This discussion explores the evolution of Open Educational Resources (OER) and open pedagogy, particularly how generative AI can significantly enhance their impact by enabling personalized, dynamic learning experiences and new forms of content creation.
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How might generative AI take the ideas
behind open education even further?
[music] We're exploring what that could
Welcome to Speaking of Higher Ed. I'm
Andrew Everett and this is episode 36.
Today you'll hear from Dr. David Wy,
associate professor and academic affairs
fellow for AI in education at Marshall University.
University.
Dr. Wy, often called a pioneer of the
open educational resources movement,
joins us to discuss the intersection of
openness, pedigogy, and generative AI.
Now, here's my colleague Arthur
Takahashi with the full conversation.
>> Hello everyone. Welcome to Speaking of
Higher Ed. Our guest today is Dr. David
Wy, associate professor and academic
affairs fellow for AI and education at
Marshall University. Dr. WY is widely
recognized as one of the founders of the
open educational resources movement or
OEER movement. In 1998, he created one
of the first open licenses for content
and that work helped pave the way for
the creative common licenses that we we
know and we uh many of us use today.
He's held fellowships with creative
comments and also with Stanford's center
for internet and society. and his work
lives at the intersection of generative
AI, open education, entrepreneurship,
instructional design, and student
success. He's been a creative force for
innovation in education, co-founding
organizations such as Lumen Learning,
Degreed, and Mountain Heights Academy.
Dr. Wy, welcome to our podcast. We are
super excited to have you in our episode today.
today.
>> Thanks. I'm super excited to be here. I
appreciate the invitation. All
right. [snorts]
So, the first question that I have for
you and that's usually the question that
we start our podcast is uh asking our
guests um you know how you uh have
gotten to the position that you are in
today. So, kind of tell us a little bit
about your journey through um education,
instructional design and also um uh open
education and finally generative AI.
>> Sure. Well, at let's [clears throat]
see, at a very high level, um, my
undergraduate degree is in music from
Marshall University. Um, this was in the
mid 1990s
and I was a student on campus. I was a
student when the internet first came to
campus. So, I remember the time pre-
internet and then and then post internet
and saw those changes and spent some
time working as the first uh university
web master at Marshall back in the '90s.
And as I was when I finished my degree
in music, I realized that my real love I
love music a lot, but I was really
enjoying the work I was doing, you know,
around technology and education. So I
went and did a PhD in instructional
psychology and technology at Brigham
Young, which is kind of part
instructional design, part uh computer
science, part edge, you know, kind of a
an amalgamation of a program. Terrific
program. Um and then for a dozen years I
worked as a tenure track facto
at Utah State and then uh as tenure
track faculty at Utah State and then
again at Brigham Young teaching um
instructional design uh open education
uh grant writing um some kind of social
entrepreneurship for instructional
design or ed people with an interest in
edtech classes like that and then so
let's see so I finished my PhD in 2000.
And then at the end of 2012, a friend of
mine and I, Kim Thanos, started Lumen
Learning, which you mentioned a moment
ago. And so after a dozen years kind of
inside the academy doing some
entrepreneurship things on the side, I
flipped over and became full-time
entrepreneur working with Kim and our
startup. Uh but continued to teach as an
adjunct on the side because I couldn't
really extract myself um from higher ed
because I just love teaching too much.
Uh, and then just to put a bow on it and
not go uh too long in this story, um,
just this past summer in 2025, I flipped
back over and now I'm back full-time at
a university back at Marshall University
where I did my undergrad uh, here in
West Virginia and now teaching in a
department um, that covers marketing,
management, information systems, and
entrepreneurship. And I teach primarily
in MIS and entrepreneurship parts of the program.
program.
Okay. Yes. So, um, back in 1998, uh,
when you first created this, uh, open
license, uh, you know, certainly one of
the first, but perhaps maybe the first
open license for content, uh, ever. Um,
what are some things that you've learned
back then that, uh, kind of have has
guided your thinking to this day? M
you know I think the um I think the
thing that I was most excited about
during that period was um I had this I
had a realization one day and I this is
certainly I was not the first person to
understand this. A lot of people before
me had understood this. Economists have
a whole vocabulary for it and way of
talking about it. But I remember I was
working as the uh as the web master at
Marshall University like I was talking
about. So this would have been in 97
and I was developing a uh JavaScript
calculator to go in a web page which was
the very height of high-tech at at the
time. And uh and I just remember I
remember having this moment of realizing
that that JavaScript calculator was very
different from a physical calculator. in
that maybe if you're in a classroom that
only has five physical calculators, you
have to wait for the at maybe as a
elementary school student or something,
you have to wait for the calculator to
come around for it to get your turn kind
of working on it. But when you take that
same capability and you make it digital
and post it online, a million people can
all use it at the same time.
And that just seemed so transformative
and powerful to me, that idea that if we
can figure out how to create, if we can
find the resources to create the thing
and post it online, then everyone could
benefit from it for a very long time
after that. So, it wasn't very long
after I had that realization that uh the
the group in February of 1998, a group
of people got together to have a
strategy session about what was going on
with what at the time was called free
software. And coming out of that
February meeting, they said, "We think
free software is a problematic name and
brand for a couple of reasons, and we
want to try to rebrand it as open-source
software." and talk about the very
pragmatic benefits that you get from
sharing and being open in that way. Um,
and so I was really inspired by that
work and that work together with the uh
with that realization around the
calculator led me to create that first
open license and really start advocating
um well for anything that's not software
you know can be covered by these open
content licenses like the creative
common license but my real interest has
always been in education. So if we can
find the funding to create that
textbook, then we can put it online and
it can bless the lives of millions of
people, right? It can even be translated
into other languages because of the the
five art permissions you get with open
licenses and things like that. But just
this idea that technology
plus uh licensing can allow us to share
and be generous in this way that was
never possible before. That's really the
kind of uh the initial motivating thing
for me back then that has carried
through uh my work until today.
>> Yeah. And uh that kind of leads leads me
into the next question um because you've
actually given us a lot of the
vocabulary that we still use in open
pedagogy and uh the open education
today. So one of the things uh that I
had always heard and then learned that
it came from you but the the idea of the
five Rs. So you've defined uh OEER
through the five R permissions. Uh for
the listeners and the viewers who don't
know what those five R permissions of
OER, what they actually are, could you
just briefly explain what they are and
how impactful they can be for pedagogy?
