you know,
532
00:33:14,705 --> 00:33:19,565
as I said, again, this whole idea
of, uh, critical thinking, um,
533
00:33:19,945 --> 00:33:23,525
and, uh, collaboration and insight,
534
00:33:24,055 --> 00:33:27,485
those are all things that I
think our liberal arts are,
535
00:33:27,665 --> 00:33:29,845
are really good at helping us develop.
536
00:33:30,545 --> 00:33:33,125
If you were talking to a
young person right now,
537
00:33:34,405 --> 00:33:39,205
somebody just graduating out
of high school and entering
538
00:33:39,315 --> 00:33:42,565
into the profession, you
say, I want to be a teacher.
539
00:33:43,325 --> 00:33:46,925
Teachers really impacted
me my entire life.
540
00:33:47,385 --> 00:33:51,125
And that's where I see myself having
the greatest impact as a human.
541
00:33:52,025 --> 00:33:54,285
And that young person was looking at you,
542
00:33:55,355 --> 00:34:00,085
what are three things you would
tell that person to make sure you do
543
00:34:00,145 --> 00:34:04,485
now while you're going through your
educational framework in order to make you
544
00:34:04,525 --> 00:34:07,205
a, an effective teacher going forward?
545
00:34:08,205 --> 00:34:12,285
I definitely think that
I would ask them to
546
00:34:12,975 --> 00:34:15,045
model adaptability, right?
547
00:34:15,185 --> 00:34:18,925
To make sure that as you
enter the teaching profession,
548
00:34:19,075 --> 00:34:22,645
that you're aware that students are also
looking at you and how well you embrace
549
00:34:23,045 --> 00:34:27,605
change. So I think that's one
critical thing. Also, this idea that,
550
00:34:27,606 --> 00:34:31,445
that I mentioned before around
problem-based learning is really critical.
551
00:34:32,145 --> 00:34:35,525
The world needs problem solvers, right?
552
00:34:36,075 --> 00:34:41,005
Ethical problem solvers that
regardless of the workplace or context
553
00:34:41,465 --> 00:34:44,525
can work with others to
solve complex problems.
554
00:34:44,545 --> 00:34:49,325
And so embedding that in the learning
environment and in the learning
555
00:34:49,555 --> 00:34:52,805
experiences is, is really critical. So I,
556
00:34:52,885 --> 00:34:56,325
I think those are some of the critical
things that I would make sure that they
557
00:34:56,326 --> 00:34:58,725
know is, is essential
for an effective teacher.
558
00:34:59,055 --> 00:35:02,725
Given where you sit as a leader
and an administrator, right?
559
00:35:03,105 --> 00:35:06,285
And you're leading now cohorts of faculty,
560
00:35:06,355 --> 00:35:11,245
what do you tell them
about how this disruption
561
00:35:11,905 --> 00:35:14,045
that's coming from AI, this,
562
00:35:14,114 --> 00:35:18,165
this change that's
coming to the profession,
563
00:35:18,915 --> 00:35:23,645
what do you tell them about what they
should be doing right now to adapt and
564
00:35:24,305 --> 00:35:28,605
to coexist with these technologies as they
565
00:35:28,985 --> 00:35:29,815
evolve?
566
00:35:29,815 --> 00:35:32,965
Experiment, right? I think
one of the things that,
567
00:35:32,966 --> 00:35:35,405
that we're working on in
the college is to have,
568
00:35:35,665 --> 00:35:40,645
or to develop an AI and other kind of
emerging technologies tinkering lab
569
00:35:41,175 --> 00:35:45,805
where people are in an environment
where they can explore and they can
570
00:35:45,806 --> 00:35:49,085
tinker and they can try out
tools, whether it's with, uh,
571
00:35:49,086 --> 00:35:53,125
with fellow educators or,
you know, a space for other,
572
00:35:53,265 --> 00:35:55,445
for educational leaders as well.
573
00:35:56,114 --> 00:35:59,245
There's on both ends of the
spectrum in some, in some cases,
574
00:35:59,445 --> 00:36:02,364
a lot of fear about safety and
the implications of using it.
575
00:36:02,365 --> 00:36:05,045
And then the other hand, very eager, uh,
576
00:36:05,155 --> 00:36:09,045
folk who want to use it and think it's
the tool for all the, the problems.
577
00:36:09,665 --> 00:36:13,725
And so I think just having
that community space for
578
00:36:14,325 --> 00:36:18,965
educators to explore, to experiment, to
ask questions, to break things, to say,
579
00:36:18,966 --> 00:36:21,364
well, what happens if we do this? And,
580
00:36:21,465 --> 00:36:24,725
and to make that part of
the learning experience,
581
00:36:24,844 --> 00:36:28,765
I think that's only going to reduce
the fear and anxiety of the unknown.
582
00:36:29,555 --> 00:36:31,245
Well, this is all good stuff,
583
00:36:31,505 --> 00:36:35,325
and the kind of thing that
positions us well for the future.
584
00:36:35,835 --> 00:36:38,805
What do you tell your
fellow deans, you know,
585
00:36:38,806 --> 00:36:42,765
some of which are really
struggling with this technology,
586
00:36:42,945 --> 00:36:46,844
and you are kind of at the forefront of
it, because outside of computer science,
587
00:36:46,844 --> 00:36:49,565
it probably affects your
discipline more than any other.
588
00:36:50,045 --> 00:36:53,765
Yeah. I mean, we certainly talk, uh,
589
00:36:53,965 --> 00:36:56,205
I think as leaders often about, you know,
590
00:36:56,305 --> 00:36:59,085
how the implications of
AI in the university and,
591
00:36:59,105 --> 00:37:02,844
and of course the workplace
as well. I, I think, you know,
592
00:37:02,845 --> 00:37:07,605
what I would reiterate with my
colleagues is that there is no one area
593
00:37:07,606 --> 00:37:11,885
that isn't impacted by
the shifts in technology,
594
00:37:11,886 --> 00:37:16,485
whether it's AI or whatever
comes after every single
595
00:37:16,864 --> 00:37:19,285
career, every single sector,
596
00:37:19,775 --> 00:37:24,605
every single space and community is being
impacted by technology in one way or
597
00:37:24,606 --> 00:37:25,439
the other.
598
00:37:25,625 --> 00:37:30,605
And so we have a responsibility
to understand if that's
599
00:37:30,875 --> 00:37:34,205
already changed our communities, and
it's gonna change it even further.
600
00:37:35,305 --> 00:37:39,405
How do we adapt the preparation that we
provide those students during the time
601
00:37:39,406 --> 00:37:44,205
they're with us to make sure that
they're capable and ready to shape and
602
00:37:44,255 --> 00:37:46,364
contribute in that kind of world?
603
00:37:47,265 --> 00:37:51,205
That's it. Well, we're gonna
have to leave it there. Ingrid,
604
00:37:51,975 --> 00:37:56,885
thank you for sharing your
vision and leadership with the
605
00:37:57,165 --> 00:37:58,645
educators of our future.
