[MUSIC]
Hello and welcome to another edition of
Undercooled, a
materials education podcast.
Today, I'm here with a special guest,
Professor Susan Gentry from UC Davis.
And I've known Susan for a long time, cuz
she was a graduate student here at
University of Michigan.
And so I've known her and
I've also gotten
reacquainted with her many,
many times at education conferences, most
recently at the NAMES conference
last summer in San Luis Obispo.
And of course, our little plug, we're
gonna have the NAMES conference this year
in Ann Arbor, Michigan, and I
hope all of you can make it.
So Susan, why don't you tell us a little
bit about yourself and
how you got into teaching and what your
position is at Davis.
Cuz it's a little unusual, but it's
really important, I think.
So go ahead.
Yeah, so I'll start from the beginning.
So when I was looking for
doing a PhD and started my PhD,
I was interested in going into industry.
And so one of the things that
interested me about Michigan,
going to grad school at Michigan and my
advisor was strong industry connections.
Sort of through the
process, I finished my PhD.
I wasn't 100% sold on industry cuz my 3D
printing machine kept breaking on me.
And so I was trying to
look for different options.
So I ended up sticking around for another
three years in Ann Arbor.
I did a postdoc in phase field modeling
with Katzio Thornton.
And so sort of during that, during my
PhD, I enjoyed my teaching experience.
And so I was interested in
those types of positions.
I was able to get a partial teaching
appointment my last year at Michigan.
Katzio helped me teaching the
undergraduate lab class at Michigan,
while I was also doing the postdoc.
But sort of through all of this, I was
still like, do I go into industry?
Do I try an academic job?
And ultimately where I ended was I felt
like the teaching job was this thing that
I would always feel like, what if?
So I started applying for the teaching
positions, figuring I'd try them.
And if not, my fallback could always be
to go back into industry.
Well, not go back, but to go back to my
original plan of going into industry.
And so I was looking at lecture positions
and things like that.
I wasn't interested.
I don't have a big enough drive of this
is my research problem I want to solve to
be a research professor and to have to
run a research group and write grants.
So that was not interesting to me.
And so when this position came up at
Davis, I was really interested.
So it's morphed titles a little bit.
The title series though that I'm in is a
professor of teaching series.
So it's equivalent to
tenure track here at Davis.
So I'm an associate
professor of teaching.
I have the equivalent of tenure.
And so I'm treated like an equal.
I'm a member of the Academic Senate,
treated like an equal in my department.
I say that this comes with the honor of
serving on three hour qualifying exams.
[LAUGH] But I get to
sort of meet with students.
My teaching load is one and a half times
that of the other faculty.
So I do teach more, but then I'm
evaluated more on my
teaching innovations,
my teaching excellence with a smaller
aspect of my scholarship.
And for my scholarship, then I've been
able to go to these
education conferences,
present on work that I'm doing.
I've worked on computational
modules for the curriculum,
looking at student learning.
Now that I've gotten tenure, I sort of
tried integrating
more active learning and
different types of
strategies into my graduate classes.
And so, yeah, it's just been a really fun
time to meet with students and
also to think about what is good teaching
and how do we help all of our students?
And how do we help them learn and grow?
Fantastic.
Yeah, I remember your first few talks at
NAMES back when you were just starting
were all on different
computational models.
And then of course I noticed in your
publication history,
you started drifting towards during the
COVID days of how to
do distance learning.
And now you're back doing equitable
teaching and active learning in all your
classes. So I hope we get
to talk about all of that.
So do you want to lead off Tim and ask
her a question about one of her topics?
Sure.
I have a two parter here because the
first thing I want to
know is digging further
back into the past, what caught you into
material science and engineering in the
first point? What's
the origin story here?
Oh, the origin is I'm the rare bird who
came into material science as who had
material science as their degree listed
when they started college.
I liked chemistry. I liked physics.
In high school, my sister had suggested
to me she had gone to Carnegie Mellon.
And so she had suggested, oh, you might
be interested in this
material science thing.
I was also at one point interested in
chemical engineering till I visited a
different university and realized that it
was like big pipes and they were like
showing off their like
two storey like facility.
And I was like, I mean, I liked chemistry
and physics, but this is that's not what
I thought chemical engineering was.
And so just a little bit
of trying different things.
But I just like the integration of the
chemistry and physics.
And I took an intro to materials class my
freshman year and liked it and I've stuck
with it ever since.