>> Sure. So the five Rs, I'll just list
them real quick and then I'll define
them are retain and then revise, remix,
reuse, and redistribute.
And so retain means that well and let me
say let me step back even further to say
when you're looking at an educational resource
resource
um it could be a video could be a
textbook chapter whatever if you have
permission to engage in these five R
activities then I would say that that
resource is an OEER.
Um, so the first of those is retain. And
what retain means is you have to be able
to download your own copy of that
resource and keep it forever and then
[clears throat] be able to do certain
other things with it. and retain really.
Initially the framework was the four Rs
framework and it was four Rs for several years
years
and then as business models started
changing with Netflix, with Spotify,
with academic publishers
uh and libraries not wanting to sell you
DVDs or sell you music or sell you
journals but just rent access to them.
it became clear that if if we ended up
in a world where where I could only
access things but I could never own
things, I wouldn't be able to do the
four R. Uh I wouldn't be able to revise,
remix, you know, redistribute and reuse.
And so uh so I added this fifth R which
turns out to be prerequisite to the
other four. You have to be able to make
your own copy, download it, and keep it.
And it can't delete itself after 6
months like a textbook rental might do
off of your Kindle or something else.
has to be real just old-fashioned
private property. You control your copy.
Then with that copy, you can do these
four other things. You can revise it,
which means you can open it up and
fiddle with its insides. You might want
to adjust the reading level because it's
written at a high reading level and
maybe your students have a slightly
lower reading level, so you want to
adjust it down. Um, you can edit it,
maybe take out some examples that are in
there, put new examples in that speak
more directly to your students. So you
can So revise is the first, remix is the
second, and that's where I can take two
or more openlylicicensed things and make
one new thing out of them. And if
they're all openly licensed in
compatible ways, then then remixing is
something that I can do. Um, the third
of those original four Rs is uh reuse.
So either with the verbatim copy that I
made originally or my revised copy or my
remixed copy, I have to be able to go
out into the world and use it publicly.
Uh whether it's in my class or in a talk
that I'm giving or on a YouTube video
that that I might want to post publicly,
I have to be able to publicly um display
and use uh the object or the resource.
And then the last one is redistribute. I
have to be able to give other people
permission to download what I've created
and that's them retaining and then the
whole cycle starts again. So those are
the five Rs
>> and uh you've also defined a uh
different kind of pedagogy based on
those five Rs. Initially you called that
open pedagogy but uh you you you changed
the term to OEER enabled pedagogy. M
>> uh for faculty who don't know what OER
enabled pedagogy is, could you uh
briefly explain uh that that term?
>> Sure. So the the kind of the simplest
definition there is any kind of anything
you can do in support of teaching and
learning. That's kind of the pedigogy
part of it. anything you can do in
supportive teaching and learning when
you have five R permissions in the
resources that you're using that you
can't do without those five R
permissions I would say is OAR it's
pedigogy that's enabled by the five Rs
of OEER so for example if um
uh in the past I have adopted an open
textbook um and then worked with my
students over a series of semesters is
to rewrite the textbook. I mentioned a
minute ago changing out examples in the
textbook. So, um the first time I did
this was in with in a project management
class I was teaching and the examples
were all kind of written for a business
school context and they weren't relating
to my students who are instructional designers.
designers.
>> So, we pulled all those examples out and
wrote new examples of project management
that an instructional designer might
care about. So, you're working with the
SMEI who's supposed to be writing
assessment items for you and they're
late. You know, what what what are you
going to do now? Um, so that's a
process, that's a kind of pedigogy of
rewriting the core course materials that
I can engage in when my course materials
are licensed in a way that gives me
those five art permissions that I that's
something I can't do if I would have
adopted um traditionally copyrighted
material or TCM, which is the opposite
of of OEER. So there there there's a
family of things that you can do when
you've adopted OAR that you can't do
when you've adopted TCM. And that's what
OAR enabled pedigogy is about. Yeah. And
uh one of the things that I have read in
in um some of your blog posts and and
seen in some of your presentations is
this relationship between OEAR enabled
pedagogy and constructionist uh theory.
uh and it seems like you tend to focus
on remix and revise as like great ways
to do uh you know teaching and learning
but could you explain that a little bit?
>> Yeah. Um actually in uh in one of the
papers a graduate student of mine uh
John Hilton who has gone on to become a
a a great scholar in his own right um
wrote this paper on OAR enabled pedigogy
where we looked at different kinds of
assessment and what we kind of thought
of as traditional assessment authentic
assessment more constructivist approach
to assessment and then what we called um
a renewable
uh assessment.
And the idea there is um is grounded in
a critique of what I um [clears throat]
somewhat jokingly refer to as disposable
assessments. So a disposable assessment
is uh or disposable assignment is when I
ask you to do some work and you know and
I know that after you do the work and
after I grade the work, you're going to
throw away the work and never look at it
again. And uh that seems like it's kind
of a shame cuz you're [clears throat]
going to invest a lot of time and
effort. I'm gonna invest time and effort
and then it's going to go into the
garbage can. So the the idea with uh
with this uh renewable assessment
approach was what if we had students
spend that time and effort creating
things that would actually add value to
the world instead of creating things
that they were going to throw away at
the end of that process. And as soon as
you start to talk about uh kind of
creation as a form of learning and form
of assessment, it starts to tie you into
that constructionist
uh you know kind of tradition. And so in
that paper, we walked through um how you
kind of layering on different pieces of
going from a typical assessment to one
that's actually going to add value to
the world through something that you are
creating, revising, remixing, but then
eventually you're putting an open
license on so that it can be the
beginning of the next person's uh you
know authentic constructionist renewable
assessment that they might do because
all of open is about creating, revising,
remixing, and sharing so that your
output can be the next person's input
and so that that the effects and the
benefit and the impact of that can kind
of grow and propagate outward. Um, so I
I don't know if that's a a an answer to
the question you're actually asking, but
um that's where that connects.
>> Yeah. And the more that I thought about
that, you know, this relationship
between the uh five Rs and uh
constructionist theory, you know, the
more the more I keep going back to the
revise and remix portions of it for for
for cognitive learning, right? Uh but
there's also motivational aspect if
you're thinking about redistributing
that to the world like adding that u you
know value to the world as as you've mentioned.
mentioned.
>> Um so it's it's just good pedagogy.