606
00:38:00,305 --> 00:38:04,685
I'm George Mason president Gregory
Washington. Thanks for listening.
607
00:38:05,785 --> 00:38:10,005
And tune in next time for more
conversations that show why
608
00:38:10,585 --> 00:38:13,685
we are all together different.
609
00:38:16,225 --> 00:38:17,645
If you like what you
heard on this podcast,
610
00:38:18,065 --> 00:38:22,565
go to podcast.gmu.edu for
more of Gregory Washington's
611
00:38:22,566 --> 00:38:25,005
conversations with the
thought leaders, experts,
612
00:38:25,265 --> 00:38:29,885
and educators who take on the grand
challenges facing our students, graduates,
613
00:38:30,085 --> 00:38:33,885
and higher education.
That's podcast gmu.edu.
00:00:04,235 --> 00:00:07,075
Trailblazers in research,
innovators in technology,
2
00:00:07,375 --> 00:00:09,355
and those who simply have a good story:
3
00:00:09,895 --> 00:00:12,275
all make up the fabric that
is George Mason University,
4
00:00:12,275 --> 00:00:16,355
where taking on the grand challenges
that face our students, graduates,
5
00:00:16,355 --> 00:00:19,114
and higher education is our
mission and our passion.
6
00:00:19,775 --> 00:00:21,795
Hosted by Mason President
Gregory Washington,
7
00:00:21,795 --> 00:00:24,155
this is the Access to Excellence podcast.
8
00:00:27,215 --> 00:00:28,235
The world is changing.
9
00:00:29,395 --> 00:00:33,955
Virginia and the nation require
institutions that can rapidly
10
00:00:34,325 --> 00:00:38,835
align the next generation
workforce with the evolving needs
11
00:00:39,255 --> 00:00:41,155
of the economy and our communities.
12
00:00:41,156 --> 00:00:45,995
More is already demanded of
this generation than any before
13
00:00:45,996 --> 00:00:46,829
them.
14
00:00:46,975 --> 00:00:51,795
We have no choice but to
prepare them for a task that is
15
00:00:51,796 --> 00:00:56,035
nothing short of saving
the world. At George Mason,
16
00:00:56,855 --> 00:01:00,515
we call it advancing 21st
century education for all.
17
00:01:01,145 --> 00:01:04,035
It's one of the key pillars of
our Grand Challenge initiative,
18
00:01:04,735 --> 00:01:09,155
and I can't think of a better person
to talk to us about it than our guest.
19
00:01:10,334 --> 00:01:11,834
Dr. Ingrid Guerra-López,
20
00:01:12,905 --> 00:01:17,155
dean of George Mason's
College of Education and Human
21
00:01:17,385 --> 00:01:21,795
Development, Dean Guerra-López,
welcome to the show.
22
00:01:22,205 --> 00:01:24,555
Thank you. It's a pleasure to
be here. Thanks for having me.
23
00:01:25,665 --> 00:01:28,075
Well, let me start high level here.
24
00:01:28,444 --> 00:01:31,955
Where does your passion
for education come from?
25
00:01:32,575 --> 00:01:35,875
So, it, it actually, I would say maybe
doesn't come quite from education,
26
00:01:35,875 --> 00:01:37,194
it comes from learning.
27
00:01:38,145 --> 00:01:41,875
I've always been really
drawn to asking questions,
28
00:01:42,055 --> 00:01:44,355
to needing to understand
how things connect,
29
00:01:44,944 --> 00:01:49,435
just overall general inquiry
and curiosity, you know,
how things fit together.
30
00:01:50,175 --> 00:01:54,675
And so learning to me is
ultimately what the promise of
31
00:01:54,865 --> 00:01:59,835
education is. Learning in itself,
it, it's intrinsically valuable.
32
00:02:00,375 --> 00:02:03,635
It expands us. It, it
deepens our judgment. Uh,
33
00:02:03,855 --> 00:02:07,715
it fuels so many other things. And
education is one of those means.
34
00:02:07,785 --> 00:02:10,115
It's one of the many pathways
through which learning can occur.
35
00:02:10,215 --> 00:02:12,995
We can learn through so
many ways: on our own,
36
00:02:12,996 --> 00:02:16,835
through reflection and experience,
uh, informally in our communities,
37
00:02:16,836 --> 00:02:19,915
through family, through our work,
vicariously by watching others,
38
00:02:20,695 --> 00:02:23,514
and through that formal educational
system. So I think it's,
39
00:02:23,515 --> 00:02:27,514
it's really important to distinguish the
education from the actual point of it,
40
00:02:27,515 --> 00:02:28,514
which is learning and growth.
41
00:02:29,095 --> 00:02:31,435
You got teachers and you
have learners, right?
42
00:02:31,435 --> 00:02:32,175
That's right.
43
00:02:32,175 --> 00:02:36,595
So, before we talk a bit about
the future in the 21st century,
44
00:02:37,065 --> 00:02:40,395
talk to me a little bit about the current
status of the education system, right?
45
00:02:40,825 --> 00:02:43,794
What are our streams, what
are our current challenges?
46
00:02:44,675 --> 00:02:49,555
And there are very few areas more maligned
in, in my opinion, than education,
47
00:02:49,645 --> 00:02:53,995
especially, especially at the
K-12 level in the country. And so,
48
00:02:54,425 --> 00:02:57,755
talk to me a little bit about
where we are currently positioned.
49
00:02:58,155 --> 00:03:02,325
Yeah, I, I do think that we do have a
deep commitment for equity and for access.
50
00:03:02,505 --> 00:03:03,445
And there's a,
51
00:03:03,925 --> 00:03:08,205
a genuine sustained effort across
states and districts to expand access.
52
00:03:08,305 --> 00:03:12,885
And whether it's through early childhood
programs or inclusive special education
53
00:03:13,165 --> 00:03:16,205
services or college
access pathways, you know,
54
00:03:16,206 --> 00:03:18,245
even support for
multilingual learners. We've
55
00:03:19,764 --> 00:03:23,764
expanded who education is for,
and that matters enormously. Now,
56
00:03:23,785 --> 00:03:27,565
the next step is really ensuring that
access translates into meaningful
57
00:03:27,675 --> 00:03:31,525
opportunity and high quality
learning experiences for everybody,
58
00:03:31,526 --> 00:03:35,765
for every learner. So I think that's
one really important strength that we,
59
00:03:35,905 --> 00:03:40,325
we have right now. I think that
there are also extraordinary, uh,
60
00:03:40,326 --> 00:03:43,525
innovation pockets across the country. Uh,
61
00:03:43,625 --> 00:03:46,325
we know that educators
are experimenting boldly,
62
00:03:46,326 --> 00:03:50,685
whether it's through problem-based
learning or competency-based progression,
63
00:03:51,605 --> 00:03:55,165
industry partnerships,
AI-assisted instruction.
