Latest / Integrate This! Ed Tech Podcast / A Lifelong Love of Learning | Dr. Nneka McGee on AI, Ethics & Teaching with Heart

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A Lifelong Love of Learning | Dr. Nneka McGee on AI, Ethics & Teaching with Heart · Integrate This! Ed Tech Podcast

0:00
Welcome to Integrate This, your go -to edtech
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podcast where curiosity meets classroom innovation.
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Join your hosts, David Berner and Jeremy Mikla,
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as we explore the rapidly evolving world of educational
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technology. From game -changing tools to insightful
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conversations with today's top edtech voices,
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we're here to help educators stay informed, inspired,
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and ready to innovate. So tune in, level up,
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and let's integrate this. Hey, welcome to the
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Integrate This EdTech podcast. I'm David Berner,
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joined by co -host Jeremy Mickela. And today,
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our special guest that we have with us is Dr.
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Naka McGee. Very excited to have you join us.
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There's a ton of cool concepts that we became
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aware of through the resources and things that
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you have available and a lot of the work that
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you've done. So we're super excited to talk with
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you. And do you mind just telling us a little
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bit about kind of kicking things off and telling
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us about How did you get to this point before
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this podcast? Everything leading up to that.
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Volume one. First, I am so excited to be a part
1:10
of this podcast, and I appreciate you both so
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much for, you know, the invite in terms of, you
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know, I'll keep it as short as possible, you
1:20
know. you know in Ohio when you know by birth
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um and you know ended up both my parents were
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mathematicians and so start there and I my mother
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was an administrator at the Ohio State University
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College of Engineering back then the computers
1:39
were huge but I wanted one and so um they for
1:44
my birthday, you know, I know I'm telling my
1:47
age, but I had a IBM 5155, 27 pound personal,
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it was supposed to be a portable computer. They
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had a big blue bag and I used to lug that thing
1:58
around. But back then you had the no basic and
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you had to know the code. And so I learned the
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code and really for, you know, had 11 computers.
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Just so happens that I ended up teaching, you
2:09
know, math. And because of the way that I learned
2:14
best, which was to have just a lot of activity,
2:18
learning about a lot of new things. That was
2:21
the type of learning I wanted to share with my
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kids when I was in the classroom. And it brought
2:26
me back to computers. I mean, when I was, I wasn't.
2:30
a school where I set up the computer lab. I had
2:34
the switches. It was, you know, all the things.
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And so I ended up bringing that to my kids. And
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so we used to think of lessons and it came back
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to first things like RSA encryption. And I can't
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tell you all the crazy things, but I just started.
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um doing work with artificial intelligence just
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stemming back from in the 80s a lot of times
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people say like Terminator and things like that.
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Well, my thing was kit, you know from the knight
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rider and things like that I was so excited and
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just because I started doing the work I You know
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ended up like hey, I should you know, try to
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get a doctor, you know Do my doctoral program
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in ai education? Uh, this was before chad gbt
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came out and actually um two weeks, uh after
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I had my IRB approval is when CHAT GPT arrived
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on the scene. So that was interesting. It was
3:27
interesting because I had been in a position
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to, I was a teacher. I had been an administrator.
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I had started two initiatives, AI initiatives
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in two different districts before CHAT GPT came
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out. And because of that experience, I was able
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to help and support other districts, other educators
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and institutions who are navigating the AI education
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space. And that leads me here to you today. Awesome.
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And you've been really involved with a lot of
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the different things that over the last three,
4:02
four years or so with different conferences and
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really highlighting a lot of the AI work that
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you've done. What's that experience been like
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for you at, you know, given your background and
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your love for this kind of work? What was it
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like when you started to really dig into AI over
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the last couple of years? Well, it's been interesting
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seeing kind of being a part of the world, the
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AI education world before ChatGPT and seeing
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it after ChatGPT. I remember being a part of
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a panel at ISTE in 2022, and it was about AIs
4:43
and emerging technologies. And the individuals
4:46
who I was on the panel with, we laughed because
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our heads, we were like, our heads were big.
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We thought we were doing something and we like
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knew nothing. You know, I knew about like, you
4:55
know, the periphery, right? Like I knew about
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GPTs, you know, things like that in the periphery.
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But none of us had any idea, like, the speed
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and the magnitude of which it was going to hit.
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And so, you know, starting out, I was like a
5:12
kid in a candy store. You know, you have to think
5:15
about this has been, you know, something I was
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interested in, you know, doing a lot of work
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and doing these initiatives. And so it was like,
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wow, this is great. The other part of it is,
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is that I also because the doctoral work and
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had it, you know, started these initiatives.
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I was also very cautious. And so that actually
5:35
surprises people when they meet me because I
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was like one who, oh yeah, we're banning chat
5:40
GPT in my district. I was the chief academic
5:43
officer at the time and people were like, we
5:44
thought you were all in and it had nothing to
5:47
do with cheating and everything at that time
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to do with, you know, terms of service. And I
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would say, are y 'all reading the terms of service?
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Are y 'all really looking at the implications?
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And so that part has been interesting because
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the things Some of the things that we were doing,
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you know, pre November 2022 is like coming full
6:05
circle. People are starting to think about. the
6:08
ethics more, right, of the thing. People are
6:11
kind of circling back to like the pedagogical
6:14
implications of, you know, artificial intelligence.
6:18
And so that's great, right? And we want to see
6:22
that. But I think that has been the biggest thing
6:24
is like, yes, I've been a kid in candy store.
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I'm gonna tell you the excitement. So I forgot
6:28
the other part of my background. that I want
6:30
to share because I'm a big Star Wars fan. So
6:34
I was so excited. This is how I felt, getting
6:37
that ticket a couple weeks ago. If you know,
6:42
you know. That's how exciting it's been. This
6:46
is great. And I feel blessed to be able to contribute.
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If you have told me back in 2018, That, you know,
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I would be in this place due to just something
7:01
that I loved and just something I'm just working,
7:03
you know, with kids with math. I would have been
7:06
like, yeah, whatever. Oh, it's exciting. Good
7:11
work and happy to contribute. Yeah, that's great.
7:14
And as as you've kind of gone around and you've
7:17
spoken with district leaders, I know you mentioned
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your background. As chief academic officer and
7:23
things like that as as these changes have occurred
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Seeing AI as an emerging technology Have you
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what is like where you're at currently today?
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What is kind of your? Assessment of the landscape
7:39
with where schools are at and I know like it's
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tough because everybody's in different spots
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And they've got you know they're approaching
7:45
it in different ways But what's just your first
7:47
kind of instinct about where we're at right now?
