Inside Our MIND is a flagship podcast of MIND Research Institute. We're a
neuroscience, education and social impact organization whose mission is to ensure
that all students are mathematically equipped to solve the world's most
challenging problems. In each episode of Inside Our MIND, we take a look at the
issues and challenges facing education that we're working to address through
research, technology, and strategic initiatives. Welcome to Inside Our MIND. [Intro Music]
Welcome once again to the Inside Our MIND podcast. I'm Brian LeTendre, the
Content Manager for the Engagement team here at MIND, and before we get into the
heart of today's show, I wanted to first thank everyone who checked out the first
episode of the podcast. The feedback that we've gotten so far has been great, and
our first episode has only been out for a few weeks now. Since that first episode,
we've made it easier for you to find our show and to share your thoughts and
feedback with us. We're now on Apple Podcasts and Google Play Music, and in
addition to Facebook and Twitter, you can email us directly now at
podcasts@mindresearch.org. I'll put a link to that in the show notes.
We'll also be bringing the show to more platforms in the future, so stay tuned
for updates. With that bit of housekeeping out of the way, let's dive
into today's topic, personalized learning. Now with the topic as broad as
personalized learning, we could do an entire year-long podcast series and not
touch on every facet of it. And to be sure, we'll talk about personalized
learning plenty of times over the life of this show. But much like we did in our
episode about EdTech evaluation, this initial conversation is about addressing
personalized learning misconceptions, as well as equipping educators and
administrators with questions to ask when designing and implementing a
personalized learning model. To do that, I recently sat down with Brandon Smith, our
Lead Mathematician here at MIND Research Institute. Brandon is a passionate
advocate for mathematics both inside and outside of the classroom. He designs
mathematical requirements for our game-based ST Math software, defines
mathematical schema, creates family math night experiences, consults with our
professional development team, and has developed exhibits for math fairs and
math camps. Prior to joining us, Brandon was a
college instructor, where he won an outstanding teacher award and was the
educational liaison for the city of Costa Mesa to Wyndham, Australia. Brandon
has a Bachelor's in math and two Master's degrees in pure and applied
mathematics. One of the key themes that Brandon hit on in the discussion that
you're about to hear is the idea that in trying to become the antithesis of
one-size-fits-all, you can actually create the antithesis of personalized learning.
He also talks about how you can avoid that pitfall by asking the right
questions and having clear goals in mind when implementing a personalized
learning model. Without further ado, here is my conversation with MIND's Brandon
Smith. Thank you very much for joining me today Brandon and taking some time out
to talk a bit about personalized learning. Because I know this is a
conversation that we've had a couple of times off the air, and one of
the things that comes up around personalized learning any time it comes
up as a term, is just how many misconceptions are out there and sort of
misunderstandings of it, because personalized learning has become such a
buzzword. Do you find that it's a term that the more people use it,
the less they actually understand it? I think what happens so
often, at least in my experience, is we get excited about a new rhetoric, or a
new way to talk about the problem, because we're all wanting to solve it.
And we start to see glimpses of potential. We get really excited, we get
full of optimism. And we start to see a couple of examples of what we think
personalized learning or any other buzzword is, but we don't really sit down
and say "Well, what's the goal? What is it trying to do?" In order to know the
misconceptions about it, we're going to want to know what some of the
positive conceptions about it are. And, if we just get something
to get really popular it literally becomes a buzzword, that becomes a cliche.
So, this is really exciting, because you know as we continue to make
more advances in learning, and the use of technology to really take learning up a
level that we might not have had before the technology, having these deep dives
into what is it, what should it be, what is it trying to do, where did it even
start, where did it come from, I think are all really important. And if all of
us joining the podcast and listening can start to get more of this lens of
problem solving approach--I hear a word but what is it trying to do, right? That
helps us not just take what I like to call the shotgun approach, where we
say learning is struggling and students aren't at the level of math perceptions
and the level of math achievement that we're looking for.