Yeah, I feel like every time we ask
someone a question on
the show, the answer is I
thought I wanted to be a chemical
engineer, but then I really didn't.
It's just funny how
much that keeps coming up.
But back to graduate education, since
that was something you
were talking about in
graduate courses, especially there's so
much rigorous quantitative content, so
much of the sort of analytical problem
solving that has to be taught at a really
deep level in graduate courses,
especially compared to say
the intro materials class.
What are things that you're doing with
quantitative problem solving in an active
learning sort of way in
these graduate courses?
What does that look like for you?
You know, it's it's an emphasis, but I
think sometimes we get too caught up on
thinking that our students actually are
getting the quantitative problem solving
skills that we think they are.
I like to sometimes reckon.
So I'm teaching a graduate thermodynamics
class is what I do this in.
And I've seen what I call the hope and
pray approach to science to solve problem
solving, which is like they just
rearrange their
equations and they get an answer.
And if they get the answer,
like they're very relieved.
As opposed to like being able to explain
their answer and, you know, can they
reproduce this on an exam, you know, or
can they do this on their own?
Do they know why their
answer is right or wrong?
You know, those are the skills that I
just feel like easily are still getting
bypassed, you know, and if I have an exam
and sure, it's a really hard exam and
then the score is a 60 and, you know,
half the students didn't get one of the
questions like, what is that telling me
about their their learning?
And so it's just these questions of, yes,
we expect it to go deeper.
But I also want to make sure that my
students like have these fundamental
this fundamental knowledge, have these
fundamental skills, because, you know,
they're sort of rearranging equations,
you know, just trying to figure out the
right answer, hoping that it works out
like that's that those skills aren't
going to serve them well as they move
forward in their graduate career.
So I noticed that in your one of your
talks, you put up very prominently
a picture of grading
for equity, the book.
And it seems like you followed a lot of
the examples in that book.
And also the specifications grading book
by Nilson, I think her name is.
And I've been reading similar things.
I just finished reading a
book called Grading for Growth.
I don't know if you've heard of that, the
Robert Talbert Road.
And there are very
similar kinds of things.
But obviously, from looking at your work,
it seems you believe that the grading
strategy strategy is intrinsically
involved in the
learning of your students.
So can you talk a little bit about that?
Yeah, and I you know, it's wanting their
their grades to represent like their
their knowledge and their mastery of the
course content as well.
And not to be like the thing that struck
me about there's this example in grading
for equity where like depending on how we
are waiting different categories of like
homework versus participation and this
and that and their exam
scores like how much am
I sitting there fiddling with this to
like when you sort of
can look at your students
to be like they get it and they don't.
But how can I sort of make my grading
scheme represent more
realistically like what do
they know and and like
what is their mastery?
And how can we also then get it so that
we don't have to like
nitpick about like this
was an 82 or an 84 on the homework or
this presentation like
you know they're going to
my students are going to go on you know
if they're in the PhD
program at the UC Davis
they take their an oral preliminary exam
at the end of their first year.
And so like that's on a
pass retake fail basis.
And so like let's stop getting into like
these little nitpicky
arguments of like you
know 82s and 84s and like let's focus on
like you know are you demonstrating these
skills are you not.
And it's hard to get
there with the grading team.
I'll be the first to admit I'm not there
yet but it's just been
really getting me to think
about like how do we get students to like
recognize that they're
you know they and they
can't just wait for the you know depend
on the class to do poorly.
But like I don't care if the class
everyone in the class did
poorly on something like
it's they're responsible for you know
mastering these topics.
And how can we sort of then link that to
the letter grades that we we have to get.
So all that sounds great.
But of course the devil's in the details.
So how do you actually assess whether
they've learned it or not.
I noticed you even went to oral exams or
you're thinking about
going to oral exams.
That's very time intensive.
So what's going on with all that.
How are you going to figure out what
they've actually
they've mastered a topic.
The reality is that some of this mastery
is still for me just
having to be is being done
like on an exam setting.
But then also just trying to give them
opportunities to like
practice mastery as well.
And so that they're they're gaining those
mastery skills so that the exams aren't
this like big thing.
But that exams are just a
way for me to like to check.
We're not there yet.
But I really tried to give them
opportunities to give get
lots of practice for those.
Yeah I really this is the thing I really
struggle with is how do
you I like the oral exams.
