[ Silence ] [ Dale Whittaker is at a podium ]>>Dale Whittaker: What
I’d like to do today is to provoke, actually. Hopefully, I will
say something that you would choose
to disagree with and we’ll get a chance
to do that at the end, or at least choose to
clarify or challenge. And so I’m going to
go out on a few limbs. And the limbs that
I’m going to go out on are early in this talk. So this talk is
divided into two parts. The first part are trends, so I will just tell you
those would be my claims. I think hopefully
we’ll substantiate and convince of you those. And the second part will
be two models of change. So the title of this talk
is “Skating to the Puck” and I just – I added that;
that’s why it’s in white. And it really is about:
How do we know where to go? The second part of
the talk is really about how do we get there when
we think we know where to go? And again, I’ll talk about
two models of change. One of those has to do
with teaching and learning. And the other one
of those has to do with student success
in general. [ Shows quote on screen ] So Wayne Gretzky said that “A good hockey player
plays where the puck is. A great hockey player plays where the puck is
going to be.” [ Screen returns to Whittaker at the podium ] So let me just outline
this a little bit. Where is the puck going? [ Shows outline on screen ] I would relate this to vision. How do we start
moving toward the puck? I would suggest that this
is related to the process of changing our organization,
organizational change. Correcting course.
What happens when the puck gets whacked
by someone else? This is about evidence-based
decision-making. So I’ll talk a little bit
about the role of data and the role of evidence in how we make decisions
that’s related to change. And reflection is
really about: Are we doing the right thing? Is it right to skate
to the puck? Is it right for
our organization? Is it right for society? And then finally, go back to
the start with the vision, and that is if we
were to arrive there, what will it look like? And will it be good? Will it be a good thing? [ Screen returns to Whittaker at the podium ] So let’s talk a little bit about where the
puck is going to be. So here I’ll start
in some claims. First of all, some of the
things that I’m seeing are that the percent of the cost of a college education
is shifting from a societal good
to a private good. It’s shifting in our state
from 20 years ago 70% borne by the state to right now
we’re at about 18% borne by the state, and the rest
is borne by the student. We’ll talk about
what that might mean. At the same time, there’s
increasing desire for access. [ Screen changes to a list of trends ] More high school
students are preparing and desire to go to college. I would also claim that there’s becoming a
blurring among disciplines. And say it here is a
reduced distinction between disciplines. And growth areas that we
see are often at the edges of disciplines or matrixed
across disciplines – molecular biology
could be an example, spatial sciences
could be an example. [ Screen returns to Whittaker at the podium ] Here’s one that I hope
to convince you of – and I’m becoming
more convinced since I put this talk together
– and that is that the value of delivering information
is going toward zero. We’re going to come back
to these, by the way. And in congruence with that,
I would claim that the value of creating new knowledge
is increasing in the context of more and more
people having access to information that exists. In the past ten
years, we’ve come to – and we are rapidly expanding
as we got into the century of biology and the century
of the brain – or the decade of the brain – we’re
understanding more and more [ Screen returns to the list of trends ] about how we think and
function and translating that to how we remember
and learn. So our understanding of
learning is very different than it was 15 years ago. And I probably should
have put this with the reduced distinction
between disciplines because it kind of stands
in contrast to that; an increased need for both
specialization and connection. So isolated specialization
is becoming less valuable, [ Screen returns to Whittaker at the podium ] but depth is becoming
more valuable. Jim Spohrer with IBM calls
this the T-shaped individual or T-shaped organization
or T-shaped university, and that is that to function
we have to have depth in an area – maybe it’s
a disciplinary area or a technological area –
but we also need to be able to function in a
very general sense and very broadly connecting
to other disciplines. In the last piece that I would
say is a strong trend is an increasingly – what Thomas
Friedman would say is a flat world. What I would say is
increasingly political boundaries are being blurred by technological
and trade access. Okay. So let me try convincing
of you a few of these things. Substantiating my claims;
that’s what I ask students to do – part of
thinking critically. [ Screen changes to chart ] What we have here is this – he said use the big
one, the big gun. What we have here is the
percentage of student share of cost in public – in
all of public education – the students’ percent of
the share of the cost. How’s that? And this, you’ll see the
reference here is May of 2012. What you see in the blue
lines, where is that? Here it is. What you see in the blue
bars are recessions. And so you can see that
rapid change happens during a recession but it often
doesn’t come back to the point that it was before
the recession. Rapid change happened
and continued happening after this recession. And you’ll see rapid
change here again. I mention Purdue is at
about 80% student share now. [ Screen returns to Whittaker at the podium ] I don’t know where you are. It ranges anywhere from
40% to – Colorado State is at about 7% state funded. New Hampshire is under 10%. Virginia is under
10% for example. So this ranges broadly. Let me ask some questions. What does this mean to us? Alright. First thing I would
suggest is that it means that there is decreasing
access by the middle class. So as the burden shifts
from the population to the individual, it’s
reported in the newspaper as tuition is going up, right? Then it makes it more and
more difficult for those that don’t qualify for
high need-based aid, which is on the very low
end of lower middle class to high need and who do not
have very, very high merit. So there’s this large group
of students – the majority – who fall within that category. The second thing that I think
you are seeing as a result of this is increase of the
community college system. I think it’s happening
in Georgia, I know that it’s
happening in Indiana. So if you look at
the state revenue over the last four years,
the majority growth has been in the community
college system. Why? Because this middle class that is having difficult time
accessing financially the tier one institutions
is going there, are going there, to cut costs. It also aligns with
the increased access, more people wanting
access to higher education. What’s not talked about much but what I believe is a
reality is it is shifting – there is a shifting
sense of the value of higher education being
a public good for all of democracy and it is
shifting to ‘If you want to get ahead in life,
it’s your responsibility – financially and
otherwise – pay for it and you will receive
the primary benefit through a better job. That’s a very different