7:50
For schools. Yeah. Yeah. No, thank you for the
7:54
question My first instinct is that I don't see
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AI as an emerging technology. I see generative
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AI as an emerging technology and You know AI
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I always talk about how for an educator, and
8:10
particularly when I'm talking with leaders, their
8:12
first interaction with artificial intelligence
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in a school will not be generative AI. It will
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most likely be in computer adaptive test. And
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so that's part of, you know, what I try to bring
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to the table is that not only, you know, is artificial
8:28
intelligence decades old, but so is artificial
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intelligence in education. And so I always kind
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of, and that's been one of the biggest um kind
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of things I want to make people aware of not
8:43
for any other reason that I hope it makes people
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feel better and less afraid that that people
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have been working on this you know there's a
8:51
um conference in an organization who's been around
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since 1989 I believe and they're specifically
9:00
dealing with this um role so what I that that's
9:03
the kind of awareness I try to bring to the table
9:05
it's like Okay, let's connect artificial intelligence
9:09
with the things that are already in educational
9:13
environments so that you see it's not this big
9:16
scary thing, it's something that you've been
9:18
using. And now let's look at the implications
9:22
of things like generative AI, because we can't
9:25
shy away from the fact that it is here and it
9:30
is very disruptive. And so that is a balance,
9:34
but I think it's an important balance. And in
9:37
a minute, I'm going to share with you a quote
9:39
that I think is so interesting from, you know,
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just this whole kind of, you know, technological.
9:50
There's this quote I love to share, and it's
9:52
the technologies of artificial intelligence,
9:55
including the ability to process natural language,
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have the potential to bring tools to the classroom
10:01
that will revitalize education. And we were like,
10:03
oh, that's a great quote. And I'm like, yeah,
10:05
that's from 1989. We were like, what? And I'm
10:10
like, yes. And it's great that it's taking time,
10:14
because I want people to be able to say, you
10:16
can breathe, yes? It is transformative. It is,
10:20
you know, we have to, you know, kind of rush
10:22
to get some things on the table, but it's also
10:26
OK to step back and do it the right way because,
10:31
you know, that is essential for our kids. Yeah,
10:35
I just when I listen to you, you give that quote,
10:39
I'm reminded back to a movie from the 80s that
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I really loved at that time, Real Genius. Um,
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and I could just see like the really smart people
10:50
in the room all getting together and they're
10:52
doing all of these great things with their algorithms
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and they're using it to, you know, have a big
10:57
party on campus or, or using it to develop these
11:00
lasers that are going to like blow up the world
11:02
or something, you know, like, so there's, there's
11:04
that ethical line here that you were, you were
11:06
discussing too, that is definitely part of it,
11:08
but also that idea that it can be very transformative
11:11
when it comes to the education space. Um, which,
11:14
you know, when we think about it here, As we
11:18
pivot a little bit from just AI in general to
11:21
the generative AI in education, where do you
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think teachers most often get stuck when it comes
11:30
to wanting to use AI? Is it because of time constraints?
11:34
Is it a confidence issue, an unfamiliarity issue
11:37
like you touched on a little bit? Or just the
11:40
fear that if they get it wrong, they're going
11:42
to blow up the planet? So all of the above. I
11:47
am still amazed, but even now, cheating and plagiarism,
11:53
basically academic integrity is the biggest driver
11:57
of why educators are hesitant to use chat GPT
12:03
and other forms of generative AI in their classrooms.
12:08
The other part of it is the training. If you're
12:12
in the ecosystem, you would think that everyone
12:15
is all AI all of the time. But there are still
12:20
so many districts that have not even initiated
12:25
artificial intelligence programs. And so those
12:30
two factors, and if you think about educators,
12:32
we don't wanna present things to our kids if
12:35
we do not have the familiarity. And we definitely
12:38
don't wanna introduce things to kids if we think
12:42
they're going to use it in ways that are not
12:45
appropriate. So those two factors are really
12:49
driving some of the hesitation. And then lastly,
12:52
it's just the unfamiliarity. I mean, I've mentioned
12:55
this several times, but most recently I was talking
12:59
to leaders and someone was like, yeah, we're
13:01
not ready for the devil's tech. And I was just
13:03
like, yeah, I'm going to. you know, if that's
13:06
your association, we're gonna revisit at another
13:11
time. And then the larger implications is definitely
13:16
policy. And so it's very difficult. for education
13:22
leaders, and I consider teachers to be leaders
13:25
in their classrooms as well. But states, many
13:29
states still don't have policies. They'll have
13:32
guidelines or here's a one pager to kind of set
13:36
you on your way. But policy takes a lot of time.
13:39
And that's the other kind of myth is like when
13:41
you hear AI policy and people are like, yeah,
13:44
do AI policy in a day. And it's like. You mean
13:49
year one, year two, year three? So again, it's
13:53
okay that it's taking time. We need to be very
13:56
careful, but at the same time recognize that
13:59
those, you know, the implications for our kids
14:02
are urgent. So given those constraints, those,
14:07
you know, things where teachers are feeling less
14:10
confident about, you know, what is something
14:12
that, you know, you could tell to a teacher that,
14:15
you know, And I'm going to give you a time constraint,
14:17
right? That within the next 30 days that they
14:21
could do to realistically help support the learning
14:23
that they're providing for their students. So
14:27
I know this is crazy, but I always tell people
14:31
to have a conversation. But I back it up with
14:34
research from John Hattie, Invisible Learning.
14:37
And what Hattie tells us and the research tells
14:40
us is that effective questioning and discussion
14:43
have an effect size. So he had a baseline effect
14:46
size of 0 .4. And so effective questioning discussions
14:50
is like 0 .42 and 0 .80. So what that's implicating
14:59
is a year to two years growth just from questioning
15:03
and I think we've lost the art in some ways of
15:07
conversation and questions as a vehicle for driving
15:11
understanding and so I always say you can go
15:15
into a classroom you can even reflect on your
15:18
own you can talk with your own kids if you have
15:22
children to say What do you think about artificial
15:25
intelligence? What does that mean to you? And
15:29
there is so much learning that can happen from
15:32
a simple question that that is the way I say
15:35
is the is the best entry point. This research
15:38
backed, you know, just talk. Right. And so that
15:43
kind of, you know. reminds me of almost like
15:46
a Socratic seminar that you're that a teacher
15:48
could be conducting with their students, but
15:50
you just you invite the AI into that Socratic
15:54
space so that those conversations in the in the
15:57
continued questioning like you're talking about
15:59
can continue to take place. Yes. That's it. Yeah,
16:06
OK, very simple. Well, that to me, that seems
16:10
like a strategy a teacher could take even tomorrow.
16:13
and implement it with whatever grade level with
16:15
whatever content area that they're dealing with.
16:18
Yeah. What do you how do you think? And maybe,
16:21
yes, they might do a little background and say,
16:24
you know, if I'm teaching, well, you know, my
16:27
my lens is math. But, you know, how do you think
16:30
artificial intelligence relates to mathematics?
16:34
Or, I mean, even broader, how do you think impact
16:36
the AI is impacting your life right now? Where
16:39
do you see AI, you know, in your environment?