We could talk about that for for a while.
But how do I do this and
make it time timely for me.
Also I have some remote students.
And so how do I do this in a way that
works for them as well.
So they're working full time and are
watching lectures on their own.
And so they can't necessarily participate
all the time in class every day.
And so how do I create this this class
environment for everyone.
Yeah. And so there's.
Oh that's a really interesting idea.
If I can ask a little more about that.
So it if you have in person students who
you're doing these sort of you know doing
different activities in class with your
in person students but then
you also have remote students.
What are some strategies that you're
trying to give you know to give some sort
of comparable valuable
experience to the remote students.
And I ask because you know in 2020 2021
when I had these hybrid courses as well I
was really struggling to actively engage
my remote students and never
quite found out what
worked for me in that.
So how are you doing that.
Yeah. So one of the strategies that has
worked I can you know they do work a lot
of them work in the same place.
Most of them are through
a national lab program.
And so you can still give them like group
work to do or group homework assignments.
But then also some of
this problem solving.
I'll make one of the groups.
It's my classes video recorded and a
video recording classroom and so I'll
make them either go up to the board with
the microphone or go
use our document camera.
But so that way they're getting to see
sort of other students working working
through these problems if I'm doing
problem solving and I can set it so that
the microphone isn't
projected through the classroom.
But that way the microphone is getting
picked up the audio is getting picked up
for the recording and so
that they can sort of be there.
One thing I did two years ago I skipped
it this year and but I think I'll go back
to some of it is to also have the
students do videos where they have to
explain this the
solutions that they have.
And so the remote students if they
weren't in a group they had they could
have easier problems if the end of all
students could do these.
If you were working as an individual
there was slightly easier problems group
problems had slightly harder problems but
that way you sort of are getting examples
and videos of how to like you know do
some of this problem solving.
And see other students solving the
problems like we skipped so much of this
in graduate education we just pretend
that they're supposed to go off and
magically do this and so you know sort of
saving time for some
of that in the class.
And so that they can sort of see some of
that and then they're still having to
explain it to each
other you're using a lot of.
Lots of feedback right during class where
you're able to see them actually do the
work and then give them feedback on what
they did and not count that as great
right just use that to teach
them is that what i'm hearing.
letting them teach each other.
Well yeah so just I mean if part of it is
is working through how do you start a
problem you know you sort of
start some of these problems.
A phase diagram you give them common you
give them the free energy curves and they
have to do the common tangent
construction to generate a phase diagram
and you know students don't even know
where to start or how
to explain that and so.
getting them to practice some of that
starting and explaining but then also
trying to make sure.
When we would do these problem sessions
that then you know things were getting
recorded for the distance learning
students, so I had seen one scheme to
make oral exams more scalable.
And the idea was that.
If students didn't get a good grade the
first time or a passing mark or a mastery
mark whatever you want to call it.
They would have an opportunity to do it
again and so they then to do it again the
professor would tell the student I will let you.
take this again or take parts of this
again, but you have to come to my office
hours and do it in my office hours and
let me talk to you about it.
That way you only have to deal with the
oral exams for the students
who actually need the help.
You don't have to waste your time on all
the students who actually learned it so I
thought that was a really clever trick
that I read about in a book grading growth.
And it's a neat idea.
Yeah, so I did so I would I sent this
students a problem 30 minutes advance
they had some time to work on their
problem so they sort of got that problem
solving time without me having to be
there, and so then
they just had to sort of.
explain their problem, it was just I need
to figure out better the logistics of how to how to do some of this and make sure I.
don't give them too many time slots
during the days so that they have to like
they have to stack themselves up.
How many students are
in your class typically.
I had about 20 students so you can
probably do it for 20 I mean I just
taught a class with 140 students in it so
that's kind of hard yet you know oral
discussion just communicating talking to
somebody you get a real sense right away if they understand it.
And that's what my my last
course was a total disaster.
Everyone got days because they all did
what I told them to do but.
But when I walked around the room and I
talked to all the teams it only took me
about 15 minutes and I realized not a
single person knew what they were talking
about and it made me really sad so I'm now having to read this.
I wish there was I mean.
yeah the gold standard for measuring
learning isn't oral exam.
Too bad it's not scalable
that's the biggest problem.
I know that there's a group that had that I think it's a UC riverside it's definitely one of these season in mechanical engineering.