view than, for example, we know that people who
have a four-year degree or higher vote at
almost double the rate; at almost double the
rate volunteer at more than 40 hours a month;
have healthier babies. There are all kinds of
societal implications of higher education
that are documented. So let’s talk a little bit
– I have my notes up here by the way – talk a
little bit about outcomes of this kind of a change. Number one, from a
university’s point of view, we start going after private
donors for scholarships. Okay. So what we try to
do is defray the costs for those middle class or
those students that are in that bubble that don’t
have access to need by going after private scholarships. So we’re all scrambling to build our scholarship
endowments. You see a shift from
in-state students to out-of-state students. Okay, what does that mean? At Purdue I can tell
you that it means that the out-of-state students
cross subsidize the gap between the state and
the individual student. So the state’s contribution in the last five years
has dropped by 16%, where we’ve raised
tuition by 7% in state. So there’s this gap there. And where is that coming from? It’s coming from the
international students and the out-of-state students. The budget model
drives a shift toward out-of-state students. And out-of-state students I’ll
claim – I’ll do more than claim – are basically private
school students, right? So in a sense we have hybrid
universities that are – and when I say private,
they have economic mobility. They can pay $40,000. And when they can pay
$40,000 a year, they can go to a proprietary in their
state, and go to a proprietary out of state, or they can
go out of state to any of our institutions. So they have that level
of economic mobility. An increase in auxiliary
businesses; so what you start seeing
is athletics gets spun off as an auxiliary service and
then taxed by the university. Housing and food services get
sold to Pepsi and Starbucks or ARAMARK and returns
revenue. Distance education gets spun
up as an auxiliary service to stand on its own and return
revenue to the university. So as this gap opens
up, in order for us to maintain our public
mission and public access, we have to find these other
ways we’re not used to to subsidize that gap. The other thing I think
you’re seeing is a – I think you will see – this
is the most painful one, it is a decrease in the
variety of offerings. Often you hear it
codenamed at institutions academic program review. So it basically – the question
is: Is our variability in offerings costing us money? Does it make sense to have
a few critical programs that support the mission
that we’re good at and let other institutions
teach those other programs? So within states
you start to see – depending on how many
universities the state has – some mission differentiation. My sense of Georgia is that your mission
differentiated from day one. In Indiana, we were
mission differentiated from day one almost
constitutionally. Where IU has the medical school
and the law school and music; we have technology
and engineering. And then there’s
a lot of overlap like business schools
that’s not well-defined. Another outcome I think
you see and I don’t know if this is an outcome – I don’t really know
what this is – but parents being
shocked and less prepared. So parents thinking that
college was like it was when they graduated – say,
when I graduated in 1983. And so I put aside $100 or $200
a month, thinking that I’m going to be saving enough for
my kids to go to college. And when it comes time to go to college the cash
gap is too large. Maybe I don’t have
a job right now or maybe I’m already borrowed
out because of the recession. I can’t borrow money. All of a sudden I find myself
in a hole where I can’t close that gap in a short
period of time. So this is where I believe
the public pressure is coming that you start to hear in the
sound bites of: Get students through faster; lower
tuition; teach virtually because it must be cheaper. And I’ll argue that one. It’s often not cheaper
because it’s faculty effort that is the cost
in anything we do. But that’s where I think a lot of these pressures
are coming right now. And I just want to talk
about the source of that. At Purdue, I think
that in our next four or five years there’s
going to be a real focus on the word “value”. That’s basically
quality divided by cost. Let’s move on here if I
can find my clicky thingy. Alright. So now let’s
talk about my claim that there is an increased
desire and/or need for access. [ Screen changes to a chart ] Let me try to tell
you what this chart is because I don’t think you
would be able to see it but I needed to show
it in its entirety. And this is an OECD
publication. This year that’s
referenced is 2002, so it’s already ten years old. And what we see here is two
generations – there we go – the blue boxes typically
on the bottom are 55- to 64-year olds and it’s the
percentage of those people who have earned a tertiary
degree, post-secondary, so college in the
United States; 25- to 34-year-olds
are the diamonds. Alright, so you get it here? This country here, Korea, has
gone from 12% – I’m sorry 12% of their 55- to 64-years-olds
have higher education whereas 64% of their 25-year-olds do. So what this is a measure
of is educational mobility, but you can map it quickly
to societal mobility and economic mobility. Alright. Let’s look at
the OECD if I can find it. Here it is. OECD average is
about a 15-point gain between these two generations. The G-20 average is
a little bit less. What is that? About a 10-point gain or so? This is supposed to shock you. Oh, what’s that one there? That’s United States. And so what does that say? That says in 2002,
the percentage of people that were 55- to 64- that had
higher education was the same as the percentage of
25- to 34-year-olds. The only country that
has regressed more than us is Israel. And they actually have
regressed and I think that I don’t know where
we would be right now. So I don’t know if we would
have regressed or progressed. But this should bother us. And it bothers us at
the national level. [ Screen returns to Whittaker at the podium ] Obama’s national strategic
investment in the future that you’ve heard
about is really focused on this competitive gap, the
Lumina Foundation’s focus on closing the gap as – to
increase societal capital, really is based on
this OECD study. Let me try to interpret now
what I think this means. Well, as I said, number one: The current generation
is no more educated than the previous generation. I think you need to
look at the countries that have passed us. So this is our current
generation right here. We’ve got Australia, UK,
Luxemburg, New Zealand, Norway, Ireland, the
Russian Federation, Japan, Canada, and Korea. But if you look at the
gains, you have countries like Poland, Portugal. Korea is shocking; Japan
is shocking in its gain. France. And I’ve already
mentioned the OECD and G-20. So the outcome of this I think
again is a societal focus on access. So here we have a conflict. We have – we as a country say
that when we look at slides like this and think
about our competitive or just our intellectual
capital position in the world, we’re highly threatened. And at the same time
we’re reducing – we express that
through our willingness to shift the budget, pay
taxes, whatever you want to call that by shifting
it to a private good. So I think these