64
00:03:55,166 --> 00:03:58,845
There's a lot of things that are
going well in terms of innovation.
65
00:03:58,945 --> 00:04:00,805
The challenge isn't a lack of innovation,
66
00:04:01,715 --> 00:04:04,245
it's that innovation is often localized.
67
00:04:04,355 --> 00:04:08,085
It's isolated in pockets
rather than scaled system-wide.
68
00:04:08,865 --> 00:04:10,845
So I would say that
that's really important.
69
00:04:11,845 --> 00:04:15,165
I would also highlight that the
research base is fairly strong.
70
00:04:15,465 --> 00:04:19,605
We know more than ever before,
um, how children learn.
71
00:04:19,785 --> 00:04:23,245
We know about brain development,
uh, motivation and engagement,
72
00:04:23,246 --> 00:04:25,285
effective feedback, et cetera.
73
00:04:25,425 --> 00:04:27,805
The learning sciences and human
development research base is,
74
00:04:27,835 --> 00:04:28,765
it's pretty robust.
75
00:04:28,945 --> 00:04:33,365
That's part of the work that we do
through our partnerships at the College of
76
00:04:33,366 --> 00:04:34,685
Education and Human Development.
77
00:04:34,705 --> 00:04:38,525
One of our really exciting initiatives
is a research practice partnership
78
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ERA•NOVA, our Educational Research
Alliance of Northern Virginia,
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where we engage with over 20 school
divisions across the region and beyond
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connecting research directly
to district level practice,
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especially this year around AI readiness.
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So you gave me a lot of the strengths,
and you talked about scalability.
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I see that as being a
challenge. Mm-hmm .
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But if we know how to do this right,
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if our research has given us
more insight than ever before,
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we, we have all of this positive,
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why do we not have better
educational outcomes,
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especially at the K-12 level?
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So there's, there's a couple of things.
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I think our educators are
represent an interesting variable,
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because on the one hand, the
resiliency of those educators are, um,
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it's a strength, right? They've
shown us that they can navigate a, a,
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a global pandemic, um, rapid
technological change, et cetera.
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But at the same time,
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we're seeing more teacher burnout and
issues with retention than ever before.
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We're asking them to be all things to
all people, instructional designers,
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and data analysts, and technology
integrators, and social workers.
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All the things without
systematically redesigning
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workload, support
structures, compensation. And
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preparation alone is not enough, right?
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You need that induction and that support
and the mentorship and the professional
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growth systems that, that
have to evolve with it.
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So that's why modernizing educator
preparation and building stronger
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support pipelines is so central. So
what I'm getting at is really that,
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that we have a structural mismatch.
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Our current system was largely optimized
for predictable career pathways and
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content transmission
and standardized pacing,
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like all of the things of the
industrial area workforce required.
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Today's economy though, requires more,
uh, adaptability and continuous learning.
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It requires comfort with a
certain level of ambiguity,
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and it also requires us to think
across different disciplines.
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So we're still organized around
seat time and subject silos,
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while the world rewards problem solvers
right across different boundaries. So,
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um, I don't know if it's a, a failure
as much as it's a structural lag.
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Structural lags unimplemented
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manifest themselves to the
broader public as failures, right?
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Yeah.
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Yeah. So let's back up for a second.
You, you hear these calls of reform,
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you hear these calls of
rethinking college education.
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Where does the call come from the loudest?
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I think it comes from, uh, different
people, from everybody, really,
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but for different reasons, right?
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So you have employers who want
graduates who can navigate
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complexity and technology and,
and, and change. Understandably,
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families want return on investment
and a good quality of life for their
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graduates. Governments want workforce
alignment and economic competitiveness,
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right? They want our educational
systems to be aligned with that.
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Students just want relevance. You,
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you go into a classroom at any level
and you hear students asking you
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like, how does this connect
to the real world? You know,
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what will I do with this? They don't
reject rigor. They reject irrelevance.
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Right?
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And then you have industries like
healthcare and technology sectors who want
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interdisciplinary thinkers,
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because those fields are evolving so
quickly that narrow specializations
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aren't enough. They want
engineers who understand ethics.
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They want healthcare
professionals who understand data.
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They want leadership who can translate
between disciplines, you know,
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and technologists who
understand human behavior.
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If I were to now ask the real
question, the big question, you know,
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we're sitting in the 21st century, right?
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We largely have a 20th
century educational framework.
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Uh, classes today aren't taught that much
differently than what they were taught
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in 1999. Uh, we,
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we had electronic means
of delivering content,
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and that was incorporated into our world.
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Fast forward,
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we have the most disruptive
technology of our generation.
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Artificial intelligence has now
moved beyond the laboratory,
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beyond the application of a few
people who are on the bleeding
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edge to really being
mainstream. Right? Right. Now,
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50% of American households
use AI in some form.
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It's about as mainstream as you can get.
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So what should 21st century education
look like at different levels?
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So from early childhood through doctoral
programs, what should it look like?
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Put your crystal ball on.
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Yes. Yes. Love to bring out my crystal
ball. So, I, I think at those, uh,
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very early years and early childhood,
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it's really critical
to cultivate curiosity,
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play-based problem solving.
And of course, you,
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you wanna integrate with early digital
literacy, right? Not just screen time,
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but digital understanding.
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So, unpack that. It sounds intriguing.
What does that actually look like?
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It's really, um, understanding
what the technology is,
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right? Where, how algorithms
work and, and again,
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at a developmentally
appropriate way, you know,
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making a distinction between, you know,
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real world connection and what you
might get out of the, the technology.
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It, it's a, it's a lot
of different things.
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They're born into a generation where, um,
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technology all around them. So
understanding what it does well,
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what it doesn't do well,
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that early discernment about
how technology can help,
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but what the limitations are as well.
I think that there are other things,
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right? So we, we,
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we tend to talk about technology and
technology being such a disruptor, but,
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but there are also those uniquely
human skills that are just as
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critical. Uh, and so as you think
of the progression through K 12,
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the project-based learning is really
important because it builds in that
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relevance,
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and it really does create an
environment where you have to integrate
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knowledge,
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different subject matters into a
coherent project that's tied to a,
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a real world authentic environment.
So, you know, even in stem, it,
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it needs to be applied, right? Like,
what community problem are you solving?
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Uh, and again, that AI literacy
that's appropriate at, at every level.
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And, and really critically, again,
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I would have emphasize that it's
that real world problem solving
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tied to community challenges.
That's something that, you know,
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is so integral to what, what Mason does.
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And I think that that's really critical.
As we move through undergraduate,
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again, the interdisciplinary
learning is really critical.
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Industry connected experience is one
of the things that we try to do at our
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college is, you know, engage our
students in sometimes as many as,
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as two different kinds of internships
or applied learning experiences in
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workplaces or in those kind of
environments, because it's so critical.