16:43
Just such rich, I have had the best learning
16:47
even before AI, when I've had conversations and
16:51
really had those questions, like you said, Socratic,
16:54
very powerful method. So one thing that I was
16:56
gonna ask you about that I found really interesting
16:58
on your website is this concept of it starts
17:03
with a plate. And so I wanted, could you kind
17:06
of explain how this is a... It's a really good
17:11
entry point for young learners, but also it can
17:13
be used with adults to to help understand where
17:18
to start with AI literacy and learning about
17:20
AI. Can you kind of explain that? It starts with
17:23
the plate concept. Yes, it's actually one of
17:25
my favorite activities and it does. It works
17:28
with all ages and it started with a mistake,
17:31
but a happy mistake. I was actually looking for
17:36
a. Image. And this is old Dolly. And I was just
17:42
like, hey, I need two eyes, a nose, a face. I'm
17:47
doing a paper plate. And it came back, and now
17:51
like the rest of the story, like Paul Harvey.
17:54
So basically what it is is like, first of all,
17:59
this powerful plate with a set of markers, and
18:01
you ask your audience or your kids to follow
18:06
those instructions. You start, draw eyes, draw
18:09
a nose, draw a mouth, and then always ask to
18:14
hold them up. What do you see? What do you notice?
18:17
Again, questioning. They all look different.
18:20
Some have bigger eyes, some have smaller eyes.
18:23
And so I say, what do you think would happen
18:26
if you put all of these plates together and trained
18:31
a machine? on what a drawing a plate with a face
18:37
looks like. And so you go from there. And then
18:40
I put up the picture of what happened when I
18:43
initially entered this in. And it's a true story.
18:45
I wasn't starting to say this will be a lesson.
18:49
It just, when it came up, I was like, I have
18:50
to use this because the image does not have a
18:53
nose. And it's like, it has the exact same district.
18:56
I just did a screenshot. And it's just the perfect
19:00
lesson to say, first of all, humans have to be
19:03
in the loop. because if you didn't check, you
19:07
would think, hey, you know, the computer knows
19:10
what to do. So I don't have to worry. So you
19:13
need the human in the loop. That, you know, generative
19:18
AI deals, it is a probabilistic system, right?
19:23
It is not, you know, magical, it's math. And
19:27
so with that, you know, there may be instances
19:30
where different things come up. So you can have
19:33
that part of the lesson. In addition, depending
19:35
on what audience I'm dealing with, I also say,
19:37
what if I took your plates without permission
19:40
and did the same thing? How would you feel if
19:42
I took your creation and, you know, used it for
19:47
my programming? That's another layer of conversation.
19:50
So one simple plate, a happy accident has led
19:53
to a very enriching activity that, and I do,
19:58
I say you can do this tomorrow. Anyone can go
20:00
grab a stack of plates and most teachers have
20:03
markers somewhere or can find them. And again,
20:07
lead with discussion. Yeah, and it's really great.
20:10
I really like the concept of like removing the
20:13
technology for a little bit. and let's just do
20:15
this activity together. And this will help us
20:18
understand the concepts that we're dealing with
20:20
when we actually do get over to the computer
20:22
and start dealing with these large language models.
20:24
That's just a really unique way of doing that.
20:27
So I know many of you may be listening on the
20:29
podcast, but I'll make sure that we have the
20:31
resource for the it starts with a plate from
20:34
your website in there, because it's really cool
20:35
to check out. But as far as when you when you
20:40
start to look at like how we communicate these
20:42
concepts with. when we get to talking about students
20:45
and AI literacy and some of these ideas that
20:48
could be utilized. What do you think usually
20:52
with where we're at right now, what's the best
20:56
entry points for maybe like curriculum coordinators
21:00
to start to encourage their teachers to build
21:04
in some of these foundational concepts into?
21:07
There into their curriculum for building up a
21:11
readiness at those younger levels what do you
21:13
think the best way to do that is or maybe what
21:16
are two or three. Concepts or routines that they
21:20
should just start to build in. Thank you for
21:24
the question. Are you specific to, are you saying
21:28
if I'm a curriculum coordinator, how should I
21:31
be planning for our teachers to teach AI literacy?
21:35
Are you just looking for specific ideas that
21:39
they could use with their teachers to encourage
21:43
them to integrate AI literacy? Yeah, so I think
21:49
really any ideas that you might have because
21:51
the one thing that has been coming up in in our
21:54
circles is we we've done digital citizenship
21:57
citizenship for a long time and a lot of times
21:59
that those those concepts and things can get
22:02
overlooked So is there is there ways that you
22:05
see AI where we can? not just treat it as a standalone,
22:09
but What are some good ways to build it in? Maybe
22:12
just more specifically focusing on some of those
22:14
younger grades, like the plate idea or things
22:17
like that. What are the most essential concepts
22:20
that we should be teaching them so that they
22:22
can just grow in their literacy at a younger
22:25
age? Right. So thank you. So the first thing
22:29
that I'll say is using the actual technology
22:33
terminology is important. So even with the littlest
22:39
learner, I'm going to say artificial intelligence.
22:41
Now, when I asked them to define it, they're
22:43
going to say robot, but you still use the exact
22:48
terminology. And depending on, and I think this
22:53
was a great point that you brought up. It is
22:57
essential that I don't think that AI literacy
23:01
is necessarily very separate from digital literacy
23:06
and media literacy. And I think because like
23:12
you said, they overlap. And actually, I think
23:14
people would be more comfortable if we incorporate
23:18
it as part of digital literacy, as opposed to
23:22
something separate, just because there is so
23:25
much overlap. So that's one thing for young kids.
23:31
I have to tell you. I am a big proponent of hands
23:35
-on activities. Because starting with things
23:41
like FERPA, like COPPA in particular, and SEPA,
23:48
and because generative AI is the emerging technology,
23:53
we don't know enough about the technology. very
24:00
hesitant to recommend it for younger students.
24:05
However, that doesn't mean that they cannot become
24:08
aware and learn terminology. So with that being
24:13
said, I am a big proponent of hands -on activities
24:16
and for younger students to gain an awareness
24:19
of things like artificial intelligence, the terminology
24:22
itself. where they see artificial intelligence.
24:26
Again, you talk about those distinctions. I think
24:29
it's important not that young kids know specifically
24:35
like the different types of artificial intelligence,
24:38
but just in particular that there are different
24:41
types because you don't want a student regardless
24:45
of age, to think that artificial intelligence
24:48
is just generative AI. They're more likely in
24:53
the home to encounter a recommender system or
24:56
in what I call an AI related system such as machine
25:00
learning. And it's so interesting because if
25:03
you asked someone who dealt with like machine
25:06
learning or computer vision or natural language
25:08
processing, which I think is okay to talk about
25:12
these things, but most people who do that work
25:14
do not consider themselves necessarily to be
25:16
working in artificial intelligence. They say,
25:18
I work in computer vision. Those distinctions
25:21
why it seems like, well, why would we discuss
25:23
those things with young kids? And it's so we
25:26
don't end up with misconceptions when they really
25:28
do get into the work and what they're calling
25:31
artificial intelligence may be a machine learning
25:34
system. Does that make sense? Just talking with
25:38
them and creating activities around those distinctions.