positions are in conflict. But what we’re seeing
is, again, the growth of the community
college system in result of this; the pressure
on distance education as a low cost form
of education. Okay. So those are
those two trends. Oh, it shook. That’s cute. Alright. The third
trend that I wanted to mention was this
concept – oh my goodness, I think I just lost a slide. Let me see if it’s next. Okay. I didn’t. The concept of a flat world. And let me just start by
showing you a simulation. [ Screen changes to chart simulation ] I can jump out here. Alright. Let me tell
you what we have here so we can understand
it as it plays. On the x-axis is
basically income per person. Each of these circles
represents a country. The scale of the circle
represents population. The countries are coded
up here so you’ll see that yellow is basically
the Americas. Blue is Africa minus
the Middle East. Green is Middle East. Red is Asia. Orange is the former
Russian Federation. And on the y-axis is the
life expectancy in years. So this is starting
now at the year 1800. And you’ll see that United
States is probably one of these yellow dots in here. I can’t tell the difference
between yellow and green. It’s probably this one. So let’s just say it’s $1,000; this is inflation
adjusted per person. And a 30-year –
that can’t be right. Let’s go up here, it’s
probably this one. A 40-year life expectancy. Okay. And China is that
big red dot even then. And what I want you to
watch for are two things: One is rate of gain of
China in relation to – or let’s say red in
relation to yellow. The second thing is look
for depressions, recessions, and the Cultural
Revolution in China. Watch for that one. And I’m just going to play
this if I can figure out how. The numbers in the
back are the years. So you can see life expectancy
remains fairly constant but income is increasing. China bounced back on income. And now we’re climbing through
the Industrial Revolution, the yellow dot on the right. You saw a dip there
around World War I. And watch – let me stop it. Stop, stop, stop. Okay, I can’t stop it. There we go. What I wanted you
to see there is – let’s still look at China. Let’s look at life
expectancy but look at income. Okay. Let me get back now. Now we’re in 1981. Okay. So just think
about that. So now we’re, you know, have
life – let me see if – yeah, that’s the United States. So we’ve grown a little bit
in population – quite a bit. We have moved up to about
a $42,000 mean income. We have about a 79
average life expectancy. And China has made
huge gains on us. [ Screen returns to Whittaker at the podium ] So let’s ask what
does this mean? First, let me get
my slide up here. [ Screen changes to Flat World slide ] Someway I’ve deleted that. And let me go back to
Maslow’s Hierarchy to talk about what this
might mean to us. I think I click on this one. Alright. If you think
about Maslo’s Hierarchy, then at the bottom
is psychological: Food, water, warmth, rest. The second is safety. So once you have satisfied
your physiological, psychological needs, then
you can begin starting to think about safety. That’s the way Maslo’s
theory works. You can’t think about social
– relationships and friends – till you feel secure. Okay. You can’t think about
esteem, which is related to individualized
accomplishment and societal prestige until
you feel like you have friends and you have intimite
relationships as an individual. And the last one here
is self-actualization, which is related to
achieving potential and creative activities. What I would argue is that higher education
typically happens within societies where self-actualization
is being realized by a majority of the people. Okay. So in other words they
feel safe, they’re not hungry, they feel socially connected. So you don’t start
getting to the luxury of higher education
till you’ve gotten through most of those areas. So the question I
would ask you is: As you watch those other
balls bouncing up closer to where the United States is and the differentiation being
less – i.e. flat world – what does that mean in terms
of consumption of resources? [ Screen returns to Whittaker at the podium ] Right? What does that
mean it terms of demand for higher education? What does that mean
in terms of production of creative activities,
which should feel – if you’re thinking about
economic competition – should feel threatening
to the United States because we’ve always excelled
on the creative production on intellectual property. The next thing that I claimed
was that the distinction between disciplines
is being blurred. What this is a
publication diagram [ Screen changes to diagram ] published by Thomas Scientific
2004 Journal Citations. And so these are
just citations that have coauthors – this
is a real simple graph – coauthors between
these disciplines who report their disciplines. So if you look at molecular
and cellular biology, it has a lot of citations and
you’ll see strong connections to neuroscience; but you
see them also to ecology and evolution; you see
them to crop science; you see connections here between environmental
chemistry and microbiology and agriculture; you see
analytical chemistry. So my – the point that I would
try to make here is that – [ Screen returns to Whittaker at the podium ] I’ll use a quote that our
Provost, Tim, uses often, “Students have interests,
societies have problems, and universities
have departments.” So basically the societal
problems are starting to bring people
up from a depth within disciplines together. And what we see up here
– we don’t see many of our traditional names
– pathology is down there. I thought plant science
was on there somewhere. Well, you can look
for yourself. So what are the outcomes here? This is the outcome that
I claimed probably results in administrations asking
for program reviews, asking the question “Do we
have the right people together for now, or do we have
people together based on what was right
20 years ago?” Increasing consolidations
and reorganizations. And we’re also seeing
significant changes in the fundamentals
of disciplines. I think – I’m not a
biochemist, I’m an engineer. But the way that biochemistry
is understood and taught now – should be taught now I guess
– is significantly different than it was understood
20 years ago, same with neuroscience. Okay. And I would
say in my area, hydrologic modeling,
same in our area. Because we can parallel
compute now. Alright. Now, I made
this claim that the value of information is going down. I’m sorry, let me say
that more specifically – the value of delivering
information, not the value of information. So let me just show
you a picture here. [ Screen changes to a picture
of a 13th century classroom ] This is one of the
first classrooms in the 13th century. Let’s see, what’s
happening here is that a few people
could read and write. That’s basically
this guy up here. Alright. He could
read and write. These are the people that are
learning to read and write. This is a religious setting. Books were scribed. So what is he doing? Anybody have a guess what’s
happening in this picture? He has the book
and he’s reading it and they are writing it. Is that anything
like taking notes? He’s got the book,
they’re reading it, and he’s writing it. Okay, let’s see. Anybody teach a large class? Anybody teach a class
like in this room? Let’s see if you recognize
any of these people. Recognize this guy? How about these
two right here? You know what this