>> Yeah. I mean, in the constructionist
framework, you could always have your
students make new things, right? But in
this kind of OAR enabled framework, you
can have them make new things from
scratch or revise things or remix
things, right? It just unlocks more
kinds of things that you can do. And um
there was one other thought I had, but
I've lost it now.
>> Yeah. Um and you know in your experience
working in this world of open pedagogy
uh is there something that um people
tend to misunderstand about OAR that uh
you know perhaps you know we we should
be addressing?
>> Yeah. Um I would say the biggest
misunderstanding about OEER is that um
so many of the people that I have talked
to over the years and people uh in
survey responses that I you know in the
results of surveys that I've seen people
think that OEAR are resources that are free
free
and this is in many ways the same
problem that the free software and
open-source software people were were
kind of fighting back in the day. the
name that name free software just can
confuse people. And so this idea that
any resource that's free is an open
educational resource is problematic in a
whole bunch of ways. Um because if you
think about it, the entire public facing
internet, a trillion pages, they're all
free for you to access.
So if an OAR was just something that was
free for me to access, the whole
internet would be OAR. We wouldn't need
another we wouldn't need another word uh
to describe it. We would just say the
internet instead of saying open
educational resources.
>> Um a lot of the internet is
traditionally copyrighted material, not
OEER, it's TCM. um a lot of resources
available in the library to students
even though you know they pay a fee they
pay a library fee which may or may not
be clear to them as they're paying their
bundle of fees but um their experience
of library resources is that they're free
free
>> um but the overwhelming majority of them
are also TCM not OEER right so um if I
think oh I'm going to adopt OEER are and
I adopt a bunch of library resources and
New York Times articles from the website
and other things. Um I can't engage in
any of the five Rs with any of those
materials. I can't do any OAR enabled
pedigogy. I don't get any of the
flexibility. Um it's it's a very very
very impoverished view of what open is
supposed to be about. open is supposed
to be about the permissions to share and
to build and revise and remix that that
we've been talking about. So I'd say the
number one confusion is people think,
oh, anything that's free is an OEER and
then they say, oh, I switched my class
to OAR, but actually their entire class
is TCM. It's all it's freely available,
but in their mind since it's free, it's
OEAR. Um and so now they think they
they're using OAR but they're missing
all the benefits of using OAR.
>> So it's free but they can't apply the
five R permissions. >> Right.
>> Right.
>> Uh so something else that you've
mentioned uh in um some of your
presentations as well is how there seems
to be also this misconception that uh
OAR also leads to better learning. M
>> um could you address that cuz you've
mentioned that there's some serious
methodological issues with some of the
research that point to that. Um but you
know in addition to that like how could
faculty instructors uh think of using
OEER to really enhance learning if you
know if OAR on its own cannot enhance learning
learning
>> right well maybe the best way to think
about that is let me grab a textbook
off the shelf here.
So, here's a here's a book about how to
write um assessments
um that I used when I taught the uh
assessment course. Um so, this book to
some greater or lesser degree,
we could do research and find out what
degree it is, but to some degree
supports student learning of this
content. Right now, if I open this book
and I go to the copyright page here near
the front and if I scratch out, let's
just imagine that I actually had legal
permission to do this. I scratch out
where it says copyright and I write in
creative common attribution. Okay, so
now it's an OEER.
Is it more effective now than it was 30
seconds ago when it was a TCM?
>> Cognitive speaking though. It's
literally exactly the same, right? So
there's there's kind of no reason
to believe that just because something
is open is going to make it more
effective than it being traditionally
copyrighted. And even um you know there
advocates in the open space for a while
and you'll actually still hear some of
them make this argument. I just I guess
they don't know the research. Um, but
for a while there was kind of a line of
thought that said,
um, if a textbook is too expensive for
me to be able to afford it, then I'm not
going to be able to learn the things I
need to learn. And so even though it's
cognitively the same, whether I have
access to it or not makes such a big
difference that I'll be able to go
conduct research and find out that if
you assign OEAR and I assign TCM, your
students are going to do better than
mine because more of them will have
access to it. But there was a really
terrific paper um out of OpenStacks uh
several years ago led by their director
of research um that kind of took the
reader through a little more carefully
through that thinking um and they said
you know imagine a typical now I'm I'm
kind of summarizing obviously here but
you know if you imagine a typical class
with 50 students in it how many of those
students are either going to be able to
afford the book or RO1 one from a friend
or access one at the library or even uh
you know whatever method they're going
to use. How many of them are going to be
able to get access to the book one way
or another versus the students that will
literally have zero access for the
entire semester
and that second group is going to be
pretty small. So out of 50 students say
it's five. So when that instructor
adopts OEER
um the increase in access only happens
for 10% of the students. It doesn't
affect the other 45 students. They were
going to find survey to get access to
the course.
So now, so I've got this population and
from like a research perspective, like
I've given my treatment to 10% of them
and now I want to measure the entire
population and look to see if there's a
noticeable change in their learning.
Well, those 45 students aren't going to
have any change attributable to access
because they were going to have access
before. these last five, I mean maybe
maybe their grades will go from 50% to
90% or 50% to 95%.
>> But having five students out of 50
experience that kind of growth is very
very very rarely going to show up when
you go to do a research study. it's just
not enough of a difference given how big
the whole group is and you don't know
ahead of time who those students would
be to try to isolate them into a
subgroup or something like that. So
>> the uh this open stacks research talks
about what they call the access
hypothesis that if we increase access
we'll be able to see measurable gains in
student learning and then they show why
most of the time that's it's just not
true. So when you do see an instructor
who's adopted OAR, faculty using OAR,
compared to other faculty who aren't
using OAR and you see this big
difference in the amount of learning
that's happening there, the odds are
extraordinarily high that what's driving
that difference is is not the licensing
of the materials. It's maybe this
teacher, it just so happens that the
teacher who adopted OAR also does a lot
of active learning in their classroom or
the faculty who adopted TCM just
lectures all the time. Um or you know
there are so many other factors that
affect student learning other than just
the licensing of the textbook that the
instructor chooses. um that if you go
back and look at these studies and I I
recently uh I wrote about this and kind
of said there are three questions to to
ask yourself when you read research
about OAR efficacy. The first is if it
is based on this idea of the kind of
access hypothesis that the open stacks
uh team outlined, has the researcher
done anything to try to determine ahead
of time how much of the population do we
really believe ought to be affected by
it instead of pretending that the entire
class will benefit from OEER adoption
because the majority of them were going
to have access to the material anyway.