25:43
I think so and I think like it's interesting
25:46
to hear you to mention that you know call them
25:49
what they are because we've we've had conversations
25:53
with other people that have been very much like
25:55
well with your littles if you need to just call
25:58
AI computers just call them computers but to
26:03
what you're saying is they need to understand
26:05
it a little bit better and maybe beyond what
26:08
is just a computer that you know you can word
26:10
process with or that you know or when you know
26:14
even just like a mobile device but you know broader
26:17
than that you need they need to understand some
26:19
of the the ideas behind what people are using
26:23
AI for. Yes, and it's okay that they can create
26:29
with it as well. I just think that, you know,
26:32
at a young age, and it just ties back into what
26:35
is the core of what artificial intelligence is,
26:38
and it's based in computer science. And with
26:41
computer science, you have computational thinking.
26:44
And one of the things that I tell, again, I know
26:47
I'm, you know, have a background in artificial
26:49
intelligence and education, but if we can teach
26:53
kids to think, It doesn't necessarily, any type
26:57
of emerging technology can come into the scene,
27:00
but they're able to have a level of discernment
27:03
and a level of curiosity. that can help them
27:07
navigate whatever comes. And so I think if we
27:11
focus more on those thinking processes, calling
27:14
it what it is, being very definite, and then
27:17
starting with, again, what research says. Kids
27:20
learn, and again, I know it's a mathematic kind
27:23
of system, but start with the concrete. go to
27:26
the representative and then let's go to the abstract.
27:29
Most kids at an elementary age, the concrete
27:34
is best. And then as they move on, your middle
27:38
school, I say that's your representative age.
27:41
And then high school, we're getting to the abstract.
27:43
Those who are interested in programming and things
27:47
of that nature, they can program. But yeah, the
27:50
younger kids. you know, what is artificial intelligence?
27:53
What does it do in terms of if you're wanting
27:56
to be specific about the different types that
27:58
when it comes to generative AI, you're looking
28:02
at, you know, probability, you know. What is
28:06
it doing even with machine learning? It's being
28:09
trained on large amounts of data. It's patterns
28:13
and classification. It's dealing with labeling,
28:17
you know, all of the things that it does in ways
28:20
that are very accessible. I do have ISTE just
28:24
published a jumpstart guide, which is a simple
28:27
six page guide, which is intentional because...
28:30
we felt that there was like resistance and like,
28:34
how can we get started? And it's available everywhere,
28:38
but what it does is it, the things that we're
28:41
talking about for our younger learners, it provides
28:45
specific details on what you can do and plenty
28:48
of examples and resources to get started. Yeah.
28:54
Okay. So I want to take us on a little bit of
28:55
a pivot here. um and maybe there's a better word
28:59
to use here but i'm not giving it away yet last
29:02
summer you had a podcast series that uh you had
29:05
released called the the detour degree which really
29:09
kind of spotlighted unconventional paths um within
29:12
the realm of education and and you know like
29:15
what inspired you to you know find the road less
29:19
graded Well, first of all, I didn't need to agree
29:23
because one of the reasons because I, this is
29:25
like AI all the time. And my brain is like, it's
29:28
like, you know, what I know that there are other
29:31
exciting, amazing things going out because I
29:34
talked to a lot of people and I was like, what's
29:36
the way during the summer? Because, um, and you
29:39
all know this, um, I learned a lesson, like,
29:43
don't try to do things during the school year.
29:44
I'm sorry. Educators are busy. The plates are
29:47
already full. I, you know, I love. The podcast
29:51
and all that we we learn all the time So I don't
29:54
want to take away from all the great things that
29:56
everyone is doing But what I wanted to do is
29:58
say for myself and my you know What I wanted
30:01
to contribute is like how can I do this during
30:04
the summer? and so That is what I did and what
30:09
I wanted to do with the first Year is first of
30:13
all for it to be a limited series But to talk
30:15
about those alternative ways like yes, there
30:18
was a school optima It's totally virtual reality
30:21
school. They have thousands of students. Like,
30:24
this is crazy. And the kids have the VR sets.
30:26
And I'm like, OK, Adam, we have to talk. We have
30:30
to talk. Quantum computing, which is coming online,
30:34
like, where, interestingly, and I say quantum
30:37
is on the same trajectory that artificial intelligence
30:40
is. It's been around since forever. I mean, it's
30:43
100 years old. But in terms of its use, and applications
30:47
now, you know, it's very powerful. We don't talk
30:51
about it. Now, quantum computing is totally not
30:53
online, but quantum mechanics and quantum technologies
30:56
are in use. So it was great not only to find
30:59
a quantum physicist, because that's my other,
31:01
you know, just kind of love of just my interest
31:05
level, but someone who is doing their doctoral
31:09
research. on quantum and artificial intelligence.
31:14
I was like, let's talk. This is amazing. And
31:17
then just bringing it, what I call, back to Earth.
31:21
I also talked with an individual who does gardening.
31:25
And we talked about a way that gardening could
31:28
be used as a vehicle for learning. Like, so I
31:32
wanted to kind of expand my own world by talking
31:36
with people that are doing the things that we
31:39
may not necessarily be thinking about with the
31:42
detour degree. I think that's great. And I connect
31:46
with that quite a bit because, you know, and
31:48
I've mentioned this to many other people, I don't
31:51
know on the show or not, but. like this has been
31:53
some of the best professional development doing
31:55
this series with David and all of the people
31:58
that we've been able to bring on because it's
32:01
really allowed for me to see diverse perspectives
32:04
to be able to hear from individuals including
32:08
you that are able to give insight to things that
32:12
we've been thinking about for a long time. um
32:14
and and to bring them to the forefront and and
32:17
to have a podcast that you can be able to share
32:20
those things out with other people just knows
32:22
that you're you're spreading that that message
32:25
much to a much wider reach of people here um
32:29
you know and and so you kind of hinted at it
32:31
here is there going to be a second season yeah
32:34
so we're i'm just gearing up for the second season.
32:39
Now this year, it's going to be a little bit
32:42
different because there are things that we're
32:46
not talking about enough in the AI education
32:50
space. And then too, as you may have seen, I'm
32:55
out a lot and I'm on a lot of panels and doing
32:57
a lot of things. And a lot of times we're like,
32:59
oh, it's not in our head. Like this is great.
33:02
Everyone agrees, right? And it's like, but wait
33:05
a minute in real life, there's nuance with this
33:07
artificial intelligence thing. And we want to
33:10
bring that to the forefront. So this year I'm
33:13
doing great debates where I'm hoping to produce
33:17
four episodes of great debates because there
33:21
are certain topics that I feel need that nuance.
33:24
And it's not a drama. Like I don't like the argument
33:28
for the sake of argument. It is questioning,
33:31
right? It is questioning and counter argument.
33:34
Like what are some things that people should
33:36
be thinking about? The other part is of what
33:39
I'm doing is dissertation work. So there is a
33:45
website called Scale. that Stanford supports.