one’s doing? They’re reading their
iPhone, texting, these two are chatting,
you know? Alright. So that’s
kind of funny. So let’s move it to
the 21st century. [ Screen changes to a
21st century classroom] What is different
in this picture? You see this person – now
I’m not going to say reading from the book so that
they can write it down. Maybe he put his slides or
his points on PowerPoint so they don’t even
have to write it down, which is a huge
technological advance. I’m being facetious here
in case you couldn’t tell. This guy’s drinking a Coke,
you know, they’re chatting, they’re sleeping, they’re
doing all this stuff. Alright. But what I would say
is this: What we see here, at least at Purdue is over 80%
of our instructional modality. [ Screen returns to Whittaker at the podium ] It may even be over 90%. It’s constrained by the
way we have built space. It’s constrained by how we
were taught and how we know to teach because I
wasn’t taught to teach, I was taught to
do engineering. And so the question would be: If you remove the following
constraints – space, technology, furniture,
time – would we move from what would be here
as a mass production, or what I would claim is a
Industrial Revolution version of teaching, would we
do anything different to move it toward a
mass customization and individualized
mode of teaching? So think about medicine. And what I would
say is in terms of understanding
students’ success – and we’re much better in
teaching – we have evolved from what I would call
medieval medicine, where we get something out of
out of a tree, or we mix it up and we put it on a person
and see if they live or die. You know, if they live we give
it to someone else and see if they live or die. And so that’s sort of
empirical medicine. Then we move to what I would
call the Industrial Revolution version, where we
know science, we know very well what
works and why it works. And so we put it on the
whole population, right? To where now I think
we’re rapidly moving to genetic medicine,
where we say “We know what works
well for the population. We know the distribution
of responses to that.” But now we’re starting to
know why that distribution of responses happens. So out here on this tail
we know this person is genetically different. We can do something
different for them. And I don’t think
we’re there in teaching or student success yet, but this would be
my challenge to us. Alright. So in order
to move there – [ Screen changes to quote ] and this is to continue
to support my claim about delivery of information. I just want to read
this whole quote to you. This is Michael Wesch
from Kansas State who some of you will know through the
Digital Anthropology Project. And he says – he claims that
there is – I’m not going to read this to you – there
is something in the air around us right now and
I’m connected to it. And it is 70% of the documented
knowledge of human kind. I don’t know if that number
is right, but I’ve heard it so I’m repeating it. But pick a number – 50%, 90%
of the documented knowledge of human kind, whether
you’re in – down on the beach at Gulf Shores, whether
you’re in South Africa, whether you’re in
western Nebraska, whether you’re sitting
here right here in this classroom you
have access to it. As soon as I made
some of these claims, some of you were typing. And you were going to the
source documents for this and you were reading about
the position of the author. You were doing all kinds
of stuff to check me out. [ Screen returns to Whittaker at the podium ] I know you were. So his question here
is: Now that we are in this ubiquitous pool of
knowledge, what is the role of instruction, of
education, of the facilitator? And I’ll make some
claims along those lines. I would say – here we go. First of all, the
question I would ask is if we’re providing –
if I’m in front of you in this picture we saw, 500
students in the classroom, and I’m giving you
that information that you have right here
by reading it to you, by you writing it down in
your notes, then the practice of you writing it
may enhance learning but basically I’m
delivering information. And there may be a lot
of ways to do that. So what does have value? Number one, taking from me, taking information
and knowledge. And so to take information
and knowledge you have to judge the information,
you have to know when and how to apply it, you need
to assess the results. Number two, meta-learning,
so the idea of understanding what it is
as a student, as a learner, how you learn, navigating and
managing your own learning. Third, judgment and
critical thinking. This is something that
can’t be done in isolation. I would claim it has to be
done in a societal context. Skip ways of knowing learning. And synthesis and analysis. So if you think of
the Bloom’s Taxonomy, basically what I’m suggesting
is residential education where people are learning
in the context of others and in the context
of expertise. I believe that it is our
responsibility to move them to the higher levels of the
Bloom’s Taxonomy to synthesis, analysis, and creativity. If we’re operating in
the rote memory level and application level
of Bloom’s Taxonomy, then we’re going to get –
I’ll just say it – we’re going to get killed by online
mass customization because it’s deliverable. Now, what I would say is I
don’t know any faculty member that doesn’t do that. What I’m not sure is
whether we do it deliberately and whether the students
know when they’re shifting to higher orders of
the Bloom Taxonomy, whether we talk it out. And the reason for that is
the paradox of expertise. So as you become expert
in something and I loved – I say that facetiously –
I hated the math professor when I was an engineer
that would say, “It is intuitively obvious,”
or “anybody would know that.” You know, all that stuff because they’ve
compiled their knowledge, they’ve compiled 20 years of
how they came to know that. And when you compile it,
just like driving a car, you can’t remember
how to do it anymore. So part of the reason that we
don’t articulate the process of learning, knowing, and
high order thinking skills to students is because
we do it naturally; we don’t know how we do it. Think about you’re a
15-year-old driving a car. You know, do they
– when you say, “Would you please stop
at that stop sign?” And they’re still roaring
it’s, like – they say, “Well, what do you mean?” It’s like “Put your foot on
the brake 300 feet before if you’re going
40 miles an hour.” It’s like “Oh, okay. Well, why didn’t you tell me
put my foot on the brake?” That’s decompiled knowledge. Okay. Alright. Now here’s the other
piece of this. Do you remember the – those
of you that are my age, remember when cable
came on the scene, we used to have
three channels of TV. And when cable came on the
scene two things happened: CSPAN and ESPN emerged
and a lot of reruns started
showing on lots of cable. Okay. So there was
increased access, there was increased
differentiation, but the value of the reruns was
at a minimal value. So people in the big three
days would have never watched CSPAN because it
was so boring. But it – not only is it a
way to spread democracy, but what it really
is is fresh content. You know that when you
watch CSPAN or ESPN, it’s happening then. It wasn’t happening before. It’s not rerun. It’s not replayed. So one of the claims I would
make is: “In your position as a research one institution