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The data literacy, you know,
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whether they're gonna go on to work
in a classroom or any other setting,
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we live in these highly
technology-integrated,
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uh, data-rich environments. And the, the
data literacy is, is really critical.
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And just like the technology
piece is important,
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the ethical reasoning is
important, right? It's,
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it's not just the use of technology.
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It's ethical reasoning
around technology. And,
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and we know from,
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there's a really interesting survey that
is deployed every three years by the
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World Economic Forum, and they survey
employers across the globe, um,
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every three years or so.
And, you know, those,
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the skills that they consistently
have at the top as desirable for
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global employers continues to be
those transferable skills, right?
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So adaptability, critical thinking,
communication, systems thinking.
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So that has to be embedded, uh,
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in our undergraduate curriculum all
the way through our, our graduate, um,
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stages with systems
thinking and research to
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impact pipelines. Again,
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I think one of the things that's unique
and a great strength of George Mason is
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that we really focus on
research of consequence.
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That there is an immediate
sort of transdisciplinary
approach to what we do in
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that we work closely with the community.
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We work on societal challenges
that matter to our communities.
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And so that has to be a critical
environment through which we,
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we teach at the graduate level
or at the doctoral level,
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those research skills that are,
you know, really tied in that, uh,
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problem of practice.
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But you walk in the classroom of today,
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and those young people are living in
a half virtual half real environment,
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right? They're on their phones when
they go home, they're on their iPads,
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they're on their laptops, and the like.
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They're literally interfacing with ai.
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AI is a helper for them. They're asking
it questions, they're engaged with it.
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They are already there, right?
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And so what does educating this
next generation of educators
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look like so that they can actually engage
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with young people at that level?
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Because it can't be traditional,
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it cannot be the way you and I learned,
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because the young people, aren't
they, we didn't have the tools.
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We didn't have the tools that they
had. I remember hours in stacks, right,
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in the library.
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Or I remember getting online
and spending hours with Google
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searches, and they're not
using Google searches anymore.
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They go right to the answer and to
the references in a very quick way
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just by knowing how to properly
prompt or do they, right?
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So these are the kinds of things that I'm
trying to see where we are in terms of
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educating the next generation
of educators who have to teach
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to students who have these tools.
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Yeah, no, absolutely. Right? If,
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if we're serious about preparing
students for a rapidly changing world,
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then that means we have to start
with the adults who guide them, and,
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and that's our teachers.
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So modernizing education
begins with modernizing the
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teaching profession in a lot of ways.
And, you know, today's teachers are not,
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they're not just content
experts or deliverers.
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It's a complex professional operating
and dynamic environment. So I think,
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you know, education today and for the
next, uh, generation of educators, uh,
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they're, you know,
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clearly instructional designers because
the content isn't enough and a textbook
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is not really enough.
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They're designing learning experiences
that are integrating many of those
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elements that I, I, I talked about, right?
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Whether it's project-based learning and
then technology tools in a purposeful
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way, or interdisciplinary content
applied right in real world
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problems.
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They have to understand how to scaffold
learning how to potentially use those
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technology tools to
differentiate instruction,
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how to potentially use those
AI tools to develop meaningful
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performance based assessments.
So that's one component of,
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you know, what they're now having to
do in this next generation. But again,
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going back to the data-rich environments
that also have to be data interpreters,
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right? We know that classrooms are
increasingly data-rich environments,
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and teachers have to be able to
interpret assessment results,
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identify learning patterns, and adjust
instruction in real times in many ways.
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So that, that data fluency, it's
not just about spreadsheets,
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it's about instructional decision making.
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The technology component, right?
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They have to be technology integrators.
It's not as an add-on. It's embedded in,
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as you were saying,
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in describing how students learn
and how they work and how they live.
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So teachers need to understand
when technology enhances learning
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and when it distracts from it, you know,
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there have been many
instances where in some cases,
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technologies were integrated in
the classroom. I'm thinking of the,
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the smart board, for example. And then
they sat there as symbols of progress,
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but there wasn't any support in many
cases provided to teachers to take
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advantage of the technology, not
only to enhance teaching practices,
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but to enhance learning outcomes
and to model for students how to use
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technology effectively. So,
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so they have to now know how to
integrate AI tools responsibly and
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how to help maintain academic
integrity while at the same
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time embracing innovation.
And, and that's a balance.
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This is where I, I want to have a,
a more lengthy discussion, right?
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Should our teachers educate our students
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in how to effectively develop
and utilize prompts so that they
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can properly interface and engage with a
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large language model.
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So AI is, is a lot of things,
right? There's a, certainly a,
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a literacy component to it, just as far
as understanding what it is. And it, it,
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it's also a tool in
that it helps them apply
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learning sciences.
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Yeah. But it, but it has a language.
And that's the thing. So, so, you know,
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I tell people all the time,
if you get on your computer,
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you give it a PDF of a paper
or of a book, and you say,
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review this book for me, and give
me, and give me your summary of it.
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I would contend to them that that
is an improper way to use AI,
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right? But it's the way in which people
engage and interact with it, right?
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But they're not really speaking
the language of how the computer,
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which AI is really giving you your
answers based on associations.
308
00:19:05,744 --> 00:19:07,005
It associates the,
309
00:19:07,105 --> 00:19:11,725
the words that you write with
specific sets of other words
310
00:19:12,105 --> 00:19:13,925
and other outcomes that it knows.
311
00:19:14,785 --> 00:19:19,725
So if you don't want it to
hallucinate or give you things
312
00:19:19,955 --> 00:19:23,325
that are really, shouldn't be part
of the question in which you ask it,
313
00:19:23,705 --> 00:19:26,565
you actually need to take care of
that in how you ask it, right? You
314
00:19:28,686 --> 00:19:33,484
need to start to focus the large
language model to a general framework,
315
00:19:34,005 --> 00:19:39,005
a general area that's involved
with the document or that,
316
00:19:39,006 --> 00:19:43,165
that you've given it. You
need to tell it who it is,
317
00:19:43,625 --> 00:19:48,605
so it knows where to pull
prerequisite information to help
318
00:19:48,785 --> 00:19:53,645
it do the identifications that are
necessary to get your answer, right.
319
00:19:53,905 --> 00:19:57,685
So one example is you have a person
do a general prompt. You give them a,
320
00:19:57,744 --> 00:20:00,805
the same book, you have them do a
general prompt where they ask it,
321
00:20:01,045 --> 00:20:04,725
summarize this for me, blah, blah,
blah. And let's say it's on physics,
322
00:20:05,105 --> 00:20:08,045
you know, it's on
electromagnetics. I'm, I'm sorry,
323
00:20:08,105 --> 00:20:10,285
I'm giving you an engineering scenario.
324
00:20:10,286 --> 00:20:10,806
It's, it's okay.