33:50
And they actually have collected a lot of the
33:53
research. And even with all of the research studies
33:55
that they've collected, only 22 of those studies
34:00
have been considered of values, not the right
34:05
word, but has the elements that scale was looking
34:09
for in terms of things that we should be looking
34:12
for in research. But there is this emerging body
34:17
of work through dissertations with AI and education
34:22
in particular and in the United States. So let's
34:25
be clear, in the United States, there's still
34:27
not a lot of research. Like when I first started
34:29
my doctoral program in 2019, I was like... You
34:35
know, where, where can we find it? So I wanted
34:38
to, I'm going to hopefully again produce four
34:41
episodes of people who have either completed
34:43
their doctoral studies or are in the midst of
34:47
doing their doctoral work in AI education. So
34:50
we can kind of talk about those emerging issues.
34:52
And again, things that people should be thinking
34:55
about. Yeah, that that's really neat. And so
34:59
I'm like, it's not going to be a Jerry Springer
35:01
all out. No, it's gonna be. You're going to bring
35:05
together, you know, some of the best and the
35:07
brightest, and they're going to be able to kind
35:10
of share what they've been working on and how
35:13
it relates to the field, which to me is a much
35:16
better way to spend my limited amount of time
35:19
that I have as a teacher and try to value my
35:22
summer, but still try to keep plugged into the
35:25
things that are going out. Yes. No drag out fights,
35:30
no. Well, maybe one, no. But if you happen to
35:35
have those, you have to let us know. And we want
35:37
to know. We wanted to try to bring those people
35:40
onto our program. I'll see you to be wrong. Like,
35:44
don't share it. But this was a good argument.
35:49
So I and I do I want to get a little bit into
35:52
some of the things. I know we took a detour for
35:54
a minute there. Literally, and it was the topic,
36:00
but some of the other resources that you have
36:03
on the website that are really cool, one I've
36:06
been trying to figure out and say the name correctly
36:09
for the last couple days, but I wanna start with
36:13
CRISP. And so you created CRISP, and basically
36:17
it's like 15 ways that artificial intelligence
36:21
is transforming K through 12 education. So it's
36:24
this chart. Can you explain where that came from?
36:28
It was that part of your your dissertation work
36:31
and how did that come about? Yeah, so it was
36:34
part of my I created it during my doctoral program
36:38
and It was just to talk about how was transforming
36:42
education and I started using it early on in
36:47
my presentations when I started talking with
36:50
people about artificial intelligence in Education
36:54
just for the reasons we I expressed earlier is
36:58
that it was like just you know people were conflating
37:01
gen AI with all AI And I was like, all right,
37:04
let me bring Chris out so we can talk about the
37:07
different ways, particularly education, that
37:09
is impacting your work. And so people, and again,
37:12
I would start with, you know, your computer adaptive
37:14
assessments or computer adaptive tests. And they
37:16
were like, and I would use the example of map.
37:18
And they were like, what? You know, or just AI
37:21
scoring. I mean. AI scoring has been a part of
37:26
assessment for decades, but they didn't call
37:28
it necessarily AI scoring, but just those type
37:32
of things. And so this was a way for me or entry
37:36
point. particularly for educators to see like
37:39
it is not this big scary thing that's coming
37:42
to get you and Coming after your job. It's something
37:45
that has been in your world for some time And
37:48
now it's just the elevation because the technology
37:51
it has advanced exponentially Yeah, and that's
37:57
a it's a good way to understand it too and I
37:59
like how you kind of have it broken down into
38:01
different categories like even just looking at
38:05
Things that require data and those are search
38:07
engines and they're there if as you look at it's
38:09
like well there there are a combination of things
38:12
that we're familiar with and some that are maybe
38:14
new to us and and that's kind of is it am I right
38:17
in that assessment of it like that seems like.
38:20
Oh yeah, definitely. So, you know, one of the
38:23
things I would do is say back when I was using
38:26
this is I would pick different programs and I
38:30
would tailor it to like in my district, what
38:32
we were using in my district that met these categories.
38:36
When I would go and speak generally to audience,
38:39
I would pick some general things. For example,
38:42
when in IVE where it's identifying needs, well,
38:44
what do we use MAP for, right? To identify, you
38:47
know, needs to see progress. Well, that's a computer
38:50
adaptive test, a cat. For example, I was like
38:55
any search engine. is, you know, if you're Googling
38:59
something and even before Gemini, you know, you
39:02
started getting the Gemini results, it was still
39:05
working on an AI related system. So those are
39:08
the ways that I will talk about it. Then at the
39:10
time. and generative AI was still fairly new.
39:14
So we could talk about, hey, here are these generative
39:18
AI systems that are based on, and now the terms
39:20
like back then it was LLMs, then it went to foundation
39:23
models. Now the terminology being used more for
39:27
the same thing is general purpose AI. And so
39:32
that's another reason why it's good to continue
39:34
these conversations and then to ask. where there
39:38
is a, you know, what do you see on a framework
39:42
like Chris, where you're like, I don't know what
39:45
editing software we use. It was great for me
39:47
even back then to say Grammarly. And people are
39:50
like, oh, but you use Grammarly, right? And it's
39:52
there to help, right? It's not what, you know,
39:54
I know there's some controversy around it now,
39:58
but back then, you know, it's just a way to show
40:02
people that AI is helpful when it's used in ways
40:05
that are ethical. Um, and where you checked,
40:09
you know, we always need our guard rails. And
40:12
so that's what Chris was about. I don't use it
40:15
as much anymore. Um, just because the conversation
40:18
has shifted and I've, I've been doing a lot of
40:21
work with AI for young learners, um, AI and inclusivity,
40:27
um, and AI literacy to an extent, but, but even
40:31
with AI literacy, and I don't know if you all
40:33
have seen this, but there's still so much of,
40:36
of a focus. on generative AI. And I always try
40:40
to find a balance, but I also want to meet the
40:43
realities and needs of the school districts and
40:47
the education leaders that I'm serving. And so
40:50
I don't want to try to ram like Chris down their
40:52
throats if they're like, we just want to know
40:54
how to effectively integrate a gen AI program
40:59
into our schools. Yeah, and that kind of brings
41:03
us into and one of the other things that you
41:05
created too, which in your head I'm probably
41:07
gonna butcher this you'll have to help me out,
41:09
but I think it's Pitheagoretic table Oh, I told
41:18
you I said that I live totally my son But yeah,
41:23
so I was looking at it and it's really cool because
41:25
I well I like it because it's got kind of that
41:28
like scientific elements feel to it right and
41:32
um it's kind of cool how basically you just you
41:34
use that as a key for indicating certain types
41:38
of different ai that you might see and how what
41:40
kind of supports it gives and that kind of thing
41:42
um can you talk a little bit about that and give
41:44
us some more detail into how you created that
41:46
and yeah so first of all what happens is that
41:51
uh and as you know educators you know look you
41:55
get thrown a lot of tools and people are just
41:58
like oh my gosh you know, use this tool and use
42:01
this tool and use that tool. And I thought that
42:04
it was important to kind of sift through the
42:07
noise and not, and I'm very tool agnostic. So
42:12
that's another thing. Generally, I don't talk
42:14
about specific tools unless it's as a rep, you
42:17
know, like here's an example, but not let me,
42:19
you know, use this. And so because of that, what
42:23
I compiled, and I've done it, I haven't done
42:25
this year's yet, but for two years, I just compiled
42:29
some of the programs and the way in which they
42:31
were being used to help people navigate the AI,
42:38
what they were interested in. And so again, Pythagorean
42:43
theorem is one of favorite shapes. And then to
42:46
try to combine that with, because you see so
42:48
much the periodic table. used to describe things.