you are very well-positioned to create new knowledge
and fresh content.” I think we’re structured,
though, to deliver that intellectual
property through two sources: One is referee journals
and the other is through licensing
and licensure. That third piece of very rapid
deployment of digital content for teaching and learning,
I don’t think we’re very – and I know at Purdue we’re
not sophisticated in yet. But there are 61 AAUs. I don’t – is Georgia? I should know. Are you an AAU? Okay. You’re a research one. There’s 128 research ones. There’s 3,000 institutions
in the United States. And approximately
– what is it, 300 a year being developed
in India and China? So that is the market for your
content that’s not fundamental and basic content,
but your new content. Okay. Get on with it, Dale. Okay, the next trend
that I mention is that we’re understanding
learning in a different way. And what I want to do is
play another video for you. For me this one is
pretty powerful. [ Video plays ] And let me see if this is it. Here we go.>>Male: Hi, students. [Background music] We are starting a new project. We just want to see the
world as you see it. So just grab any camera;
anything like a flip, or if you have one of these. [ Multiple speakers and Music ]>>Male voice: This is what we
do with our lives. This is what we
do for our lives. [ Music ]>>Male voice: This is what they do
with their everyday life. [ Music ]>>Male voice: Welcome to the school.>>Male voice: Where education is the … [ Multiple speakers ]>>Female voice: And you don’t
know anything else. That is what we
know, is school.>>Male voice: The student’s taught that discovering knowledge
is beyond the power of the student and is in any
case none of their business.>>Female voice: Okay. Well, what if
I don’t know what I want to do yet?>>Female voice: Normally college life
feels kind of encapsulated.>>Male voice: Recall is
actually the highest form of intellectual
achievement and the collection of unrelated facts is
the goal of education.>>Female voice: Kind of like
you live in a bubble.>>Male voice: The teachers are not
the ones pushing the same old way of doing things; it’s that
the students are as well.>>Male voice: We are taught
that one’s own ideas and those of one’s classmates
are inconsequential. [ Music and Multiple voices ]>>Male voice: So I’m walking
across campus pretending to be
on the phone. It’s kind of actually
embarrassing that I’m walking across talking to myself,
talking to this recording.>>Male voice: We’re told there’s
always a single unambiguous right answer to a question.>>Female voice: The more in the box
my life got, the more that I hated it.>>Male voice: The idea of being yourself
has no meaning for me anymore.>>Male voice: No, I’m
just being who I am.>>Male voice: Students are also
told that the voice of authority is to be trusted and valued more
than independent judgment.>>Female voice: Because I remember
that I used to talk when I was in elementary school and I
just got shot down so much that I stopped trying.>>Male voice: What students mostly did in class is guess what the
teacher wants them to say.>>Male voice: We don’t learn the material because that isn’t
what the simulation of school asks us to do. The artificial environments
steers us to meet artificial requirements and
bureaucratic regulations. So we read and do homework. We couldn’t get rid of
the words, so we put them in scare quotes, scaring away
all the meaning of irony. Students mediated and
inauthentic and numb and vulnerable put course
requirements in scare quotes and laugh a hollow laugh at
an impossibly pyrrhic victory, not as a joke, but
as a lifestyle.>>Female voice: But sometimes
that bubble’s popped early.>>Female voice: I’ve got “Standardized testing
equals standardize students” printed across my chest. And I’m ready to
make a difference.>>Female voice: Kenny Rodriguez said, “Traditional education
needs to die. It needs to go away.”>>Male voice: These revolutionary
new ideas, they’re not so new.>>Male voice: Going to college is not
the same as getting an education.>>Female voice: Mr. Fulkerson expressed
agreement with my statement. When he asked immediately
afterwards what I was going to do about the situation, I was a little less
enthusiastic.>>Female voice: Are you going
to be a passive recipient of education, or are you
become an active owner of your own education? [ Music ]>>Male voice: What do you think
Marshall McLuhan ought to do if he wants to be taken more
seriously in the world today? [ Multiple voices and Music ]>>Female voice: …from the hands of
God, with blogs, words written daily by people like you, like me,
that have no other choice but to share what they know with
someone, anyone, everyone. You complain of over
determination…was not a gift before believed in them. Why should we submit that the
theory of the nice agency? Let’s look around
and see the ways to make things work… When you ask me what I was
going to do about the problems of standardization I
didn’t know what to say but now I’ve got a few ideas. I hope you like them. [ Video ends ]
[ Screen returns to Whittaker at the podium ]>>>Dale Whittaker: Okay.
Mike Wesch is a digital anthropologist
which basically means he observes people
in their natural setting. And I think if any of you have
college age students or live with them in the residence
halls, you’ll understand that this concept of digital
native is almost something that those of us that did
not grow up digitally – and that’s basically anybody
that’s not probably an untenured faculty member
at this point or in that transition where we’ve
got three to four years of digital natives
on the faculty. It’s just we have
to understand them. Okay. So I’m very
hopeful about this. One of the questions is: How
do we teach based on research, and how do we use our
teaching as research? So we’re at the end
of the trends now. [ Screen changes to a list of reflections ] And let me go back and do
a little bit of reflection. And what I would suggest
is that in institutions like ours we have a number
of great opportunities and great advantages. Number one, we create
knowledge rapidly. [ Screen returns to Whittaker at the podium ] Number two, we have a
resident education with people that interact with each other. Number three, we
have the opportunity and we do teach
higher-order thinking skills. So if we do our job well, we will build a
strong foundation, we will have efficient
time to degree with reduced wasted time, we
would have more affordability, and these are all goals and we would eliminate any
gaps among the subgroups. And finally, we would
prevent derailing. What I’d like to do is
quickly talk about two models of change that we’ve used;
one for teaching and one for student success. Alright. So let’s talk about
how do we move to the puck. On the teaching side,
what we wanted to do is take what we know about
the way people learn and the way – and use our own
teaching as experimentation and institutionalize
that in a way that would rapidly
change our program. And we chose the early
adopter model in this case. I’m going to talk about
two models: Early adopter and step change that’s across
the entire institution. So let’s just talk about
this early adopter model. The idea here is
that the proclivity to change is normally
distributed like this: [ Screen changes to bell graph ] Where over here on
the right-hand side you got those people that say,
“Oh, me, me, me. I love to change.