The second question is to ask about um
whether there was any uh randomization
or any attempt to uh establish
equivalence between the teachers in the
two groups because almost every research
study you'll read compares faculty
who've adopted OAR to faculty who adopt
TCM. But they make those choices themselves.
themselves.
I choose to adopt OAR. I choose to adopt
TCM. not put into a random randomly
assigned group. Um most studies don't do
any kind of like propensity score
matching to say this faculty is kind of
equivalent to this one so we'll match
them up. So what you get is it's like
doing a health study where people get to
choose whether they want to exercise or
not and then but you don't randomly
assign them. Then you go look and see
was one group healthier than another.
was surprised the group who chooses you
who chose to exercise was healthier than
the group who who didn't choose to. So
but the effect of the teacher is
perfectly confounded with the effect of
the material that they have chosen. And
then the [clears throat] the third so
the second question is to ask is there
any control for teacher effect and then
the third question is is there any
control in the study um for the
instructional design of the materials or
of the the pedigogy that's used in the
classroom and you could imagine 10 other
questions that you could ask but if you
just ask those three of like go think of
your favorite OEER research study that
shows an improvement in student learning
and then ask those three questions. And
the answer to all three of the questions
is probably no. And if it's no,
if if the answer to any of them is no,
then the paper doesn't actually tell you
that OEER causes a difference. It tells
you that OAR might cause a difference or
teachers might cause a difference or OAR
might cause a difference or
instructional design might cause a
difference. So, so I I've been trying to
encourage researchers in the field to be
more rigorous in the design of their
studies. There have been a handful of
really what I would consider really
well-designed, rigorously controlled
studies and they show no significant
difference, which is what we would
expect because if I change the copyright
page out of the book and I keep the
teacher the same, the instructional
design the same, everything else the
same, we ought to expect the outcomes to
be the same. So to the second part of
your question about what should we do um
in order to try to improve outcomes is
there's a whole body of research around
what are called evidence-based teaching
practices ways of teaching that we know
from good research are associated with
better student outcomes. So I think the
question with OEER is when I have OEER
which is only different from TCM in that
it gives me these five R permissions right
right
>> how can I leverage those five R
permissions in order to implement more
of these evidence-based teaching
practices because I know that this works
but maybe I wasn't able to implement it
before because the way my curriculum was
designed was at odds with this
evidence-based practice. Now if I have
permission to make these changes that I
can change the open textbook or whatever
o OEAR I'm using to enact more of these
evidence-based practices then you know
then we should expect to see differences
in outcomes because we're using more
evidence-based practices in our teaching
>> and I think that's a a perfect
transition to uh the next part of the
conversation which is with the advent of
generative AI
um how has that changed your approach to
OAR and also OAR enabled pedagogy?
>> So um I will admit that this is still a
topic that I'm actively thinking about
and I I think that's true for most
people. I mean AI is still advancing
very rapidly. there's new capabilities
all the time and as an educational
technologist I just look at every new
capability like how can I use that
capability you know to drive student
learning better um I'll say that
probably the primary way that it's
changed my thinking about OEER is um
about what
uh what's the right word ideal is a
little too strong but what what should
the ideal OEER look like and I think
Maybe 3 years ago, we would have said,
you know, it it looks like a textbook or
it looks like um courseware like a myab
or uh or something like that, but it's
openly licensed. That's what the ideal
OAR is.
Now today in you know toward the end of
2025 I think the ideal OAR looks more
like a very very sophisticated prompt
maybe 2 or 3,000 words long that I can
give to my students that they can enter
into a generative AI and then they might
experience a 20 or 30 minute long
interactive study session where uh
explanations are customized to things
that they care about and find
interesting or relevant. There's lots of
formative assessment along the way. U
misunderstandings are diagnosed kind of
right as they happen and corrected. Um
the idea that if I can take a fixed
amount of time and write
kind of like a traditional OEER where I
individually write every word that a
student will ever read. I call it an
open textbook and I give it to them.
um there's a certain amount of learning
that can happen there.
But if instead if I spend that same
amount of time writing a prompt that can
create a customized version of that
experience for every student who
interacts with it. that seems like it's
a much better use of my time to um
instead of writing a textbook chapter to
write a prompt that would lead a student
through a conversation about all the
topics that would have been in that
chapter. But we'll begin by asking them,
tell me some things you're interested
in. Oh, you like music, you like
basketball, you like hiking. Okay, those
are the examples I'll use as I explain
these topics to you now. Okay, we just
finished talking about this. Uh let me
ask you a question. What did you know
what do you think the relationship
between supply and demand really is
about? Open-ended answer. Uh so that
first part was right, but the second
part isn't quite right. Let me tell you
more about the second part. Right? That
whole just that conversational learning.
Um to me that's what the future of OAR
is about is about creating those prompts
as opposed to creating static textbook
chapters. Mhm.
>> Um in addition to there are a number of
um what they call open weights
uh models, language models that where
you can actually revise and remix the AI
itself, the language model to get it to
behave more pedagogically,
to have more disciplinary knowledge,
things like that. So, I'm I'm very
excited about the kind of next
generation of OAR being these prompts
that are openly licensed so that they
can be revised and remixed because maybe
I'm using Chat GPT and you're using
Claude and you're going to need to
refine it a little bit to get the
results that you want. Um, but also
these open models that you can download
and run right on your desktop or right
on your laptop that are private because
they run locally and no data ever goes
up into the cloud.
Power usage kind of implications because
I'm just doing it on my laptop instead
of up in the cloud again.
>> Mhm. I think they're it it's a com it's
a it's a is it I think it's a kind of a
complete reconceptualization of what OAR
really look like cuz in the past we've
created a static artifact and we've
applied an open license to it. Then
we've told people you can take this
artifact and make all the copies of it
that you want. But now instead of
creating static artifacts, we can create recipes
recipes
for experiences and we can openly
license those and distribute those. And
instead of my learning experience being,
you know, reading 10 pages of static
words, it can be very conversational and
I can explore what I'm curious about and
poke and prod at this and get
corrections when my when my
understanding is inaccurate. like that
just seems so much more powerful to me.
Um, and that's certainly what I've been
doing in the in the OAR creation work
that I've been doing and encouraging
anybody who will listen to the same.
>> Yes. So, there are a lot of things going
on in your answer here that I'm super
excited about. So, uh this idea of
having prompts as OAR uh and and us as
instructors publishing those prompts and
also uh open weights uh that's what you
call generative OAR, right? Mhm.