325
00:20:10,806 --> 00:20:12,685
But let's say it's on
electromagnetics and you say,
326
00:20:12,925 --> 00:20:17,405
summarize this book on electromagnetics.
That's one way, another way to say is,
327
00:20:17,984 --> 00:20:22,365
you are the foremost electromagnetics
physicists in the world.
328
00:20:22,715 --> 00:20:27,005
Your research is on blank
relative to electromagnetics.
329
00:20:27,315 --> 00:20:29,484
Take this book, summarize it.
330
00:20:29,595 --> 00:20:34,325
Give me relative feedback with
emphasis on A, D, C, D and E.
331
00:20:35,265 --> 00:20:40,085
I'm gonna get a very different set
of outcomes that I've gotten with
332
00:20:40,086 --> 00:20:42,805
just a straight summarize
this. Yeah. Right?
333
00:20:43,465 --> 00:20:48,244
And because our young people are
gonna be interfacing in dealing
334
00:20:48,275 --> 00:20:52,484
with young people who are gonna be
interfacing with this technology, to me,
335
00:20:52,485 --> 00:20:56,805
it's critical that they know how to do
it. People are gonna use it. So you,
336
00:20:56,905 --> 00:21:00,925
you better learn, they better know how
to use it in the most efficient way,
337
00:21:01,305 --> 00:21:03,484
in the most efficient
mechanism possible. Right?
338
00:21:04,105 --> 00:21:07,925
And so we're still debating
whether it's cheating or not,
339
00:21:08,305 --> 00:21:13,244
and we really should be about how do
340
00:21:13,265 --> 00:21:18,244
you best employ it to give you an
advantage over the other folk who
341
00:21:18,245 --> 00:21:23,125
are still debating whether it should even
be used or not. Right? Because to me,
342
00:21:23,126 --> 00:21:24,244
that ship is kind of sailed.
343
00:21:24,244 --> 00:21:28,845
Oh, absolutely, absolutely. What you
are describing, so I mentioned earlier,
344
00:21:29,145 --> 00:21:31,645
AI is a lot of different things,
right? It can be seen as a tool,
345
00:21:31,646 --> 00:21:36,365
as a career pathway, uh,
as a disruptor. But to me,
346
00:21:36,366 --> 00:21:39,045
you're describing AI as a literacy, right?
347
00:21:39,315 --> 00:21:42,165
It's something that
students must understand.
348
00:21:42,545 --> 00:21:47,205
We teach reading and writing
because literacy empowers agency and
349
00:21:47,785 --> 00:21:51,445
AI literacy is gonna serve
a similar function. Um,
350
00:21:51,805 --> 00:21:56,765
students and educators both need to
understand how AI systems are trained,
351
00:21:57,055 --> 00:22:01,725
where bias can enter,
what hallucinations are,
352
00:22:02,185 --> 00:22:05,525
how to verify an AI generated output,
353
00:22:05,585 --> 00:22:10,405
or what ethical boundaries really
matter as you create your prompt or as
354
00:22:10,406 --> 00:22:15,365
you think about how to engage
with AI and how data privacy works
355
00:22:15,465 --> 00:22:18,605
as well. So without that kind
of literacy, I definitely agree.
356
00:22:18,606 --> 00:22:21,445
Like we risk creating
passive consumers of,
357
00:22:21,465 --> 00:22:26,165
of technology instead of
informed critical users.
358
00:22:27,305 --> 00:22:29,045
You know, we have very,
359
00:22:29,046 --> 00:22:33,925
very highly regarded education programs
here at George Mason from special ed
360
00:22:33,945 --> 00:22:35,244
to education leadership.
361
00:22:36,345 --> 00:22:41,165
And so what makes Mason stand
out as an education institution
362
00:22:41,166 --> 00:22:41,955
in your mind?
363
00:22:41,955 --> 00:22:45,605
Yeah, I think, um, and I mentioned
this a little bit earlier,
364
00:22:45,885 --> 00:22:49,925
I think the fact that we have such
strong ties to our community and our
365
00:22:49,926 --> 00:22:51,325
educational partners,
366
00:22:52,095 --> 00:22:56,484
we're working in real problems of
practice that our school partners see
367
00:22:57,025 --> 00:22:59,925
as, as priorities. One of the,
368
00:23:00,065 --> 00:23:04,244
the really exciting initiatives
that I mentioned our ERA•NOVA
369
00:23:04,994 --> 00:23:09,244
partnership. We're really approaching,
even AI, for example, not,
370
00:23:09,305 --> 00:23:13,165
not from a high perspective, but
working directly with our, uh,
371
00:23:13,166 --> 00:23:17,925
school division leaders to define
what readiness actually means.
372
00:23:19,165 --> 00:23:23,165
Whatever your subject matter is, it's
gonna be relevant a across the different,
373
00:23:23,445 --> 00:23:27,365
uh, content areas of teaching. So
we're asking things like, you know,
374
00:23:27,395 --> 00:23:32,285
what competencies should
teachers have in an AI enabled
375
00:23:32,286 --> 00:23:37,125
classroom? Um, and, and, you
know, responsible classroom
integration look like.
376
00:23:37,365 --> 00:23:41,765
What, what is that? How do we balance
innovation with student safety? Um,
377
00:23:42,945 --> 00:23:46,365
how do we actually even know
whether AI is improving learning?
378
00:23:46,585 --> 00:23:49,045
So one of the things that, um,
379
00:23:49,265 --> 00:23:54,205
we are doing as a result of that
collaboration is identifying very
380
00:23:54,605 --> 00:23:58,805
specifically the kind of skills that we
should be embedding across all of our
381
00:23:58,915 --> 00:24:02,605
educational programs across all of
our teacher preparation programs,
382
00:24:03,275 --> 00:24:06,725
whether it's in special education
or early childhood education,
383
00:24:06,726 --> 00:24:08,085
or secondary education,
384
00:24:08,355 --> 00:24:12,005
because that's just going
to be part of the job.
385
00:24:12,435 --> 00:24:15,765
I've heard some alarmist kind
of warnings that, you know,
386
00:24:16,585 --> 00:24:20,605
AI is going to, uh, eliminate teachers,
and that just simply isn't true.
387
00:24:20,815 --> 00:24:25,565
We've been hearing those concerns
for a long time. We heard it,
388
00:24:25,665 --> 00:24:26,006
you know,
389
00:24:26,006 --> 00:24:29,725
with the radio and the television and
the internet and the cell phones ,
390
00:24:30,475 --> 00:24:34,165
what it's going to do is elevate
the teaching profession, right?
391
00:24:34,806 --> 00:24:39,365
Because if you look at not just the
teaching profession, but all professions,
392
00:24:39,366 --> 00:24:42,965
it is fundamentally changing
the way in which you work,
393
00:24:43,145 --> 00:24:47,605
the actual critical tasks that
are required, how well you do it.