I don’t care what it is. I don’t even care if it’s right,
but let me try something new.” I tend to be probably leaning
in that direction myself. And over here on the left
you’ve got those folks that say, “There’s nothing
you can do to make me change, whether it’s the
right thing or not, I’m not going to do it.” And this is a very small
number just like those on the right is a
very small number. And the majority is
right here the middle. Most of us fall in the middle
of the normal distribution. [ Screen returns to Whittaker at the podium ] And this is a group that
is a very valuable group and say things like,
“I’m not going to change until I know that it works. Show me that it’s
worth my effort. Show me that it’s the
right thing to do.” When someone that is – someone
else that’s doing it is doing it do I trust them, do I think
that they have credibility? And so in listening
to these people, these are also the people that
will say, “Are you watching out for throwing out the
baby with the bathwater? Are you aware of the
unintended consequences? If you go that direction
have you thought about these things?” So that’s why this
group is so valuable that often not the ones
to start the change. So the early adopter
model uses those people on the right-hand side to bring along the
majority in the middle. Let me just quickly go
through how it works. First of all, we have to
agree – you have to agree on the goals: The
outcomes, the values. [ Screen changes to practice slide ] And that has to be
agreed on by everybody. And then turn loose
the early adopters and let them experiment. And what they do is basically
prove it to the show me’s. But what they have to agree to
– if you’re an early adopter – you have to agree
to full transparency and if you’re sponsoring this
change, you have to agree to the safety to failure. It has to be safe to fail. And so the early adopters
have to be measured so that everybody else
that doesn’t have the time or energy to put
out that change for experimentation
reasons can watch, make their own decisions. Those early adopters are
normally not credible within society because they’re
the flakey ones, right? You usually say, “If
you’re an early adopter, you’re a flakey.” So what you have to do is
in a societal context say, “We want to watch you, we
want you to try on our behalf and we’re going to
support you in that.” So that’s a leadership
language requirement. And there has to
be safety to fail. [ Screen returns to Whittaker at the podium ] Now, over time the
whole goal is to move back along
the bell curve. So after the first
early adopters go out and are measured you’ve got
some that are very – like me – very willing to take maybe
a little bit of energy and try it and you
want to move back along to that proclivity
of the bell curve. Let me just talk
about this last one, minimizing the negative
impact of those on the left-hand side: You
can call them deadwood; you can call them
boat anchors; you can call them
all kinds of names. But basically if they are
there because they’re not in it for the group sometimes
those people have very strong voices and you have to
recognize that as a group. You have to decide who
– and often it’s easy to confuse those in the
middle that are saying, “Are you sure you
want to do this, and did you think about XYZ?” Early adopters tend to
confuse those with the people that say, “I am not
going to change.” They say, “Nobody
wants to change because they’re asking
these questions.” So you can’t confuse
those two. Alright. Let’s talk a
little bit about the role of data and information. In order to move along the
bell curve you’ve got to – I would suggest you
have to use evidence. Part of that is
the assessment, part of that is data. So one of the questions
one could ask is: “Where are we going?” once you’ve decided on
the goals and values. Good ways of doing
that is use pure data, where did other people
go; baseline data, where are we right now; best in class data,
who does this best? For the ‘prove its’ to
prove it to the show me’s, then you need to really be
careful what you measure. And I on my campus say that my
holy grail is learning gains and it seems easy and
it is very difficult to measure this. But in the projects we sponsor
we’ve have a million dollars in classroom renovation
we do each year. And if we can’t show
learning gains are different in that kind of class,
then in a cheaper kind of classroom we’re
going to stop. We do the same thing in
hybrid and flip classes; we’re putting in half a
million in technology. If those students don’t
learn better than – [ Screen changes to data/information slide ] just because it feels better
doesn’t mean we should continue it. So this for me is
a holy grail. There are indirect
measures like retention. And satisfaction you see
here has a question mark. It’s easy to ask
faculty members “Did you like
doing it this way?” It’s easy to ask students
“Do you like this kind of class?” And those are important
because they relate to motivation, which
relates to learning. But they’re not
the end results. So you have to get
the learning gains. And then the third
reason to use data is to keep an eye on known risks. So when the show me’s say,
“You’ve got to pay attention to these potential risks
as we move forward,” someone needs to
pay attention to them. Alright. And then finally
“Are we there yet?” When you set – when
you use data to set out a goal you baseline and
you say, “We want to be here,” then it’s nice to plot that in
a longitudinal way because it feels good when you start
making progress toward goal. [ Screen returns to Whittaker at the podium ] I would encourage you to
set aspirational goals. Two years ago I wouldn’t
have believed this, but we set a goal of 50%
four-year graduation rate for our freshman class. And everybody that was a
data guru said, “Whittaker, you’re going to lose
your job over that because there’s no
way we can get to it. We’ve been at 32%
for 20 years.” And that varies by
about 5% a year. And we did. We set an aspirational goal. And what it did
for us was said, “We have to change behaviors. We know we can’t get to it anymore doing
the things we’re doing, so we have to do
something very different.” And so it actually did. [ Screen changes to roadblocks slide ] Let me talk about
the roadblocks with the problems
with data, though. And you’re going
to recognize these. We as faculty like
to do things right. So we’re all statisticians
in our own disciplines. One of the easiest
things to say is, “We can’t draw a conclusion because the data
isn’t good enough.” And we kick the can on a
decision down the road. What I would suggest you think
about is balance the data with the expertise and
intuition that’s in the room because we’re very
reticent often as faculty to believe our intuition
and expertise. But if you have diverse
expertise in the room and views, I would encourage
you use it to make decisions. The other problem
is too much data. And for me this is a
problem with poor hypotheses. So often you’ll get
loads and reams of data and the question is,
“So what does it mean?” Well, for me that
means we didn’t ask the question right
going into it. The third one is
windows on the elephant. In our institution
we have data silos. So Student Affairs has some
information about a student, Admissions has some,
your registrar has some, and we can’t cross it. That’s the windows on
the elephant problem. And most often this is
an institutional problem, data is reported
at the wrong point. So if you’re a department head
and you have decisions to make about your programs and
all you get is a grade [ Screen returns to Whittaker at the podium ] of your department against
a soil and crop science, let’s say, then that’s just
like getting a D on a paper with no corrections
on it, right? There’s no actionable
intelligence there or if you’re a dean and
you only know what all the colleges are doing