And they've been looking at oral exams
they started them during during COVID and
so you know coming up with rubrics and
things so that they could do this with.
You know, in some of the you know with
100 students and things like that sort of
they wouldn't do all their exams this way,
but at least to do one or two check ins
and then also wage to you know frame it for the students.
As like learning opportunities rather
than this like panic you
know really scary thing.
You know so there's people who are
interested in doing that and then it's
also just trying to make you know keep in
mind that like time goes into grading and
so you know opportunities to use these sort of strategically I think are really really interesting.
yeah two ideas in there that really stood
out to me one was giving the oral exam
almost as the retake opportunity it
sounded like to give that extra time and attention to the students
who apparently need it most so that's really cool.
But then, as you were Susan as you were
describing the implementation that you're
giving the students the exam problems
just a short time ahead of the interview
I'll call it I thought that was pretty
interesting because I do a similar thing
with my lab classes where the students have to give impromptu presentations and I give them.
just 15 minutes to prepare okay here's
your prompt here's what you're going to
present on you have 10 15 minutes get
your thoughts together and then give like
a you know five minute whiteboard talk
because one of the professional skills
that I feel like we value so much is the
really thinking on your feet the
extemporaneous oh someone just asked me a
question and I need to be able to explain it even though maybe I haven't thought about this topic for a couple years and so scaffolding is the way to do it.
I think it's also important for them to work through their nerves
I had students there and they sort of knew what was coming, but you could you can see
them visibly you know their hands shaking
but like you know as a
professor i'm used to that.
you know I'm I'm not put off when
students do that I know that these are
really nervous like high pressure
situations it's just that you know by
ignoring them weren't they're not going
15 minutes to prepare for something like
that but you know the more you do it the
more you get used to it and like you find if nothing else ways to manage some of those some of those feelings
and I don't judge them like I said you know I know I can see them shaking and it's like I'm not going to get used to it.
you know we just keep moving on.
So I saw in some of your other talks that
you use learning assistance a lot do you
use those in the
graduate courses as well.
I won't say that I've used them a lot I've used them for a project based class. I've used them for a project based class. I've used them for a project based class. But I've started
exploring how to use them more.
I don't use them in a I don't use them in
the grad class and I don't know how I
could use them in the grad class in you
know similar to Michigan we have to be
careful with rules regarding especially
now that all of our our teaching assistants and research assistants are unionized
And so it's really unclear even in other
situations of
opportunities for graduate students.
I mean they could sign up for a one-unit
class and do this but it why would they
and so it works a lot better with the
undergrads and so I've had this junior
level project based class where I had
senior you know I get senior students who
then sign up to do it and then they get they've been getting course credit and they get to do it.
They get they've been getting course
credit and then I'm very careful to
delineate their responsibilities versus
the responsibilities of the T.A. or the
greater but then you know these are
senior students who need leadership
experience you know or want you know to
try you know to get more involved in the
department so I'm sort of I'm thinking of
using some of them next quarter and
teaching intro to material science class and
and so I'm probably
gonna get like two or three
to help me out with some
of the lab opportunities
or some of the office hour times.
- Can you talk a little
bit about the, you know,
you were talking about how you were
starting to use videos
that graduate students would make to
teach a muddiest point
or something like that as
part of the instruction.
Now that you've done this for a while,
do you see impact of that?
Is that something
you're gonna continue to do?
- I mean, I just like, you know,
it goes back to the learning assistance,
it gets back to the graduate education.
Having people have to
explain how they solve the problem
or answer a question is just such a good
experience for them.
So I've done these videos
where they would do like,
in my grad class they
have to answer like a common
undergrad problem of how can entropy
increase or decrease,
you know, how can be, I
calculated the change in entropy
and it was negative.
And so just getting practice,
having to give words to those answers,
and then also just trying
to build some of these up
as a repository so that
they can watch all of these.
You know, it's one thing, I've been
teaching for a while,
but sometimes I struggle
with answering questions
in different ways.
And so to hear someone else
answer it in a different way,
come at it from a different angle,
you know, I think that's why it's so
important in these like
peer to peer instruction
opportunities for learning,
you know, to hear the
explanation from someone else
or to hear the explanation
from someone who's had to master
the concept more recently than I have.
You know, I took Intro to Material
Science as a freshman in college,
back in 2005, you know,
and so to have someone who had to
struggle with these questions
more recently than I have,
sometimes they can just
answer it a little better.