>> Okay. And uh the idea of creating the
prompts and assigning the prompts to our
students uh you've mentioned this
concept of generative textbook. Is that
what you're uh referring to when when
you talk about these uh prompts? Um
so
when I talk about the prompts so I would
say that there are um so there's a site
generative textbooks.org or where I'm
doing some active experimenting with
this idea, >> okay,
>> okay,
>> that that you can go and look at. And
what you'll see there is that um
basically as a as a learner, I come in
and say this is the generative textbook
I want to study from and this is the
chapter that I want to study and this is
the kind of learning activity that I
want to do. I either want to have a
conversation or I want you I want the AI
to build me uh on the fly an interactive
simulation where I can slide sliders and
change variables and see how relation
causal relationships play out between
different concepts. Um or uh the third
is a um a retrieval practice kind of
exercise where the practice quiz isn't
multiple choice, but it's all open-ended
and there's immediate feedback um along
the way. And if you think about kind of
those three choices that the learner
makes, they're really kind of
establishing the context
plus the prompt and then you have the
weights on the other side of it. So the
prompt says here's the activity I want
to engage in. Have a conversation with
me where you explain
we you know what a prompt looks like
right? But you also together with that
prompt you have to combine it with
enough context
so that the model can give you accurate
responses. So if you play around on the
generative textbook.org site you'll see
that what the context looks like is a a
detailed set of learning outcomes. Here
are all the outcomes that we need or
objectives depend I know there's people
have strong feelings about objectives
versus outcomes but essentially here are
all the things that I need to learn. >> Mhm.
>> Mhm.
>> Right. And then below that um
what looks
looks more like a um like an
encyclopedia encyclopedia entry
something just very kind of dry and factual
factual
just kind of information about each of
those learning outcomes so that when the
model generates its answer it has a high
quality reference that it can look to to
find the information it uses to generate
the answer. So, I'd say you need the
context plus the prompts together. Um,
and then you can use the context and the
prompts. You can use them with a
proprietary model or with an open
weights model. Um, right now,
uh, when you play around in the site,
you'll see that it builds up the it
aggregates all the context and the
prompt into kind of one chunk of text
and then it lets you choose which AI
model you'd like to work with and then
sends you off to that mo. It copies all
of that context and the prompt into your
clipboard and sends you off to whichever
model you choose. You might choose chat
GPT and then when you get there you just
hit paste and enter
>> and then the you know then the learning
experience starts.
>> So for our viewers and listeners um is
that resource openly licensed as well?
Can they go and incorporate that into
their courses?
>> Yeah, so the generativebooks.org or the
source code, the software that runs that
site is all openly licensed. Um, all the
prompts that are in there are openly
licensed. All of the context is openly
licensed. There's a there's a no code
authoring tool where there's just that
looks very much like Pressbooks. Like
there are boxes and you put text in the
boxes and you hit save. So if you can
use Pressbooks, you can use, you know,
or WordPress or anything else like that,
you can use a tool like this.
>> Um, so that's a great
>> Yeah, anybody can register. There's no,
you know, it's all open. Yeah.
>> And uh, you know, another thing that
comes to mind with these more
personalized um, learning experiences is
something that you also uh alluded to in
uh, some of your presentations, but it's
uh, Benjamin Bloom's two sigma uh, problem,
problem,
>> right? Um, I mean that that's what comes
to mind. So, if you could perhaps
explain what what that is and uh, how
perhaps this could be uh, a solution to
to that problem. Yeah. So the the two so
Bloom's two sigma problem. So um Bloom
and his um I believe his graduate
students wrote a series of papers um or
did a series of research studies that
culminated in this 1984 paper that Bloom
wrote called the two sigma problem. And
in that in that body of research, what
they found was that uh there are two
changes that you could make that would
radically improve student learning. The
first is that you could start using a
mastery based approach with students.
And what a mastery based approach, let
me contrast it first with a typical
approach. um a typical approach, you
know, this week we're doing chapter 7
and at the end of the week we take the
chapter 7 quiz and if you fail that's
too bad for you cuz on Monday we start
chapter 8
and you just kind of move through the
course that way and you only get you you
take the chapter 7 quiz one time and if
you fail it, you fail it and but we're
moving on cuz Monday's chapter 8. A
masterybased approach looks more like uh
you know, I'm going to take the chapter
7 quiz. It's going to show me the things
I've mastered and things I haven't
mastered yet. I might get some feedback
about the topics I haven't mastered yet,
be able to go back and study some more,
and then come back and try a different
version of that assessment to and be
able to go through that loop. However
many times it takes me to learn, let me
take as many times as it takes me to
learn to be able to achieve mastery.
So the first thing that Bloom does was
he did in those Bloom and his colleagues
was change from a traditional approach
to a master-based approach. And then the
second thing that they did was um these
students in the in the treatment group
were either like were tutored, but I
don't mean like an afterchool tutor like
from 8 to 3 all day long their all their
learning experience all day every day
was working one-on-one with a tutor or
maybe one-on-one very small group.
Um, and what he found is that if you
combine those two things, if you take
the mastery based approach and this kind
of one-on-one or one on very small
groupoup tutoring approach,
uh, and you look at, um, the the grades
that students receive after those after
their learning experience, the students
in the treatment group and students in
the control group,
the average student, so if you think
about the bell curve, that the average
student in the group that used the masterybased
masterybased
tutorial approach learned as much as the
98th percentile student in the
traditional classroom setting.
And it was about two standard deviations
more than average, which is why it's
called it goes by the two sigma name
because sigma is the the letter that's
used to designate standard deviations.
So that seems like a super exciting
finding. like there's something we can
do that can take the average kid and
make him outperform 98% of other kids.
But they called it the two sigma problem because
because
we can barely afford to put one teacher
in front of 40 kids. We there there's no
way to give every kid their own
individual tutor all day long every day.
So there's what I think is one of the
most inspiring paragraphs anywhere in
research in this in this 84 paper of
Blooms where he calls the field. He
says, "Look, we've shown that kids are
capable of learning so much more than
they're currently learning. And the
reason that they're not is us cuz we
can't figure out how to provide this to
them. So, if someone
could come up with some way to replicate
this kind of mastery based tutorial
approach, but in a way that can work in
a normal classroom used by a normal
teacher, he says, with little or no more
cost and and little or no additional
training [clears throat]
than like that would be miraculous
basically. So it's this kind of call to
everybody to take take up this work. >> Mhm.