394
00:24:47,984 --> 00:24:50,365
So it is, uh, in my
opinion, going to elevate.
395
00:24:50,366 --> 00:24:54,525
So I think that's one of the things
that's really unique about us.
396
00:24:54,675 --> 00:24:58,445
It's that integration between
research and practice. It,
397
00:24:58,905 --> 00:25:02,125
we don't just stay at
the theory of things,
398
00:25:02,345 --> 00:25:04,885
but we're using research and, uh,
399
00:25:05,125 --> 00:25:10,045
research capacity and theory to work
with our educational partners and
400
00:25:10,046 --> 00:25:13,244
the educational community to,
to address real challenges.
401
00:25:13,825 --> 00:25:17,805
So if I were to ask you
who's actually successfully
402
00:25:18,865 --> 00:25:23,484
making this change and adapting
as you've highlighted here, who,
403
00:25:23,494 --> 00:25:24,845
who's doing that at George Mason?
404
00:25:25,105 --> 00:25:27,205
You mean across our
educational programs or?
405
00:25:27,206 --> 00:25:27,595
Yeah.
406
00:25:27,595 --> 00:25:30,325
Yeah. I, I think I, like
I said, I think we're,
407
00:25:30,335 --> 00:25:33,845
we're all doing it that ERA•NOVA
that research practice partnership,
408
00:25:33,846 --> 00:25:37,405
we have faculty across many programs,
409
00:25:37,406 --> 00:25:41,845
including educational
leadership who are really
410
00:25:42,025 --> 00:25:45,805
vested in working. We have, uh, a
couple of faculty right now. We,
411
00:25:45,825 --> 00:25:47,205
we were successful in, uh,
412
00:25:47,206 --> 00:25:51,085
obtaining a global data sharing agreement
with a couple of our school divisions.
413
00:25:51,905 --> 00:25:56,205
And what we did is we prioritized
the areas of interest of those school
414
00:25:56,206 --> 00:25:56,646
partners.
415
00:25:56,646 --> 00:26:01,445
So we already have faculty
in the college testing out
416
00:26:02,265 --> 00:26:07,205
AI tools to enhance math
instruction and literacy
417
00:26:07,315 --> 00:26:11,045
instruction. And that's huge
because it, it, you know,
418
00:26:11,225 --> 00:26:14,805
it requires for the school division
to have a lot of trust in us.
419
00:26:15,505 --> 00:26:19,165
And so we're, that's just
the, the kind of, I think,
420
00:26:19,395 --> 00:26:22,405
work that we're doing in partnership
with our school divisions to,
421
00:26:22,505 --> 00:26:25,365
to modernize the teaching profession.
422
00:26:25,775 --> 00:26:30,725
These technologies are gonna solve
some significant problems for us.
423
00:26:31,325 --> 00:26:32,365
I, I do believe,
424
00:26:32,945 --> 00:26:37,205
as you highlighted that the teaching
profession isn't going away.
425
00:26:37,835 --> 00:26:42,685
What I caution is stating
that it's not going to have to
426
00:26:42,686 --> 00:26:44,205
radically change, right?
427
00:26:44,984 --> 00:26:49,244
You can interface with a
teacher who understands
428
00:26:49,875 --> 00:26:53,685
many of the great works
of Shakespeare, right?
429
00:26:54,145 --> 00:26:59,045
Or you can interface with
a bot that has read every
430
00:26:59,046 --> 00:27:03,765
great work on any subject
and can correlate it,
431
00:27:03,815 --> 00:27:04,648
right?
432
00:27:05,145 --> 00:27:09,605
And so how does that professor
engage with a student
433
00:27:09,955 --> 00:27:13,885
that has access to that tool,
right? Because in some instances,
434
00:27:14,825 --> 00:27:16,525
the, the, the, the, the tool,
435
00:27:16,665 --> 00:27:20,885
the technology actually has
a greater knowledge base
436
00:27:21,744 --> 00:27:26,525
and is able to synthesize that
knowledge base better than the
437
00:27:26,526 --> 00:27:30,685
professor. The tool
itself has the ability to
438
00:27:32,215 --> 00:27:36,125
synthesize and bring
information together. And, and,
439
00:27:36,484 --> 00:27:38,285
and for lack of a better
way of saying this,
440
00:27:38,286 --> 00:27:39,845
and almost like a human-like manner.
441
00:27:40,425 --> 00:27:45,285
So we have to teach people
how to find their place
442
00:27:46,145 --> 00:27:47,445
in that environment.
443
00:27:48,185 --> 00:27:52,005
And I think that that's
critical and non-trivial, right?
444
00:27:52,565 --> 00:27:55,405
I know we have people thinking
about this and working on this here.
445
00:27:56,225 --> 00:28:00,845
Do you have some examples of any
programs that are utilizing that?
446
00:28:01,845 --> 00:28:05,765
I guess I would kind of take
us a little further back.
447
00:28:06,355 --> 00:28:10,845
It's not about content, right?
The role of an educator.
448
00:28:11,545 --> 00:28:16,045
It requires that human judgment. We can't
compete with the knowledge generation,
449
00:28:16,145 --> 00:28:18,285
the analysis, in some
cases, the synthesis,
450
00:28:18,305 --> 00:28:20,525
but that's not the value
of an educator, right?
451
00:28:21,234 --> 00:28:25,685
It's really that human connection.
It's that mentorship, it's discernment.
452
00:28:26,515 --> 00:28:31,285
It's very subtle art of recognizing
when a student is struggling.
453
00:28:31,835 --> 00:28:33,605
It's the human connection.
454
00:28:33,905 --> 00:28:38,205
It is the helping to love to learn,
455
00:28:38,305 --> 00:28:40,765
to engage with learning
on an ongoing basis.
456
00:28:42,065 --> 00:28:47,005
That's the challenge is right now,
we're, and you know, lots of folks are,
457
00:28:47,025 --> 00:28:48,285
are talking about this. We're,
458
00:28:48,535 --> 00:28:53,365
we're educating students for a world
that we probably can't even imagine.
459
00:28:53,905 --> 00:28:55,565
No, that's right. Right? But,
460
00:28:55,585 --> 00:29:00,245
but I contend to you that we've always
educated young people for worlds that
461
00:29:00,246 --> 00:29:01,685
they could not imagine. Right?
462
00:29:02,365 --> 00:29:07,325
I remember we were educating
people in the early and mid-2000s
463
00:29:08,425 --> 00:29:13,245
for an explosion of
wireless and internet of
464
00:29:13,246 --> 00:29:18,205
things based technologies
that hit long before these
465
00:29:18,206 --> 00:29:22,125
young, we didn't know what those
technologies were gonna look like, right?
466
00:29:23,825 --> 00:29:27,725
But we graduated young people who can
interface and, and engage with them.