So that's where we get terms like the opportunity gap, the achievement gap, the
perception gap. Students aren't there, and people are different, but yet our
education always looks the same. And so we say "Well, one-size-fits-all doesn't
work. So maybe what we want to do is just do all kinds of stuff that isn't
one-size-fits-all." And personalized learning now kind of fits that mold of
being the antithesis of super traditional education, but that doesn't
mean that just because we want to go anti one-size-fits-all that I can do
anything I want. We still want to explore the unknown of how to solve this problem
in education in productive and targeted ways. And so hopefully we can help unpack
some of those, at least from my perspective, and really have a powerhouse
experience for people on personalized learning. And I think you hit on such a
great point there, and I think that this this idea that when there is a concept
that seems outdated or sort of obsolete, that we tend to swing totally
in the opposite direction, even from a guideline standpoint and a
regulatory standpoint. My background is in early education and care, and I know
embedded in our regulations when I was working with child care providers around
education and curriculum and things like that, everything was about meeting the
individual needs of each child. Making sure that we're tailoring the experience
to each child. And I think that then gets interpreted in this sort of knee-jerk
way to be the opposite of everything that we've known before. And like you
said, everything in the middle kind gets lost. Yeah, in trying to be the
antithesis of one-size-fits-all, it sounds weird, but we actually also become
the antithesis of personalized learning. Because we don't necessarily take
a targeted approach. We know that education is broken, in the sense that
students are coming out of school often times without the depth of
understanding that all of us see, without the appreciation the beauty of
mathematics that educators can see and feel. We all know that dissonance, we can
all feel that dissonance. But the question to me always is what do
we do about it? So, what are the issues at play, and let's target those and
personalize learning now, instead of just being a blanket term
for anything that's non-traditional. I think it can really become a term about
making learning personal. So, personalized learning requires that learning is
happening. And so, really to have personalized learning isn't just to say
you get to choose what you learn, or you get to spend time creating an
environment in which you learn. It's almost like if you were really into cars,
and I have a word problem about apples and oranges and I turn that into cars
and motorcycles. That doesn't mean that you automatically can solve the problem
any better. I haven't given you any tools. If you can solve the problem whether
it's apples and oranges or anything else. It's pretty much equally enriching or
not enriching for me. Right. What happens if I can't? If I can already do it,
I'm not having a learning experience at that moment. What happens
when I can't do it? In the moment that I am stuck, that's the moment that learning
is happening. And personalized learning now has to be something that really
drives and focuses on that moment of learning, and in particular the moment of
if I'm having a misconception or an error or even I might not know that I
have it right. So it's an important piece in learning to get the feedback that I'm
on the right track. And I think you hit on two great misconceptions there and
also that point. Number one, on the positive point about that moment is happening--
where that learning is happening. But the misconceptions that
you hit on are one, that choice does not alone create personalized learning, and
having an environment doesn't alone create personalized learning. And so
sometimes those approaches to quote-unquote "doing personalized
learning" people take and glom on to those particular concepts and think that
that's what it means. At least, that's the way that we've enacted
it. Right. So, what I mean is oftentimes we a lot of us get really excited with
having an innovative viewpoint on something. But usually when we have the
viewpoint, it's low risk for us. We have an innovative viewpoint, meaning we're
kind of a rebel against the culture or whoever it
is that's responsible for the decision, "I'm going to be
brilliantly counter-cultural." And so an innovative viewpoint is one thing. But
what we want to be looking for are targeted and innovative actions that
don't just give me a new opportunity to learn but they actually achieve new
learning results. So if choice alone was enough, what that means is it doesn't
matter how I learn as long as I just choose what it is I get to learn.
But there's going to be things in life where we might not want students or
anybody to make the choice of if they learn it or not. So reading and speaking--
we would all say that those are very practical skills. And so personalized
learning can't be choice. If it was, then we would just say "Oh, it's totally fine
if some people chose not to learn those," With the environment, there is a level of
environment that is important to learning. So, environments that build
mindsets that failure is okay--in fact it's expected, it's why humans always
fall before we learn how to walk. ingrained in the human experience from
the moment we're born is learning by doing. By early failures being important
stepping stones to later success. So if you're creating an environment where
failure is always punished, where every time I'm practicing something I'm always
getting a grade for it or something like that, then you are creating an
environment that's against learning. And so creating an environment that instills
positive mindsets to show that learning math is not something that's alien
or inhuman, that we can take a human approach to learning math just like
learning anything else--those components of environment are really important. But
what I get at with environment, I think you were hinting at as well, is
if I'm spending time looking at this fun world and then every so often I do a
math problem, learning didn't happen until the math problem was there.
At least, the learning of the math didn't. So, if exploring the world is not
inherently a mathematical experience itself, you're spending duty-cycle--
students making a choice what they explore in that environment--but their
task on hand is so minimal that you don't get much out of it. It has to be
personalized at the moment that those decisions are being made. Learning by
doing doesn't mean being active when I learn, it means doing the pertinent tasks for
learning to happen. And each one of us are going to approach a problem with
different conceptions, different misconceptions, different life
experiences. And because of that, we might have different early successes or
different early failures. And so, personalized learning needs to tailor
for the array of decision-making and responses that a student might make, and
make sure that the interaction in that moment is really important. So it's not
just the environment that, you know, goes kind of counter personalized learning.