but you can’t break it down at the department level. So sometimes we don’t
disaggregate data at the right level. Alright. So that model goal
is for basically to leave – not worry about
the boat anchors, minimize their voices – and eventually move
towards 84% change. Example that I would use is
this program we call Impact. And so we wanted to
change the way we taught, and we wanted to do it
in a deliberate way. [ Screen changes to goals slide ] So our goal was to change
the entire campus culture to a student-centered
pedagogy; to enable faculty-led
course redesign using campus-wide resources. Faculty we’re going and
being nickel and dimed all over campus by continuing
ed and by distance ed, the testing services,
and so on. And they had to figure out how
to put the package together. We wanted to make sure that
we had not just physics or math education doing
this, but that it was diverse and that all colleges or all
departments were involved. And we wanted to teach
based on research and use our teaching
as research. So I’m going to skip
through these slides and talk about this one. [ Screen returns to Whittaker at the podium ] We’re in the third cohort now. And we started out by asking, “What are our really
large classes that will impact a
lot of students?” was one question. How many of those have
high failure rates? In other words, we’re
not going to worry about English 106 because
students seem to do well in there but we’re going to
worry a lot about Calculus. We’re going to worry a lot
about Organic Chemistry. So which one of those big
classes have high failure rates? And then the third
question we asked is, “Are there any early
adopters out there?” And we really thought that the
intersection would be zero. Because that would be like saying you teach a
really big class, you know, that’s already a penalty in
some cultures, our culture. So you’re penalized – you get
to teach a really big class and you do it terribly
because you have all these kids failing. “So why don’t you join our
program so we can fix you?” Well, it turned out that
there were 13 scholars that were course coordinators
that taught these large courses that raised their hands and
said, “I want to do this.” [ Screen changes to IMPACT slide ] So we got really lucky
in the first cohort. From that point on, the
President talked about it, the Provost talked
about it, and it rolled. So it worked out well. So cohort one, you’ll see the
colors are different colleges. Cohort two we targeted
at 20 classes. And then cohort three
we are targeting at 30 and we have the spring ’13 classes
selected as of this week, so those faculty members
will come in this spring. As of this fall we have about
7,800 students being taught in active collaborative
flipped classrooms. [ Screen returns to Whittaker at the podium ] There’s all kinds of
different versions of this. Each one of these has testing
services that does validation on every test question. All outcomes are disaggregated
by activity and assessment. So we try to put our
very best practices – all of our support
– under every one of the faculty members
that chose to do this. We bought out their time. So we asked – we said,
“We’ve got $10,000 to buy your attention. You and your department head
figure out what that means.” It may mean, you know,
paying for summer salary. It may mean release
from a course. It may mean giving me a TA;
I’ll keep teaching my course, whatever that means. So here’s what we’ve
learned so far. [ Screen changes to what we’ve learned slide ] We learned that the demand for our space has
been way exceeded. So our top priority in our new budget
that was presented this week is a $ 90 million active learning
library classroom facility. We also learned that
this is starting to reset expectations. And we’ve only been doing
it for three semesters now. So it’s starting to
reset expectations about what’s excellent at
the undergraduate level. We’ve learned that
a number of things that we thought
early on didn’t work. So we thought by
designing the class and turning the faculty member
loose that would be good. But what we’ve learned now is
that the faculty member wants heavy support while
they’re teaching the class, they’re changing it on the fly
and assessing it on the fly, [ Screen returns to Whittaker at the podium ] and they want us there
for one more semester. So now it’s a
three-semester package: Build it, teach it, fix it,
and try it again, and then they’re kind of
on their own after that. We’re just getting to
the fourth semester where we’re asking some
of those if they want to be mentors back
in the front end. Alright, I’m going to
play one more video and then I think it’s
time for me to stop. [Video plays] [Audience conversation]>>Tim Delworth: My photo
was up there a minute ago but my head’s so big only
half of it fit up there. [Laughter] I’m Tim Delworth and
I’m from the Math Department or as I title this one
“Our Lady of Mathematics Reformed.” And I’m here, you know, to
talk about our experience and I’ll give a little
bit of background. I’ve been teaching
large lectures for about ten years here. And, you know, I did what I
was told to do, which was go into a large lecture
and teach. And that’s what I did. And I knew we had to make
changes but I didn’t know how because the chairs were
bolted to the floor; and Physical Plant gets upset
when you bring a wrench in. And I got thinking
about my 10-year old. He can flip pancakes,
my 10-year old, Carter. And he can flip them
because he spent about a year making
huge amount of mess flipping pancakes. We cleaned up a lot of
pancakes at our house. But right now he’s really
good pancake flipper because he got his
hands dirty. He got messy. And that’s what the
students have to do. They have to get involved. And I walk into that large
lecture here and I just – I mean, they get glossy and
they stare at the clock, just waiting for that
sweet release of 20 after. And I knew we had
to make changes. Like I said, I didn’t
know how to. And so last spring a
couple things happened. I was told that in the
fall I would be teaching in Wetherill 200. And I’m like, “Oh good
God, it’s a balcony.” And then the other
thing that happened to me was my department
head came to me and told me about this initiative impact and that the math
department had to stop saying no
to everything. [Laughter] And then he thanked
me for volunteering. [Laughter] But I was ready
for a change. I was ready for
a change anyway. So here’s my experience. So we met all summer in our impact group,
we exchanged ideas. I can’t stress enough how
rewarding that part was, just being in the group. I was the only one from –
I think – from the College of Science that was there. What I thought I
was going to do and what I’m doing are two
totally different things. I had no idea going into it what
I was going to come out with. And so, let me get
to my experience, then last fall I’m teaching a
lecture of 180, 200 students. Everyone stayed in the
class all through exam one and then 30 students
self-selected to go into my impact session. And my impact session only
met one time a week instead of three times. We met for 75 minutes. The students were instructed to watch the online
lessons for 75 minutes. And then we spent the
75 minutes working and we went really hi-tech. These are huddle boards. And there’s a bunch
of them down there. And students were put
in groups of three and they were given problems and we spent 75
minutes working in math. And they made mistakes and
they argued with each other and there was a
lot of interaction. And by the time it was over, I
mean the students understood. It was amazing, the process. The students that
self-selected were about average after exam one, a couple points
above the average. And my first order of
business was to do no harm because I didn’t want to mess
these 30 kids up really bad. I determine their grades.