467
00:29:27,945 --> 00:29:32,845
And so I think you're hitting the
nail right on the head with this whole
468
00:29:32,895 --> 00:29:33,728
piece
469
00:29:34,745 --> 00:29:39,725
of leaning into that human
connectedness part, right? My,
470
00:29:40,065 --> 00:29:42,285
the best teachers, uh,
471
00:29:42,425 --> 00:29:45,405
the best teachers that I've
had throughout my career
472
00:29:47,075 --> 00:29:49,285
have been people who could do that, right?
473
00:29:49,905 --> 00:29:53,405
Who could look at you and see your
strengths in your development cycle,
474
00:29:53,545 --> 00:29:57,485
who could see your weaknesses, right?
And they didn't do that by, uh,
475
00:29:57,725 --> 00:30:01,365
a test per se. They
did this by discerning,
476
00:30:01,475 --> 00:30:05,765
they did this by watching
you engage and seeing,
477
00:30:06,745 --> 00:30:10,085
you know, it could be where you stopped
your pencil as you were writing.
478
00:30:10,305 --> 00:30:14,405
It could be the look that was on your
face as you were engaging, right?
479
00:30:14,985 --> 00:30:19,845
It could just be the feeling
that they got from engaging
480
00:30:19,955 --> 00:30:24,605
with you on a specific issue
or on a specific problem,
481
00:30:24,735 --> 00:30:29,005
right? Those pieces are, in my opinion,
482
00:30:30,085 --> 00:30:30,918
uniquely human.
483
00:30:30,945 --> 00:30:31,745
That's right.
484
00:30:31,745 --> 00:30:33,165
And we have to figure out
485
00:30:34,695 --> 00:30:39,195
how to emphasize them
and lean into the tools.
486
00:30:39,335 --> 00:30:40,168
That's right.
487
00:30:40,395 --> 00:30:41,275
You, you, you get what I mean.
488
00:30:41,715 --> 00:30:42,185
Absolutely.
489
00:30:42,185 --> 00:30:44,475
That is the solution.
That's, that is, or at least,
490
00:30:45,335 --> 00:30:47,075
that's the solution right now, .
491
00:30:47,435 --> 00:30:49,115
Right? That that's right. We,
because don't be because we.
492
00:30:49,275 --> 00:30:49,956
Don't know what the
future's gonna look like.
493
00:30:49,956 --> 00:30:51,875
That's right. We, we don't know
what the new thing will be.
494
00:30:52,295 --> 00:30:55,955
And so regardless of the
change and the, regardless of,
495
00:30:56,415 --> 00:30:58,235
of the tools that come along, right?
496
00:30:58,265 --> 00:31:02,675
What we're really trying
to promote is adaptability.
497
00:31:03,375 --> 00:31:07,195
And again, change is always, it,
it's only accelerating, right?
498
00:31:07,196 --> 00:31:10,635
So we don't have the luxury of
looking away and saying, well,
499
00:31:10,636 --> 00:31:12,875
I don't like technology and
I don't like the AI thing,
500
00:31:12,876 --> 00:31:16,075
or whatever the technology might be. And
just say, well, I'm not gonna engage.
501
00:31:16,695 --> 00:31:18,195
The world has moved on, right?
502
00:31:18,375 --> 00:31:22,355
So I think one of the critical things
that is gonna be really important for
503
00:31:22,795 --> 00:31:23,295
educators and,
504
00:31:23,295 --> 00:31:28,035
and educational systems
is to promote the ability
505
00:31:28,095 --> 00:31:32,075
for students to engage
in lifelong learning and
506
00:31:32,315 --> 00:31:36,835
adaptability 'cause that is always
going to be a constant requirement.
507
00:31:37,095 --> 00:31:42,075
So let me ask you this, because
you, you clearly are, uh,
508
00:31:42,135 --> 00:31:46,915
as an educator, you're gonna have
to deal with humanist on the,
509
00:31:47,055 --> 00:31:51,755
the ethical values of what you teach
and what you don't teach, right?
510
00:31:52,095 --> 00:31:57,075
And so how can classical liberal
arts education evolve to meet the
511
00:31:57,076 --> 00:32:02,035
needs of these 21st century students
and workers and employees and employers,
512
00:32:02,036 --> 00:32:02,535
right?
513
00:32:02,535 --> 00:32:07,315
How do we evolve the classical liberal
arts framework in order to meet that
514
00:32:07,385 --> 00:32:08,218
need?
515
00:32:09,065 --> 00:32:12,475
Yeah. I, I think, you know,
it's just as important as it's,
516
00:32:12,475 --> 00:32:16,035
as it has always been.
Um, I think, you know,
517
00:32:16,135 --> 00:32:20,995
we want to, um, leverage,
you know, the logic,
518
00:32:21,255 --> 00:32:26,235
the logical reasoning that comes
from, from philosophy and, you know,
519
00:32:26,335 --> 00:32:30,435
the history, uh, patterns
right across history.
520
00:32:31,215 --> 00:32:34,235
So I, I think they're just
as relevant as before,
521
00:32:34,295 --> 00:32:38,355
but I think like everything else,
it has to evolve and we have to do,
522
00:32:39,365 --> 00:32:43,365
uh, a better job of applying
those insights, right? Like to me,
523
00:32:43,366 --> 00:32:44,525
liberal arts as,
524
00:32:44,545 --> 00:32:49,405
as someone who navigated philosophy
and English and psychology, uh,
525
00:32:49,406 --> 00:32:50,365
in my undergrad,
526
00:32:50,845 --> 00:32:55,365
I have found those skills
to be so critical to
527
00:32:55,375 --> 00:32:57,845
everything I do. And so I,
528
00:32:58,125 --> 00:33:02,125
I think it's just making sure that we're
taking it a step further and that we
529
00:33:02,126 --> 00:33:05,885
are using the liberal arts
in a way that's applied,
530
00:33:05,985 --> 00:33:10,805
and that is clearly relevant. I, I
think it's relevant, but as educators,
531
00:33:10,845 --> 00:33:14,685
I think we need to do a better job of,
of making that connection. But, you know,
532
00:33:14,705 --> 00:33:19,565
as I said, again, this whole idea
of, uh, critical thinking, um,
533
00:33:19,945 --> 00:33:23,525
and, uh, collaboration and insight,
534
00:33:24,055 --> 00:33:27,485
those are all things that I
think our liberal arts are,
535
00:33:27,665 --> 00:33:29,845
are really good at helping us develop.
536
00:33:30,545 --> 00:33:33,125
If you were talking to a
young person right now,
537
00:33:34,405 --> 00:33:39,205
somebody just graduating out
of high school and entering
538
00:33:39,315 --> 00:33:42,565
into the profession, you
say, I want to be a teacher.
539
00:33:43,325 --> 00:33:46,925
Teachers really impacted
me my entire life.
540
00:33:47,385 --> 00:33:51,125
And that's where I see myself having
the greatest impact as a human.