Things like watching a video and being able to hit rewind. If I already know it,
the enrichment of the video might not be that much. What happens when the student
doesn't know it? And let's say they go through a part of the video and they're
stuck. If they have a misconception that they haven't been able to act on and see
the result of their decisions and how that played out, the only choice they
have is to go back and rewind. And when you do that, you hear the exact same
thing again. And so, so many of these things we say are
personalized learning, we end up using that as a blanket term for "cool stuff
computers can do." And really, what we should be analyzing is--what is a
computer or technology of any form doing that's really going to help me--and
holding ourselves accountable for those learning outcomes. Often times we hold
ourselves accountable for using the fun rhetoric, but do we really hold ourselves
accountable for that true learning to happen. So one example for me is that one
of the big things that comes to mind when I think personalized learning-at
least in the marketplace right now--
is it's almost always set in the context of technology. Which it doesn't
have to be. And it's very often used in the world of adaptivity. But if you
look at what the adaptivity is doing, in most of the cases all it's doing is
telling the computer to choose what the student sees as
placement--what should you see, what do you not need to see. But in that moment,
if I am consistently overestimating something or under estimating something,
what do I do beyond the same hint that I saw the last time I was
here when I was placed before? And so, personalized learning can't happen just
with placement alone. It's not that placement is bad--it's that it's
not strong enough to encompass really what personalized learning is trying to
do. And so do you feel like that's where there's often missteps, is that there's
too much of a focus on placement, and so it's weighed too heavily in that process?
Yes. I think the way that I would kind of classify it for myself,
is personalized learning is very focused on variety, regardless of what it is.
So I can make an avatar. I can customize that avatar to have hair. I
personally would love to do that since I have none. Same--haha. You look great by the way. You too.
So, I I want to select the environment in
which I work. I want to choose the problem I'm working on. Choice, choice
choice--variety, variety, variety. We think with personalized learning that
variety is the spice of life. And so one form of variety--which is an important
form--is placing students where it is they need to be. And so that is important,
and placement is a key piece. But if we're so focused on variety, we really
miss what personalized learning can do. It needs to make learning a personal
thing. If we go a little extreme on this idea of variety and personalized
learning, we start to have conversations about learning styles. And it's still
very common for us to think "Well, my learning style is different than your
learning style." But we've debunked that. Just because you have a preference
when you select from a menu how you want to learn something doesn't mean learning
is actually improved because you use it. And so, we spend so much time on variety
because one-size-fits-all feels robotic, but I don't think you have to. There's a
step here, where you want learning to be a human experience and a non-robotic
experience, but I don't just throw any and everything out. Personalized learning
to me is student-centered learning. It's not about what I learn, it's about how I
learn it. That piece is often missed when we do all that variety. And so,
that's where I think the reason EdTech has such a push on personalized learning,
is it's a very scalable environment to provide variety. But variety itself
could just be confused as a shotgun approach hoping that something
eventually sticks. Absolutely, and you mentioned you know in
terms of the environment itself not being enough, and that to me ties into
the customization issue that you just talked about as well. It seems like a lot
of times when we get into personalized learning, the elements of it that people
consider personalized are the things that are almost distractions from what
the actual task is. Whether it's the environment itself, that there's too much
going on it's too busy, there's too many things to focus on that are not
the actual tasks that the kids need to be focused on. And then the customization
options and things like that are just bells and whistles that are
not inherent to the learning that needs to be happening. Yes I think that's a
really great way to say it. I mean, there's nothing wrong with bells and whistles on
some things in of themselves, but if I buy a car with all the bells and
whistles but I can't leave my yard because it never starts, it doesn't
matter. So, fundamentally I need my vehicle to serve the purpose, the primary
purpose for which it was intended. And then, personalizing in terms of
customizing, "Give me what I want," you really start to realize well if learning
is already happening, then all of this stuff ends up taking time and we have
very limited school time. Families are busy when they're out of school. It's
not like because we're going to add a new thing where I get to customize this
everything, that somehow I magically get more learning time to happen. And so,
because we're constrained within specific periods of time--we only have so
much access to really deep rich math experiences--we need to make sure that
the heart of a student's cognitive load are on the things that matter. And too
much of it isn't. So, placement is important because
I'm trying to place you in to the piece of learning that's most effective and
important for you. So there is obviously some value there. But I think what's even
more important than just getting the placement is what happens when you're