>> Mhm.
>> So um so understanding that that for
folks who are listening it probably
becomes kind of obvious what the
connection between that and generative
AI is because there's a lot of talk
about generative AI acting as a tutor.
>> Mhm. And um
if generative AI can be an effective
tutor, then could that be one of the
answers to this challenge that Bloom
laid out for all of us? Now, I don't
know that there are a lot of people who
are excited about the prospect of
sitting and typing to your tutor all day
long and not interacting with another
human being. That doesn't seem like it's
a great learning experience. So there's
um it's it's not just as simple as
saying, "Oh, make a chatbot and now
we've solved Bloom's two sigma problem."
Because part of part of why it works
with a tutor is you establish that
relationship and there's a a human
dynamic there that when you study
closely with a person over time that
develops. Um but it certainly um
generative AI
definitely feels like the most promising
uh kind of attack vector that we've had
on Bloom's two sigma problem in a while.
It seems like there ought to be a way
that we can take generative AI,
change it, wrap some other things around
it, and use that in order to to make
real progress on getting you helping
students really learn all that they can
learn, helping them really achieve their potential.
potential.
So on that note, from an instructional
design standpoint, and I know you've
taught instructional design uh and and
generative AI uh in the past, I think it
was last year, right? Uh generative AI for
for
designers. Yeah.
>> Yeah. So uh what would you what would be
your kind of suggestion or
recommendation for IDs instructional
designers or uh even instructors right
who are designing their own courses um
when it comes to Gen AI and OAR.
Well, well, it's going to be very
closely related to the question from a
few minutes ago about how can we use
OEER to actually improve student
outcomes, which is to say
go back to that base of research about
evidence-based teaching practices
and think about how could I enact this
evidence-based teaching practice using
generative AI because
because
um so I already mentioned retrieval
practice. Let's talk about retrieval
practice for a minute. Um, students love
practice quizzes, practice exams. They
love to be able to do that. They take a
ton of effort to put together on our
part, which is why we don't generally
give them as many practice exams as they
would like for us to. Um but if you and
we know that that kind of retrieval
practice is just about the highest kind
of ROI
uh on your study time compared to any
other technique like
>> rereading the parts of the textbook that
you've highlighted just right
ineffective right
>> so go back to that research about what
really is going to drive student
learning and see you know ask yourself
how could I leverage all these new
capabilities I have in generative AI I
and with the OEER that I might use
together with generative AI, how can I
enact these practices at a greater scale
or more often? Um, so I'll give you an
example. I'm teaching an intro to
databases class this semester. It's one
of the MIS classes here at Marshall. And
for and this exact problem, which is why
it's on my mind. Um, students were
asking, you know, is is there going to
be a practice midterm or is there going
to be a practice midterm? we can have a
chance like to practice.
And so I won't take you through the my
whole thought process, but where it
ended was
I um I sat down and wrote a series of
prompts and I tweaked and tweaked and
refined and refined each of those
prompts until I could get the prompt to
generate a question that I would feel
comfortable including on the midterm.
So this midterm is very projectbased.
It's around doing database design tasks
and data normalization tasks. It's not
multiple choice questions. It's like
here's a database diagram, read and
interpret it kinds of things.
So I worked on these prompts and worked
on them until I got comfortable that
they were creating good questions. And
then I worked on them some more. And
then I went into class one day and I
said, "These are the prompts that I'm
going to use to create the questions on
the midterm.
Here are the prompts. You can take them
and you can use them to generate an
infinite number of practice midterms, as
many as you want. And my commitment to
you is that the questions that show up
on the midterm, I will generate also
using these prompts."
And so I made the midterm from those
prompts and they made I don't know how
many practice midterms from those
prompts. But instead of investing the
work again in creating like a finite,
you know, three specific questions for a
midterm and three other versions of that
question for the midterm, I spend the
time on the prompts,
right? And because I spend the time on
the prompts, they're able to generate
all the practice midterms they want. And
if I'd had a student who had missed that
day and I wanted to give them a
different form of the midterm,
60 seconds, I have another form of the
official midterm that I can use as well, right?
right?
>> Yeah. Love that. >> Yeah.
>> Yeah.
>> Um, okay. So if you could fund one study
next year to advanced uh gener
generative OAR or you know somehow
incorporating Gen AI and OAR together.
Uh what would that study try to test or answer?
answer? >> Oo
>> Oo
like unlimited budget like anything you
want to do like what would be your ideal study?
study?
Um I think today tomorrow I may have a
different answer but um [clears throat]
are you familiar with the idea of
stealth assessment?
>> No from uh from gaming research. So u
people who look at game-based learning
have this idea of stealth assessment
which is that like if I designed this
game that's supposed to help you learn a
certain number of skills or some
knowledge but it's kind of
jolting to play this game and learn all
these things and then turn around and
sit down and take a quiz. Right? In
theory, if the game is really teaching
you and giving you opportunities to
practice all the things you're supposed
to learn, your behavior in the game is
leaving traces of what you know. And I
can actually you can play the game and
then I can go back and review the game
play and use that as the assessment. So
the assessment is totally invisible.
Like you don't even realize that you're
being tested cuz you're just playing the
game. But as you play the game, you're
leaving these traces of did I know this?
Did I know how to do that? Was I able
to? Was I not able to?
>> So you play the game and then and then
the the the gameplay data can be used
for assessment purposes.
>> So I'm I'm really cuz there's a there's
a lot of conversation obviously about
assessment and generative AI and
cheating and academic integrity and
things like that.
I'm I'm really interested in the idea
that there is a a version of stealth
assessment that can happen in the
context of conversational learning with
a generative AI.
So if it's teaching me a topic and
asking me a question and I'm asking it a
follow-up and we're having this
conversation about the topics that I
would have just been reading about in
the textbook. At the end of that
conversation, can I take the transcript
for that conversation and go back and
trace the learning for all the different
topics? And I I'm just going to assume
that maybe you didn't know anything at
the start, but can I see those traces
and where they get to? And at the end,
can the learning experience, the
learning conversation that you had, can
that also serve as the assessment
instead of you doing that and then
turning around and taking a quiz? Mhm.
Mhm.