541
00:33:52,025 --> 00:33:54,285
And that young person was looking at you,
542
00:33:55,355 --> 00:34:00,085
what are three things you would
tell that person to make sure you do
543
00:34:00,145 --> 00:34:04,485
now while you're going through your
educational framework in order to make you
544
00:34:04,525 --> 00:34:07,205
a, an effective teacher going forward?
545
00:34:08,205 --> 00:34:12,285
I definitely think that
I would ask them to
546
00:34:12,975 --> 00:34:15,045
model adaptability, right?
547
00:34:15,185 --> 00:34:18,925
To make sure that as you
enter the teaching profession,
548
00:34:19,075 --> 00:34:22,645
that you're aware that students are also
looking at you and how well you embrace
549
00:34:23,045 --> 00:34:27,605
change. So I think that's one
critical thing. Also, this idea that,
550
00:34:27,606 --> 00:34:31,445
that I mentioned before around
problem-based learning is really critical.
551
00:34:32,145 --> 00:34:35,525
The world needs problem solvers, right?
552
00:34:36,075 --> 00:34:41,005
Ethical problem solvers that
regardless of the workplace or context
553
00:34:41,465 --> 00:34:44,525
can work with others to
solve complex problems.
554
00:34:44,545 --> 00:34:49,325
And so embedding that in the learning
environment and in the learning
555
00:34:49,555 --> 00:34:52,805
experiences is, is really critical. So I,
556
00:34:52,885 --> 00:34:56,325
I think those are some of the critical
things that I would make sure that they
557
00:34:56,326 --> 00:34:58,725
know is, is essential
for an effective teacher.
558
00:34:59,055 --> 00:35:02,725
Given where you sit as a leader
and an administrator, right?
559
00:35:03,105 --> 00:35:06,285
And you're leading now cohorts of faculty,
560
00:35:06,355 --> 00:35:11,245
what do you tell them
about how this disruption
561
00:35:11,905 --> 00:35:14,045
that's coming from AI, this,
562
00:35:14,114 --> 00:35:18,165
this change that's
coming to the profession,
563
00:35:18,915 --> 00:35:23,645
what do you tell them about what they
should be doing right now to adapt and
564
00:35:24,305 --> 00:35:28,605
to coexist with these technologies as they
565
00:35:28,985 --> 00:35:29,815
evolve?
566
00:35:29,815 --> 00:35:32,965
Experiment, right? I think
one of the things that,
567
00:35:32,966 --> 00:35:35,405
that we're working on in
the college is to have,
568
00:35:35,665 --> 00:35:40,645
or to develop an AI and other kind of
emerging technologies tinkering lab
569
00:35:41,175 --> 00:35:45,805
where people are in an environment
where they can explore and they can
570
00:35:45,806 --> 00:35:49,085
tinker and they can try out
tools, whether it's with, uh,
571
00:35:49,086 --> 00:35:53,125
with fellow educators or,
you know, a space for other,
572
00:35:53,265 --> 00:35:55,445
for educational leaders as well.
573
00:35:56,114 --> 00:35:59,245
There's on both ends of the
spectrum in some, in some cases,
574
00:35:59,445 --> 00:36:02,364
a lot of fear about safety and
the implications of using it.
575
00:36:02,365 --> 00:36:05,045
And then the other hand, very eager, uh,
576
00:36:05,155 --> 00:36:09,045
folk who want to use it and think it's
the tool for all the, the problems.
577
00:36:09,665 --> 00:36:13,725
And so I think just having
that community space for
578
00:36:14,325 --> 00:36:18,965
educators to explore, to experiment, to
ask questions, to break things, to say,
579
00:36:18,966 --> 00:36:21,364
well, what happens if we do this? And,
580
00:36:21,465 --> 00:36:24,725
and to make that part of
the learning experience,
581
00:36:24,844 --> 00:36:28,765
I think that's only going to reduce
the fear and anxiety of the unknown.
582
00:36:29,555 --> 00:36:31,245
Well, this is all good stuff,
583
00:36:31,505 --> 00:36:35,325
and the kind of thing that
positions us well for the future.
584
00:36:35,835 --> 00:36:38,805
What do you tell your
fellow deans, you know,
585
00:36:38,806 --> 00:36:42,765
some of which are really
struggling with this technology,
586
00:36:42,945 --> 00:36:46,844
and you are kind of at the forefront of
it, because outside of computer science,
587
00:36:46,844 --> 00:36:49,565
it probably affects your
discipline more than any other.
588
00:36:50,045 --> 00:36:53,765
Yeah. I mean, we certainly talk, uh,
589
00:36:53,965 --> 00:36:56,205
I think as leaders often about, you know,
590
00:36:56,305 --> 00:36:59,085
how the implications of
AI in the university and,
591
00:36:59,105 --> 00:37:02,844
and of course the workplace
as well. I, I think, you know,
592
00:37:02,845 --> 00:37:07,605
what I would reiterate with my
colleagues is that there is no one area
593
00:37:07,606 --> 00:37:11,885
that isn't impacted by
the shifts in technology,
594
00:37:11,886 --> 00:37:16,485
whether it's AI or whatever
comes after every single
595
00:37:16,864 --> 00:37:19,285
career, every single sector,
596
00:37:19,775 --> 00:37:24,605
every single space and community is being
impacted by technology in one way or
597
00:37:24,606 --> 00:37:25,439
the other.
598
00:37:25,625 --> 00:37:30,605
And so we have a responsibility
to understand if that's
599
00:37:30,875 --> 00:37:34,205
already changed our communities, and
it's gonna change it even further.
600
00:37:35,305 --> 00:37:39,405
How do we adapt the preparation that we
provide those students during the time
601
00:37:39,406 --> 00:37:44,205
they're with us to make sure that
they're capable and ready to shape and
602
00:37:44,255 --> 00:37:46,364
contribute in that kind of world?
603
00:37:47,265 --> 00:37:51,205
That's it. Well, we're gonna
have to leave it there. Ingrid,
604
00:37:51,975 --> 00:37:56,885
thank you for sharing your
vision and leadership with the
605
00:37:57,165 --> 00:37:58,645
educators of our future.
606
00:38:00,305 --> 00:38:04,685
I'm George Mason president Gregory
Washington. Thanks for listening.
607
00:38:05,785 --> 00:38:10,005
And tune in next time for more
conversations that show why
608
00:38:10,585 --> 00:38:13,685
we are all together different.
609
00:38:16,225 --> 00:38:17,645
If you like what you
heard on this podcast,
610
00:38:18,065 --> 00:38:22,565
go to podcast.gmu.edu for
more of Gregory Washington's
611
00:38:22,566 --> 00:38:25,005
conversations with the
thought leaders, experts,
612
00:38:25,265 --> 00:38:29,885
and educators who take on the grand
challenges facing our students, graduates,
613
00:38:30,085 --> 00:38:33,885
and higher education.
That's podcast gmu.edu.