there. Are you building this mastery based learning,
where personalized learning now can be something more about learning at my own
pace. Not that I'm going to put out less effort, but different things are going to
catch me in different ways. I might go through one learning concept
quickly, and [due to] life experiences or whatnot, I grab it. And other things I
struggle on. And so really to be personalized learning I think there's a
moment here where we need to in the moment be providing the right amount of
time and the right kind of feedback for learning to happen. And if it takes me a
little more time or my misconceptions are a little bit stronger--not a problem,
because you have the time. And so we don't just say "Well, you got
three questions right--I'm gonna give you the harder one." And then you get to the
harder one and I go "Well, you've messed up a couple of times--I'm gonna go back to the
easier one." Right. I should have already mastered the easy ones--why am I
going back to it? You're asking me to make a connection between the easier
one and the harder one that I obviously can't make. Because if I could have made
it, I would have. And so this idea of "Oh well, this is too hard, let me just give you
the one that you're successful on," takes away the requirement when deep learning
happens where I'm in the midst of it, and I start to feel that frustration come on
and building a desire that turns frustration into that thirst for
challenge. Which you know we say a lot around MIND is you always want to be
turning frustration into a thirst for challenge. It's not about getting rid of
frustration, it's about managing that. Because the problems that we need to
solve as a society that are going to become increasingly necessary for humans
to tackle, are tough ones. If they weren't tough, they probably would have already
been solved. Absolutely. So we have really difficult problems to
tackle and solve, and we need to be building up persistence and perseverance
on problems that were stuck on. And we need to have environments that are rich
with decision making. See if you make different decisions than I do and we
both get feedback on it, that's like perfect personalized learning, because I
can monitor your decisions or you can monitor my decisions and provide the
feedback when and where and how I might need it.
If what I'm doing is calculating and entering an answer and the response
is "Yes you got it," "No you didn't, would you like to try a hint," what decision
did I make to make that hint valuable? And the answer that is I didn't
make any decision to make that answer valuable because you got the exact same
hint that I did. Right. What feedback am I getting off of that decision
to be able to then puzzle through that and kind of problem solve through
that? And what model do I have to even start making the right decisions in?
I could just be fundamentally interpreting the problem in some
different way. And so, creating really powerful models of learning that get to
the heart of what's happening, that are rich with decision making--not
instructions--where I'm having to think and reason and problem solve time and
time again my way through, and getting feedback on the choices that I'm making--
that feels like a pretty nice poster child if you will for personalized
learning. And all this other stuff where you can have rewinding or choice or
whatnot--you might get some value on there and I could imagine that there's a
chance that they could enhance a solution that looked like that. We do
this in everyday life, if we're really stuck on something. We take a break and
we go do something else. But if the moments of learning aren't valuable in
and of themselves, it doesn't matter which moments I choose. Right. They're
going to be just as non-valuable. And so this is where when I when I think of
personalized learning I really dive into what is the goal. The goal was not to be
the antithesis of one-size-fits-all. It was we found that our approach to
learning wasn't working, and we kind of did a full 180 and tried to do
everything else, and we ended up adding fluff to it. The goal is still the same
as it always was--all students can and learn in a deep and meaningful way. And
we as a society owe it to ourselves, to our future generation, to our current
students to provide every opportunity for them to maximize learning. So
learning still needs to happen. And if that's the ultimate goal, no matter what
buzzword we use under that goal, we can analyze--is this buzzword really
being acted appropriately, or did it just become really popular and then therefore
cliche? What I'm hearing from you as we kind of talk about this stuff is that
when you're trying to implement personalized learning--when you're trying
to create a school culture that embraces personalized learning--a lot of it is
going back to that fundamental question, and making sure that you're asking
yourself the right questions as you embark upon this journey, so that you
don't get caught up in the buzzword, so that you don't get caught up in whatever
the flavor of the month is, but you keep coming back to that core concept. Yes, and
this is one of the reasons--I mean, I was in academics for a while and
taught at the university level, and tutoring businesses and all this sort of
piece, and what I found was the brilliance of really focusing on solving
a problem. And so, MIND exists for that purpose--we are a non-profit, and so our
stakeholders are the students. And so, the buzzwords many times bother me a little
bit because they get in the way. They become rhetoric in the place of action.
And if we could really start to nail down towards solving the problem, we
would be putting a pressure on a lot of different groups, we'd be putting pressure
on ourselves to really evaluate and make sure what we're doing is successful. And
so when you take that approach, personalized learning isn't about
technology, even though it's the common phrase in EdTech.