>> Um if I could fund anything myself,
I think I would fund a study looking at
um a couple of things. One of them would
be like how can we design the most
effective conversational learning
experience possible and to what degree
can we leverage the transcript of that
learning experience as the assessment
data so that I come in I have this
conversation might last half an hour 45
minutes and at the end of the
conversation I'm done my grade is done
there there's there is no additional
assessment because as it was teaching me
it was assessing
And so those get threaded together in a
way that um like how would you use AI to
cheat on that? You know, there's
probably some way to do it, but it's
certainly a lot less vulnerable uh to
cheating than a multiple choice quiz or
an essay question or something. So, I
think there's something real interesting
there at the intersection of kind of
conversation based learning and stealth
assessment. That is what I would want to
fund if I had all the money in the
world. Yeah, I love that that idea. All
right, so this is my last question
before our uh continuing the
conversation question and before we go
on this short break, but um if you could
go back in time, any point in time
during your career uh when you started
really playing with this idea of open
content, right, and you could give that
young David um a piece of advice, what
what would that be?
okay, I'm going to have to explain this
piece of advice, but that piece of
advice would be to involve commercial publishers
publishers
in that conversation far earlier
than [clears throat]
this timeline, David actually did. So,
in the open- source software world, they
um knew right from the very beginning
that it's it's big companies with lots
of money that fund the development of
most software. And so, if open-source
was going to [clears throat] really take
off and become a thing and be successful,
successful,
major for-profit companies were going to
have to choose to open source a lot of
the software that they wrote. And so,
they started early on having those
conversations. And now
IBM, Google, Facebook, they all open
source so much of the software that they
create. And it has made this ecosystem
that has driven innovation on the
internet on on devices um
in just an [clears throat] unbelievable
way. When I first started the work on
open content, I really only was reaching
out to instructors,
to uh department chairs and deans, to
provosts like, can we please don't pass
policies that say cuz back in the early
2000s, people are like, "This sharing
thing sounds scary. It'll it'll be the
death of the university. We're going to
not allow faculty to share their
resources and things like that." So I
was really focused internally
um but within within academia. >> Mhm.
>> Mhm.
>> And by the mid by the mid2010s
um when I when I first started um so one
of the other things that um that I was
doing back then was I was running the
open education conference. So I um
created that and ran it for its first 16
years. And in the in the mid2010s, I
started inviting Pearson, Sgage, McGraw
Hill, McMillan, like trying to get them
to come to the conference and understand
why it would be good for them, how it
could be good for them to start openly
licensing some of the content they created.
created.
But because I hadn't done that early enough,
enough,
the um the identity of some people in
the community had come to be one not of
using openness to drive student
learning, but um being open because
commercial publishers are evil. And
because commercial publishers are evil,
>> we need to retaliate. We need to react
by creating OAR. we need to take them
down like they're the worst.
And so that attitude had had too long to
kind of develop. So as I started
inviting those commercial publishers in,
um some people in that conference
community just treated them so rudely,
so disrespectfully.
Um they sponsored the conference for a
year or two and then they just, you
know, they wouldn't come back and they
wouldn't engage. Like Sengage made a
major announcement about an OAR
initiative that they were launching at
the open education conference and the
community basically said
openness for people who are virtuous and
righteous and you clearly are not. Why
are you trying to pretend that you you
know just just shut them down hard right
like right when they announced it. And
um if you again if you look at the open
source software case and there's a a
report that's written every year every
other year out of the Linux Foundation
something like 95% of all open- source
software is written by someone working
at a for-profit company paying them to
open source the software that they write.
write.
So imagine today,
imagine all the OAR we have today if
that was just 5% of all the OAR that
existed because Sgage and Pearson and
these other their commercial publishers
had gotten involved. Um it's just a huge
loss for all of us. And like if I had
one thing to do over again in my open
career, that's what I would do. I would
try to pull them in sooner before that
bad attitude had really solidified. Um
because we we still are we're missing
out on just a ton of synergy and benefit there.
there.
>> Well, thank you for uh for that for that
answer and um all right everyone. So
we're going to go on a quick break but
stay with us. When we return I'll ask Dr. WY are continuing the conversation
Dr. WY are continuing the conversation question and we're going to be taking a
question and we're going to be taking a look into the future of Genai and O OEAR
look into the future of Genai and O OEAR in higher education.
in higher education. [music]
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>> Welcome back everyone. It's time for our continuing the conversation question.
continuing the conversation question. So, Dr. Wy, as you look ahead, uh what
So, Dr. Wy, as you look ahead, uh what gives you the most hope and perhaps what
gives you the most hope and perhaps what gives you the most uh uh caution or make
gives you the most uh uh caution or make you pause about the intersection of
you pause about the intersection of Genai and openness in higher education?
Genai and openness in higher education? I think probably the thing that gives me
I think probably the thing that gives me the most excitement is um
the most excitement is um uh is a is a combination of just how
uh is a is a combination of just how quickly the quality of the models of
quickly the quality of the models of generative AI models is advancing and
generative AI models is advancing and how many of the major players in the
how many of the major players in the generative AI space have committed
generative AI space have committed themselves to sharing open weights not
themselves to sharing open weights not for all of their models but for some of
for all of their models but for some of their models. um because it's the case
their models. um because it's the case that the you know the very bleeding edge
that the you know the very bleeding edge frontier models will never be open
frontier models will never be open source. The the quality of the
source. The the quality of the open-source models tends to lag about a
open-source models tends to lag about a year maybe 18 months behind the frontier
year maybe 18 months behind the frontier models.
models. Um, but if I'm sitting down to
Um, but if I'm sitting down to learn intro to psychology,
learn intro to psychology, do I really need the bleeding most edge
do I really need the bleeding most edge frontier model to do that or is the
frontier model to do that or is the open- source model today good enough?
open- source model today good enough? And I would argue that with the right
And I would argue that with the right context and the right prompting, the
context and the right prompting, the open source models today are very good.
open source models today are very good. And so the idea that that's just going
And so the idea that that's just going to keep getting better and better and
to keep getting better and better and people are going to continue to release
people are going to continue to release open versions of those model weights.