42:52
So I was like, what's a way to turn it on its
42:55
head, but still use those elements? And so that
42:58
is where the inspiration behind the Pythagoretic
43:01
table. So again, it will. In this case, it deals
43:09
with things like what are the, you know, foundation
43:12
models that are out there, not only foundation
43:15
models, but the chat bots. So a lot of, you know,
43:18
the first section with this version, there's
43:20
a newer version I'll have to share with you.
43:23
But for the version that is still on the website,
43:28
it starts with the, you know, LLMs and the chat
43:32
bots. It goes through, it separates things by
43:35
like language supports and academic support.
43:37
Some of them may be familiar and some of them
43:40
may not be familiar. Also the organizations that
43:44
are driving some of the work. I call them anchor
43:47
organizations and I'm trying to, particularly
43:50
now when I talk to organizations, institutions,
43:54
education leaders, it's just... anchoring our
43:58
knowledge base to the organizations that are
44:02
veritable that, you know, I've been doing the
44:04
work for some time, I think is important, just
44:07
because there are so many definitions out there.
44:10
There's still so many misconceptions out there.
44:13
And I feel like if we can ground ourselves in
44:15
that work and then to obviously some of the newer
44:19
tools that are available so that they can explore.
44:23
So it just has the links color coded. to what
44:28
type of AI or AI related system that it is so
44:34
that people can explore. And like I said, there's
44:36
a newer version. So I do change it every year
44:38
because the thing that happens is because...
44:42
the nature of the ed tech world, you know, here
44:46
today gone tomorrow type and or not effective
44:51
or, you know, I've heard things. And so I do
44:55
make changes. And so I haven't done this year's
44:57
yet, but I do need to update. I didn't realize
44:59
I had not put the version from 25 on the website.
45:05
So I will make sure you all have that. OK, so.
45:11
Pythagoretic Pythagoretic Pythagoretic Pythagoretic
45:14
Pythagoretic. OK, I think I got it. So one of
45:18
the things that's really cool about that is we
45:20
we run into this so often is that we like we'll
45:22
go out and talk with administrators and things
45:25
and they're like, well, what tools should we
45:27
be using? You know, and so I really like how
45:29
you've done this and in the sense that like breaking
45:33
apart what all these similar tools do to support.
45:38
Education is just to support pedagogy and you
45:41
have more of a there's a. It's more like a category
45:45
you're picking from. It's not that you're honing
45:47
in on one tool, though I know we do also have
45:50
to. One of the conversations is big for us too
45:52
is just if a tool is considered data privacy
45:55
safe or not. It's a big thing for for our state.
45:59
At least I know that's that's something we talk
46:02
about, but I wanted to ask you one more question
46:05
about this. If. if you were to work with the
46:08
school for like uh 20 minutes during a staff
46:12
meeting and you gave them the thethagoretic table
46:16
um what would you want them to walk away with
46:18
after that time and i realize it's not a lot
46:20
of time but so i i've used this in trainings
46:25
before and i i use what i call the rule of three
46:28
omni -triumperfectum So I say from this list
46:33
to choose three you already use and choose three
46:35
you want to explore and then have a conversation
46:38
with your neighbor about what you learned. So
46:40
I give them room to explore. We know this about
46:43
like I could talk about the tools I use that
46:46
means nothing. I mean honestly nobody cares and
46:48
unfortunately it's research based like one of
46:50
the things about research that I found was hilarious.
46:54
As a district leader like who do people want
46:56
to learn from? Do you know who was last? District
46:59
leaders. I was kind of in my feelings a little
47:01
bit, but it was hilarious, right? It's a humbling
47:04
lesson. People want to learn from each other.
47:07
And so when you're in those settings, that's
47:09
what I use it for. At first I thought, OK, this
47:14
could be overwhelming. So that was another reason
47:16
to categorize it. And that's why. I always start
47:19
with first choose three that you already use.
47:22
So now we're bringing that familiarity in and
47:25
now choose three you want to explore. So it kind
47:29
of constrains it a little bit, makes it a lot
47:31
more palpable. And then you're conversing with
47:33
your neighbor. I'm always going to go back to
47:35
talk. Yeah, I think that's a great strategy to
47:41
use. And it definitely is applicable for anyone
47:43
doing professional development around any topic
47:47
is take advantage of the people in the room,
47:51
because I've often heard it said the smartest
47:52
person in the room is the room. It is every single
47:56
one of those people connecting. Yes, definitely.
48:01
So one thing that I hear a lot from teachers
48:05
and even from students, and I've had a couple
48:08
of my own students that have experienced the
48:11
college world with AI. One of them is 21. The
48:15
other one just graduated. He's 23. But they've
48:18
both had to deal with AI in their university
48:21
capacity. But I know it extends down into especially
48:24
that high school space. But it's really about
48:27
coming from the teacher. and expressing their
48:32
transparency about what they consider appropriate
48:37
use for particular, for their course in general
48:40
or for particular activities in that course.
48:43
And one of the frameworks that I saw you produce
48:46
here and put out there is the AI creative framework
48:50
or AI creative framework indicator, which is
48:55
an interesting way to share and I think be ultimately
49:01
transparent about what is presented to students
49:05
as is acceptable for use on particular assignments
49:08
or in general for a course. Can you explain that
49:12
a little bit for us? Thank you for asking about
49:15
the AI creative framework indicator. So again,
49:18
based on my research and just based on the realities,
49:22
what you're seeing a lot of is just as you mentioned,
49:26
this is how you can use AI in the classroom.
49:30
And they have some great skills. Leon, and I
49:33
hope I'm not saying his last name incorrectly,
49:36
Fersi. has a great kind of skill. You've seen
49:40
like the stoplight scale of like when you can
49:43
use it, when you can't use it. You know, as you
49:46
said, you have, particularly in some of the college
49:49
spaces, you cannot use artificial intelligence
49:53
to generate any work, but. One of the greatest
49:58
quotes that I just love comes from one of the
50:03
superintendents I served under. And he said,
50:06
let your conscience be your guide. I'm about
50:09
empowerment. And it's like, as opposed to me
50:12
setting guard rails and telling you when and
50:14
when you can't use it. just let me know how you
50:18
use it. And that's what the creative framework
50:20
comes from. And I didn't limit it because a lot
50:23
of times it's limited to assessment and creation
50:28
of particular text -based assignments. And so
50:32
I wanted to broaden it out because if I'm using
50:35
it in a creative way, let's say for... artwork,
50:39
digital art or whatever, I wanted it to be, what
50:42
are we creating and how are we using it? But
50:45
I wanted it to be an empowering tool. And so
50:47
if I was still, you know, in the classroom, I
50:51
would hesitate to say, I don't trust you enough
50:56
after I've given you like how to use this appropriately
50:59
when you can and cannot use it. That's such an
51:02
important foundational piece. And I know we've
51:03
touched on it, but I just want to emphasize,
51:06
yes, they need For what it's worth the AI literacy.