Personalized learning isn't the device, it's not the choice over what I learned
and what I don't. That is a personal choice on what I learn, but that doesn't
mean that I actually learned it. Right. The ability to rewind or learning
preferences--none of these things are proving the results. And so in order to
prove the results, we really want to go back to the basics in a way. We
want to make sure that students are making a lot of decisions, because that
is an action.You can measure behavior. You can give feedback on that. A
student's decision--when they're making a lot of them over and over--you're getting
rapid prototyping on your decisions. Just like an entrepreneurial approach, where
you don't plan out this whole master plan and expect that it's just going to
work, 21st century entrepreneurship is requiring more and more
to create assumptions and test them as quickly as possible, and make sure that
by the time you scale a solution, it actually solved the problem it was
trying to scale. That rapid iteration where I'm making a lot of decisions,
getting meaningful and formative feedback as I do it within models that
allow me to interpret what's happening--we're not just gonna throw symbols on
the screen and hope that you memorize--all of those pieces are core and crucial
elements in learning. And it makes learning personal when I make a lot of
decisions that way, not only am I engaging my mind actively and creating--I
perceive something and I make an action, I get feedback on my choices.
I learn very quickly that failure is okay, because the natural process of
learning when I don't have instructions to follow--I have to take that
explorative mind and know that I don't even know what's happening here, and so I
know I'm going to mess up. Right, it's all part of the process. Yes, and it's
important--it's a hugely important piece of the process. And so as we're
evaluating solutions that tout personalized learning, I would encourage
all of us to think a little bit about where they are saying they're being
personal. Are they just allowing a student to select the environment in
which they learn? Are they just adapting based on placements or allowing you to
rewind and things like that? You're not going to get maximal results for the
precious school time or the time you have at home. And so you're going to
create such minimal improvements--if any--that in a way you're really starting to
border on wasting a student's time. Really what you want in personalized
learning--and to me this is one of the big keys--is adapting at the moment of
learning. If I am constantly in an environment where like I said I'm
overestimating the answer, I need to start to get feedback that I'm
overestimating, and start to adjust at the moment that learning is happening.
We need to adapt to the decisions that students are making, and hints aren't
going to do that. How do you try it three times and say "Would you like the hint?" And
then I don't get it, and I have to read a paragraph? It's not
going to cut it--the moment of learning has already passed. Right. If I've made
the choice then I have to go read a paragraph, I'm delaying the feedback from
the decision so far that it's almost ineffective. It needs to be right there
at the moment. And that to me really embodies what personalized learning
should entail. We have the tools and the time and the feedback necessary to make
learning a successful experience for myself as a student. I appreciate you
kind of taking the time to take a deep dive into that today, because I know just
in talking with you that you are super passionate about that, and there
are a lot of misconceptions out there about personalized learning. As you said
the term often gets in the way of what we should really be focusing on. And so I
think as we kind of wind down are there any other final thoughts that you have
on that? Or takeaways for people who might be listening and sort of
thinking about how they're incorporating these concepts into their own
environment, and how they're maybe as a school kind of embarking on this journey
now? A really important takeaway in general is looking at student behavior.
So, how are how are they behaving? Not just 'are they goofing off' behavior, which
always happens in a group of students. Happens in a small group short and in
large groups. But student behavior in terms of if they're entering something
and on a computer, are they just, you know, typing a number on the keyboard and
then just kind of hitting--look at what they're doing. Learning by doing is
a crucial component, but it doesn't mean that you're always doing
well. Practice doesn't make perfect. Perfect practice makes perfect. And so
when we say learning by doing I really mean learning by doing pertinent tasks--
things that are core to where it is that you're going. And so look at student
behavior in those moments of learning, and start to adapt suggestions and
feedback based on that. The answer that the student gives is a
result of their behavior. The answer being wrong isn't the core problem--
there's something else causing it. And so you can backtrack that usually to how
are people interacting with something. And if you can change those
interactions in a way that's really powerful, then you're going to see the
end result change as well. So really on everything--every buzz word, everything
that is a cliche, everything that was big in the '90s or early '00s and we're not
trying--all of those things were probably taking a shotgun approach to do
something. But really focus on what the goal is, what the problem is we're trying
to solve, and what is it the student is doing actively in that process. Are they
doing tasks pertinent to the learning? If they're not you're not going to see the
results you want. Well, I really appreciate you taking time to take
this deep dive again today, and and I'm sure that we will be having future
conversations about whether it be personalized learning or different
aspects of subjects that we're tackling here at MIND I'll be looking forward to
sitting down with you again. I'm really exciting to be a ton of fun. Thank you
for listening to the Inside Our MIND podcast. You can learn more about MIND
and find the show notes for this episode at mindresearch.org. You can also follow
us on Twitter @MIND_Research research and on Facebook at JIJI Math. If
you'd like to learn more about our visual instructional program ST Math,
visit STMathcom.
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