open versions of those model weights. We're going to keep writing prompts and
We're going to keep writing prompts and writing context. Um like the future of
writing context. Um like the future of OEER
OEER and generative AI being open, running on
and generative AI being open, running on my phone, running on my laptop. um being
my phone, running on my laptop. um being able to put the model weights, the
able to put the model weights, the context and the prompts on a thumb
context and the prompts on a thumb drive, drop it in an envelope and send
drive, drop it in an envelope and send it to Nepal, send it to Thailand, send
it to Nepal, send it to Thailand, send it to, you know, anywhere in the world
it to, you know, anywhere in the world where maybe there um isn't reliable
where maybe there um isn't reliable internet connectivity. Um, but I can
internet connectivity. Um, but I can still, if I can find a computer, I can
still, if I can find a computer, I can plug this in and have my own generative
plug this in and have my own generative AI all working locally, teaching me the
AI all working locally, teaching me the things I need to know, doing translation
things I need to know, doing translation on the fly for me. Um,
on the fly for me. Um, it's it's like the it's like the vision
it's it's like the it's like the vision I had of open content before. or we're
I had of open content before. or we're like if we can just create that artifact
like if we can just create that artifact the first time, if you can just find a
the first time, if you can just find a way to fund the development of that
way to fund the development of that textbook, you know, then millions of
textbook, you know, then millions of people could benefit from it. It's it's
people could benefit from it. It's it's very much the same except instead of
very much the same except instead of creating one static artifact, I'm
creating one static artifact, I'm creating this recipe of potential that
creating this recipe of potential that can just go everywhere. So, that's the
can just go everywhere. So, that's the thing that is the most exciting to me
thing that is the most exciting to me about it. Um, the thing that gives me
about it. Um, the thing that gives me the most pause, I think, um, at least in
the most pause, I think, um, at least in in formal education settings is
the um the kind of pressure I think that a lot of university leadership feels to
a lot of university leadership feels to need to adopt AI policies
need to adopt AI policies right now because we still don't
right now because we still don't understand generative AI very well and
understand generative AI very well and how it fits into the education context.
how it fits into the education context. um like just the just agentic browsers
um like just the just agentic browsers this past summer totally changed um like
this past summer totally changed um like what online learning is going to look
what online learning is going to look like in the future. Online learning is
like in the future. Online learning is going to have to change in the face of
going to have to change in the face of these agentic browsers. Um but I I worry
these agentic browsers. Um but I I worry that if we adopt policies too quickly,
that if we adopt policies too quickly, we're going to box ourselves into
we're going to box ourselves into corners. There's going to be all this
corners. There's going to be all this amazing untapped potential out here
amazing untapped potential out here that's going to be out of reach because
that's going to be out of reach because we've said policy-wise, you're not
we've said policy-wise, you're not allowed to ever do this, that, that, or
allowed to ever do this, that, that, or that. And that might that might make
that. And that might that might make sense on the day that you say those
sense on the day that you say those words, but 3 months later, a year later,
words, but 3 months later, a year later, it's like a year is like a decade now,
it's like a year is like a decade now, you know, with the the speed at which AI
you know, with the the speed at which AI is advancing.
is advancing. >> Um, I'm concerned about premature
>> Um, I'm concerned about premature policy. Like imagine if in imagine if in
policy. Like imagine if in imagine if in 1999
1999 our universities had set policies around
our universities had set policies around what is and isn't allowed with the
what is and isn't allowed with the internet.
internet. Would we even have LMS's on campus
Would we even have LMS's on campus today? Would we be would we be allowed
today? Would we be would we be allowed to YouTube didn't exist? I just all the
to YouTube didn't exist? I just all the stuff that came later that we could have
stuff that came later that we could have policied oursel into a corner on.
policied oursel into a corner on. Uh I have I just have lots of concerns
Uh I have I just have lots of concerns around kind of innovation. and
around kind of innovation. and participation
participation being foreclosed before we before we
being foreclosed before we before we really understand what the possibilities
really understand what the possibilities are.
are. >> And uh Dr. Wley, is there anything else
>> And uh Dr. Wley, is there anything else that I know we talked about a lot of
that I know we talked about a lot of things uh really exciting things uh very
things uh really exciting things uh very enlightening conversation uh but is
enlightening conversation uh but is there anything that we didn't talk about
there anything that we didn't talk about that you would like to perhaps uh
that you would like to perhaps uh comment on?
comment on? I think I would just say that even
I think I would just say that even though there is so much kind of chaos
though there is so much kind of chaos and confusion and contention and
and confusion and contention and like the world is is not the happiest
like the world is is not the happiest that it's ever been right now, the world
that it's ever been right now, the world at large. Um, but I still think that
at large. Um, but I still think that education can be such a powerful force
education can be such a powerful force for good,
for good, for peace, for improving, you know,
for peace, for improving, you know, prosperity. Um, and it's it's never
prosperity. Um, and it's it's never there has never been a more exciting
there has never been a more exciting time to be a learner than right now.
time to be a learner than right now. Like with access to generative AI, the
Like with access to generative AI, the way that you can ask any kind of
way that you can ask any kind of question that comes to mind when you're
question that comes to mind when you're stuck on your homework at 1:00 a.m., you
stuck on your homework at 1:00 a.m., you can just get that help and keep going
can just get that help and keep going instead of being, you know, log jammed
instead of being, you know, log jammed the way you used to be. There's never
the way you used to be. There's never been a more exciting time to be a
been a more exciting time to be a learner. And I don't know that our world
learner. And I don't know that our world has ever needed educating more than it
has ever needed educating more than it needs right now. So those two things
needs right now. So those two things seem like really hopeful and promising
seem like really hopeful and promising things to me. So despite all the turn
things to me. So despite all the turn and swirl uh that's going on, I'm I'm
and swirl uh that's going on, I'm I'm pretty optimistic about the future. So I
pretty optimistic about the future. So I think that's the last thought maybe that
think that's the last thought maybe that I'd share.
I'd share. >> All right. Well, Dr. uh Wy, thank you so
>> All right. Well, Dr. uh Wy, thank you so much for uh talking to us today. Like we
much for uh talking to us today. Like we again we were super excited to have you
again we were super excited to have you on the podcast and this conversation was
on the podcast and this conversation was really really enlightening. Thank you.
really really enlightening. Thank you. >> Well, and very fun for me too. Thanks
>> Well, and very fun for me too. Thanks for the the invitation. This was great.
for the the invitation. This was great. Thanks for listening to Speaking of
Thanks for listening to Speaking of Higher Ed. You can find all episodes and
Higher Ed. You can find all episodes and more on our show page at
more on our show page at austa.edu/inovation
and continue the conversation with us at facebook.com/auugci.
Speaking of higher ed is produced [music] by the center for instructional
[music] by the center for instructional innovation at Augusta University.
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