51:09
I just again as we talked about I think you can
51:12
wrap it up into some others and kind of you know
51:14
Be more efficient with that. But after I've given
51:17
you those type of lessons Wow, what what what
51:21
trust can we endear in our kids if we say just
51:23
let us know how you've used it And here's this
51:26
framework for you to let us know how you've used
51:29
it I think there would be a lot less anxiety
51:33
and a lot less of people, because what I'm hearing
51:37
is actually, yes, you have students that are
51:40
using it, but more, they're not using it to generate
51:43
work. They use like LLMs, their chat bots for
51:46
search engines. Like they're looking for information.
51:50
They're not looking to generate assignments.
51:53
I mean, that's what I'm hearing from college
51:55
students. Yes, you're going to have yours, but
51:56
those are the same people that were buying like,
51:59
you know, Buying the the lecture notes, right?
52:02
Whatever whatever they're gonna do to get ahead.
52:05
It wasn't it's not The vehicle was just it's
52:09
another vehicle. It's not gonna stop them if
52:11
it was something else out there They would be
52:13
using it. So that's what the creative framework
52:15
indicator is for I know a couple of districts
52:19
that use it I I probably should push it out more
52:23
do some more kind of research based articles
52:26
on it Just because when it started You know,
52:30
and like I said a couple of schools. I know one
52:32
district adopted it I just I need to do more
52:36
with it because I think it's important and I
52:38
do use it in my you know in my work like when
52:41
I do blogs and stuff I will put that little notation
52:44
at the end. That's the other thing I want to
52:45
be very simple I don't want people like you'll
52:48
see now how people have these long explanations
52:50
and I have to use it in some of my academic work
52:52
where it's like we use chat GPT for editorial
52:56
refinement and we use this tool and this tool
52:59
as opposed to just having a simple notation I
53:02
think if it does catch on or if some similar
53:05
it doesn't have to be this one but if something
53:07
similar that empowers our kids and I think that
53:11
that will help with the trust and the transparency
53:13
issues that we see so much in the space right
53:16
now. I think one of the things that I appreciated
53:19
about it as compared to say like that stoplight
53:21
model that you had mentioned, and I've seen a
53:24
lot of districts adopt that because I think it's
53:26
very straightforward and simple for them to understand.
53:30
But I think it also at the same time establishes
53:33
a hierarchy with the red, the yellow and the
53:37
green and that, you know, one is inherently better
53:40
than another. And, you know, the then there's
53:43
the area in the middle and it's like we don't
53:45
want to deal in the middle so you've got to be
53:47
either all in or all stop or all go right um
53:50
but i think what i really like about your framework
53:52
here is that it well the as i'm looking at it
53:56
here it's hexagonal and i'm trying to describe
53:58
it a little bit for the listeners here um with
54:01
different pieces wedges coming in think of like
54:04
um Think kind of like the old Trivial Pursuit
54:07
game, right? And you get the little pieces of
54:08
the pie to stick in and they're all different
54:10
colors representing different things, but no
54:13
color is better than any other color on there
54:16
and no wedge is inherently better than any other
54:20
wedge. So you have things in there like no use
54:22
of AI at all. And you have, you know, a middle.
54:26
area in there and you know some that are just
54:29
like well I used it here like you had just said
54:31
for editorial purposes and with citation and
54:34
you know or you know we were co -creating this
54:37
together and I think that would be very you know
54:41
you you talked very early on here about establishing
54:44
a vocabulary this would be a great way to establish
54:47
a vocabulary to build that trust and transparency
54:50
between teacher and student to say hey I use
54:53
this for idea generation. or when they submit
54:57
their work saying, I used AI editing for this.
55:03
Yeah, I totally agree with you because, I mean,
55:07
why not? The biggest thing, I know you've heard
55:09
this too, because one of the other issues when
55:11
it comes to trust in the classroom, our kids
55:13
are highly, I mean, they're smart and they're
55:15
observant. And if you've been around, Laura,
55:18
especially at each level, they're looking at
55:19
you all the time and seeing what you're doing.
55:21
You know what they see now? They see adults using
55:24
generative AI all the time. And just as we're
55:26
like, oh, that looks like AI, they know, and
55:28
they're like, oh, you're giving us an AI generated
55:31
worksheet, but we can't even, you know, pull
55:34
it up and think about. what that does to the
55:37
most important thing in the age of AI, the human
55:41
relationship. If we cannot trust each other and
55:44
are the things that make us human. why would
55:48
we let AI fracture that? And so again, that was
55:52
the inspiration behind it. And again, to take
55:57
it away from just assessment. I wanted to broaden
56:00
it so that any creative could use this because
56:04
again, you're starting to see, I mean, I saw
56:06
at the end of a movie that came out recently,
56:09
no AI was used in this movie. Like you're having
56:12
to explain, if you have to use a paragraph to
56:15
explain, I mean, it's not going to have an impact
56:18
in just having something that's very similar,
56:20
similar to. So the inspiration was the creative
56:23
comments. You see it, you understand it. It is
56:26
very simple. And so that was an inspiration for
56:29
the AI creative framework indicator as well.
56:35
Awesome. Well, Nick, thanks for all these awesome
56:38
ideas and resources that we've been talking about.
56:41
And I'll make sure that we link those things
56:43
in the. show description, everything. But we
56:45
do want to get a little bit more into who you
56:47
are as a person. I mean, so this is one of the
56:48
things we like to do. So it's not, you know,
56:51
all serious topics and things like that. So I
56:54
want to kick off our lightning round. And Jeremy
56:57
and I go back and forth on these these on these.
56:59
You can, you know, as you can give us one response
57:02
or you could like dig into it a bit further,
57:04
whatever you want to do. And then we have a this
57:07
or that that's that one's a little bit more strict.
57:09
It's just one or the other. Right. So So the
57:13
first lightning round question I have for you
57:15
is what's the first detour in your life that
57:18
ended up being a gift for you? The first detour
57:23
that I think is impactful is my dad taking me
57:28
to see his math teacher when I was in college.
57:33
And as I said, I had a career transition. And
57:38
I've used that example of him thinking it was
57:41
important enough. And this is in deep woods of
57:44
Mississippi to take me to see who taught him
57:47
math. And then eventually I became a math teacher.
57:54
Make a what's what's a song an artist or even
57:57
a playlist that instantly gets you into a good
58:00
work groove. So I have to tell you, I am someone
58:05
who when I am like working, I cannot have noise,
58:10
if that makes sense. But when I'm in the kind
58:16
of editing mode or where it isn't requiring.