I could have fixed it. [Laughter] The department hates
when I say that. [Laughter] Well, what happened
was on exam two – and so then they only
met with me half the time that they were supposed
to meet with me. And now with exam two they
were still a couple points above the average, same
as they were on exam one. And exam two they
were a couple points – nothing changed. They met with me half the
time they were supposed to meet normally
and they ended up with almost exact
same results. But the student
comments were fantastic. One student wrote, “I love
being in the Thursday class.” Of course with the student
comments there’s a lot explanation points. “I love being part of
the Thursday class. It was helpful to see the
different ways other students thought through the problems. I enjoyed the new
section of the course and only had the
class on Thursdays.” I know that helped. And they loved the extra
practice and the interaction. So their averages were
pretty much the same but two things happened: The attendance rated
was near 100%. The 30 kids that went
into it, I had three weeks where there was
100% attendance and there would be
one kid missing, and then there might be two. The other thing that happened
my DFW rate was 3% out of this section. Small sample size,
self-selected to get in so we can argue
the statistics, where my normal course is
between 20% and 30% DFW rate. So I enjoyed it, I
enjoyed the process, I enjoyed teaching it. I was originally a high
school teacher 20 years ago and I felt like I was
back in the classroom and actually doing
some good work. So that was my experience.
I’ll turn it over. [Applause] [Video ends]
[ Screen returns to Whittaker at the podium ]>>Whittaker: So I think you
can kind of get a sense from Tim that what
we’re seeing so far – we’re just starting to get
the assessment results – his attendance has skyrocketed
whether it’s psychology, or management, or physics. The achievement on standardized
tests seems to be similar. So I’m not sure
that we can say that there were
increased learning gains. We’ll have to keep
watching that. One of the questions I
would like one of the – my hypotheses is
that we’re testing at the low Bloom’s levels. So I would like to see
some more advanced analysis synthesis questions on
those assessments and see if that differentiates groups
because I would hypothesize that those students that learned
actively, I think, at a higher order. And then the third thing
that I’m interested in but we won’t know for a
number of years is retention. So what happens when you give
the same test three years out or two years out
to these students? Is there any separation in how deeply they
learned this information? So in review, this was a model
– is a model – that started with early adopters, we’re carving off
rapidly the majority. It is changing in a
way that we hoped, but we didn’t expect the
culture on the campus to rapidly shift to a pedagogy
that is different than any of us basically know or knew. The second example that I would have given
was our foundations of excellence process where we
brought 200 people together – a very large team – used
evidence to ask where we were on student success, used
exemplars to say where we want to go, and produced a report
that talked about the evidence and made recommendations. And the reason that
that was important is because when you use
this report with deans, department heads,
trustees, or other faculty, the evidence is already cited. So you can’t really
question whether it’s valid. The ownership is cited because
we had students, faculty, staff, and administrators and distinguished
professors all on the teams. So the credibility
was established in the upfront way. But we had to take
a step change. We couldn’t wait for the
evolution that we’re doing with this second model. So it’s a very different
model. With that – Jean, I
know that I’m over time. So I’d turn it over to you. And thank you very
much for inviting me. This has been a blast. I look forward to
the interaction. [Applause]>>Jean Bertrand: Okay. Is there one or two
quick questions?>>Dale Whittaker: That was our
first expenditure of resources. The first question
we asked is – that was exactly
the response we got. First of all, we had 1,700
faculty and we found 10. So, you know, we’re
talking about small numbers. And the first response we
got was: “I teach, you know, multiple sections
of 500 students. I prepare, I’m trying to
manage my graduate students.” So what we asked him was,
“What can we give you to give you enough time
to step back and do this?” with the belief that almost
never do we get the luxury to really create or
recreate a class. When you’re hired, you hit the
ground, you get the course, you may get someone’s notes – or if not you’re
really scrambling to stay two weeks
ahead of the students – you teach the class, you
go to the next semester, you come back, and you brush
it off and you teach it again. You tweak it to the
extent that you have time. But it’s so rare to have
this opportunity to step back and ask all of the questions. So that was what
we wanted to do. So we arrived at $10,000. That buys a lot of
attention in liberal arts. It buys a little bit in
engineering and management. And it’s been used
differently. Some people take it
as summer salaries. Some people, as I mentioned,
ask the department head to have someone else teach
your course for that semester or that course for that
semester so they can focus. Whatever. This is a scale question. And so one of our
assessment questions is about scaling of one answer. When you go from
tabloid armchairs to active collaborative
rooms – you didn’t see one – you go from 15 square
feet per person to 35. So with the same
enrollment we have to grow our teaching space. So that was one of
the justifications for this new building. The second is both with Tim – he said he saw those students
one day a week instead of three days a week. And with our Psychology 120
those both went from Monday, Wednesday, Friday
500-seat classes to Monday for an hour and a half, 120. Wednesday, a next
group of 120. Friday, a next group of 120. So you get at the scale by
working the time in a sense. These are all experiments. We have – so one of the
beliefs is that the quality of learning is
directly related to student-faculty ratio, that
that’s based on the assumption that the ratio impacts
the interaction. So if you can raise
the interaction and raise the ratio, then
you can kind of address that. So these experiments
have to do with trying to tweak those variables. It’s a really good question. And not all of our experiments
are going to scale. It just won’t work. But if they increase learning
enough, we reduce the number of students that have
to retake those courses. You know, 30% of
those students are retaking or leaving. If we reduce those to,
say, he said 3% or 4% in that small population then
we can – we have the resources to teach more smaller sections because we don’t
have to reteach them. We haven’t seen it yet. But we’re asking that question
with that cohort that was in Tim’s class right now. So what we’re measuring
is grades in post-requisite
courses predicated by the grade going
into the course. One of the interesting things
is we spent half of our time in this project –
the faculty do – articulating their outcomes. But we never anticipated
that in the first cohort. So just getting the
outcomes right, and in that, we now
invite in all the faculty that have post-requisite
courses and all the faculty that have pre-requisite courses. So if you’re teaching
Organic Chemistry, you sit with all the
faculty that teach Chem 2 and you also sit with
faculty in Plant Biology and Biomedical Engineering and whoever else uses organic
chemistry as a post-requisite. You ask them, “What is it that you think these
students should know?” And you ask them, “What
should I believe these students know coming in?” And the outcomes are
tweaked based on that. We’ve never done that before.>>Bertrand: Well, at this
time we’d like to invite you out to our reception, just
right outside in the lobby. And then for those of you
that would like to stay and just have an
informal discussion, we’ll do that after we have
a little chance for a break. So thank you very much. And thank you, Dale. © 2012 University of Georgia College of Agricultural and
Environmental Sciences

Skating to the Puck – Dale Whittaker
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