58:22
a lot of my cognitive load, it depends on the
58:26
situation. So sometimes it could be classical,
58:29
sometimes it could be rap. It depends on the
58:33
mood and how I'm feeling, but I love all types
58:36
of music. All right. So this next one, if you
58:42
could take a one week learning trip anywhere
58:44
to learn about something that you don't currently
58:47
know anything about. Where are you going or what
58:50
are you learning about? So I want to go on a
58:56
cruise to Antarctica and I want to do the Drake
59:00
Passage because I want to see if it's as scary
59:02
as it looks. I know that's the weirdest thing,
59:07
but yes, I don't know much about Antarctica and
59:11
I'm so intrigued by the Drake Passage. I definitely
59:16
wouldn't pick a cold place like Antarctica, but
59:18
I book it. That's why all different things for
59:21
different people. What's a tool or a habit that
59:25
most people would be or the tool or habit that
59:28
you use that most people would be surprised to
59:30
learn about? I think that most people are surprised
59:33
to learn that I do not. I love technology and
59:37
I know a lot about technology, but I do not use
59:40
a lot of technology. So when people are like,
59:43
oh, just put me on your app. And I'm like, yeah,
59:45
I have very few apps. And they're like, what?
59:47
And I'm like, yeah, I mean, and then I, you know,
59:50
I don't want to go grim reaper on them, but I,
59:56
you know, that's a whole nother podcast. All
1:00:03
right, what's one thing you're currently obsessed
1:00:05
with learning just for fun? So I know it's fun
1:00:12
for me, but but like I said, I'm learning a lot
1:00:16
more and trying to get more Education around
1:00:22
quantum computing like 20 years ago I actually
1:00:26
wrote a manuscript about which is so crazy because
1:00:29
back then it was interesting, but about a rogue
1:00:33
quantum computer. And I actually went to like
1:00:35
one of those pitch things and people were like,
1:00:38
this is like the craziest thing ever. And it
1:00:40
could like never happen. I mean, I was all in,
1:00:42
I went to like Fermilab in Illinois. Like I was
1:00:45
so interested in it actually. Um, I kind of like
1:00:49
put it aside. And so now, you know, that is coming
1:00:52
back. And again, it started with the kids. We
1:00:54
were, um, I was working on a lesson that actually
1:00:57
took me two years to create about RSA encryption,
1:01:00
which runs, you know, all of the things, the
1:01:02
internets, the financial systems in terms of
1:01:06
protection. And, you know, when quantum computers
1:01:09
get uh to a certain level all of that's gone
1:01:12
they'll be able to solve they'll be able to crack
1:01:14
rsa encryption something that it would take you
1:01:17
know a cray supercomputer you know thousands
1:01:19
and thousands of years it'll be able to do you
1:01:22
know in minutes and so um yeah i'm so i'm so
1:01:27
interested now that i'm back you know in that
1:01:29
world um i spend a great deal of time doing research
1:01:34
and kind of learning more about what's going
1:01:37
on there So David and I are gonna have a conference
1:01:41
and we've hired you to come on stage to be our
1:01:44
keynote speaker here and Before we let you out
1:01:47
onto the stage the sound guy wants to know What
1:01:50
do you want playing to pump up the audience as
1:01:53
as you step onto that stage to give your keynote?
1:01:56
What's your walk -up song? Guys what is that
1:02:03
song? I think her name is Sia for Wonder Woman
1:02:08
Um, I forget unstoppable. Is that what it is?
1:02:14
Oh, I know what you're saying. Yeah. Poppable
1:02:17
today. Yeah. Yeah. As you can tell, we're going
1:02:22
on the karaoke here too. I know, right? I would
1:02:25
want it, but then I'd probably like, no, I mean,
1:02:27
I want it, but could you play a few little bars?
1:02:29
They won't think I'm like big kid. Alright that
1:02:35
brings us into our this or that section so you
1:02:38
can only choose one or the other and so I'll
1:02:40
go through all these coffee or tea tea Okay cook
1:02:48
at home or eat out Oh cook at home Early bird
1:02:55
or night owl oh Depends on the on the I would
1:03:02
say night owl Depends on if we're at SD or not,
1:03:07
right? Depends on a project if I'm working on
1:03:10
a project night time is quiet time So, you know,
1:03:14
like I told you when I you know, it's best time
1:03:17
to work without a lot of you know No, you know
1:03:19
noise but being an educator I mean you had to
1:03:22
get up at you know, 435 a .m. And so did that
1:03:25
for a long time Okay, if you're taking a trip
1:03:30
podcasts or music no podcast I love listening
1:03:35
to folks. I would guess that Integrate This is
1:03:39
probably the first one on there. Oh, yeah, definitely.
1:03:42
I know you are sending me a T -shirt, too. This
1:03:48
one's always a surprising one. We never know
1:03:50
what people are going to say on this one, but
1:03:52
mountains or beach. Oh, I love a good beach,
1:03:58
but mountains are so man that clean and crisp
1:04:02
air. That is pretty difficult, but but I'll have
1:04:07
to say beach Okay, yeah, that's mountains is
1:04:12
I think still ahead for us like things like the
1:04:14
one I think typically so I can't understand I
1:04:18
totally can but In the last one your city adventure
1:04:24
or nature escape nature escape definitely Which
1:04:31
is crazy because I'm not like a big bug person
1:04:33
but man I love a good just out in the woods nature
1:04:37
Where my parents grow we still have land there
1:04:41
in Mississippi. It's just like the best Get away
1:04:45
in tune with nature Awesome. Well, um, they could
1:04:50
want to thank you again for your time and we
1:04:52
really appreciate you Spend time with us. And
1:04:55
is there anything that you want to plug that
1:04:57
you have coming up just so that we can let listeners
1:05:00
know conferences, anything that you want to put?
1:05:05
Well, first of all, thank you again, David and
1:05:07
Jeremy. This has been wonderful. I appreciate
1:05:10
it. Great conversation. As I mentioned that.
1:05:14
Definitely want to shout out the AI for young
1:05:19
learners, balancing tech use with authentic off
1:05:23
-screen experiences with this jumpstart guy from
1:05:26
ISTE. I will be at ISTE this year doing things
1:05:31
with AI for young littles, doing a short session
1:05:34
about quantum and how it's emerging in the education
1:05:40
world as well. And so that will be exciting.
1:05:45
Great. Yeah, and hopefully we'll see you at ISTE
1:05:47
as well because Jeremy and I will be there. So,
1:05:50
yeah, thanks again. Are you all presenting? No,
1:05:54
we're just coming to take in all the festivities
1:05:58
and sessions. So, but thank you again. And we'll
1:06:04
make sure we put your resources and things in
1:06:06
our show notes for everyone to access. And yeah,
1:06:10
we thank you for joining us. Thank you. Thanks.
1:06:20
Thanks for listening to Integrate This. Want
1:06:23
to take your learning further? Head over to our
1:06:25
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1:06:29
and more EdTech tips you can use right away.
1:06:32
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1:06:35
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1:06:39
wherever you get your podcasts. Until next time,
1:06:42
keep exploring. Keep innovating and keep integrating
1:06:46
this.