And for some of the things
that you're starting to do,
you had written that you wanted to do
in-class problem solving
and student-led instruction of problems.
Is that for both
graduate and undergraduate?
Yes.
I say with the hesitation only because I
teach a lot of different classes,
and so it's also the
reality that, you know,
how I have to come up with different
activities for different classes.
This quarter I'm teaching a lab class,
and so it's just, you
know, it looks a lot different.
And so for me, it's been
thinking about my educational,
my teaching as slow innovations.
And so like how can I
start trying things out?
I've been trying out a lot of these
things in my grad
class because it is small.
It's only 20 students and they're a
little more forgiving.
So that I can see how
things work and then, you know,
bring more of some of
those things that I'm doing,
bring them into my
bigger undergraduate classes,
and just, you know,
try out different things.
Again, though, you know, 100 students in
my intro class, you know,
versus 20 students in a grad class,
sometimes it's just the
mechanics are a little different.
So why don't we take a
look at both of those?
Let's start with the 100-student
undergraduate class.
What does your class look
like? Do you lecture a lot?
Do you break students up into teams?
What kinds of activities do
you do for a very large class?
This is where I wish I did more.
So the honest answer is
that it's mostly lecture,
but then I try and, you know, bring in,
you know, once a week.
I try and one out.
It's three hours of lecture a week,
and then the students
have a lab section as well.
And so, you know, trying to take
advantage of those when they are in class
to, like, bring in, you know, I have
designed some activities
for them to do in class, like that, you
know, take maybe half of a class,
you know, think pair
shares occasionally as well.
But trying to sort of use that as
additional opportunities for them.
And what does the space
look like for the 100 students?
Is it a traditional sloped lecture hall?
Yeah, you know, that's-- they've been
building some new camp--
they recently built a new building that
has more of those, you know,
long tables with chairs and things.
But often when I-- I haven't looked at
which classroom I'm given next year,
but next quarter.
But a lot of times, yeah, it's been those
sloped lecture halls
with the mini little desks and, you know,
these ideas of turning around.
I mean, this is where,
like, think pair share
or, like, do a computer activity but work
with your neighbors,
you know, sticking with things like that
as opposed to things that involve
completely moving around.
We have-- like I said, we
have some of those spaces,
but the challenge can be
making sure that we're getting--
we're getting assigned
those spaces from the register.
So if you got a flat
classroom with movable furniture
and stuff like that, would you
teach the course differently?
You know, it just starts to
bring in more opportunities
to have students work together.
I don't-- you know, I like what you're
doing in your class, Steve.
It's just-- it's hard for
me with all my other classes
to have to, like, redesign that class to
be an entire problem learning.
And so if I think of
it more, though, like,
how can I get from where I am at now?
How can I add in, like,
one more activity a week?
How can I, you know,
expand that activity?
That's what I see.
Where I see makes the most sense for me.
And honestly, I think makes a lot of
sense for instructors is, like,
rather than going all
in and having to say,
"I'm going to completely redesign my
class next quarter,"
in addition to everything else I'm doing,
like, if I can add one more activity in
or think about how can I get
them to do something in groups
where they're having to
explain things more, you know,
get to those higher levels of learning
where it's more
interactive and problem-based
and I can, you know,
be bringing things in,
like, that's-- you know,
that's my goal for my classes.
And what about a graduate class?
I think there's really good advice there
for any newer
instructors out in the audience
that you don't have to
reinvent the entire course
every time you teach the course.
And the incremental change
is so much more manageable
and it does get you
really significant improvements
if you're thoughtful about where you make
those little changes
to where they're needed most.
So what does your graduate class look
like with just 20 students?
Do you teach it
differently than the undergrad?
Is it lecture or do you do a lot of
problem-solving in the classroom?
So this is where my ideal schedule is--
so this one has four
hours a week of class.
And so my ideal
schedule that I like to go to
is aim for about three hours of content
and one hour of problem-solving.
I've tried to, at different
times, do my problem-solving
only on Fridays because that
sometimes has worked better
for my distance learning students,
sometimes to be able to attend live,
if they're working from
home or on a 480 schedule.
But then-- so that's
just been practically--
other times it's sort
of then mixing that up.
And so I think keeping in--
we have to cover thermodynamics
and so there is a fair
amount of lecturing in that.
But then are there then opportunities
rather than only do
Friday problem-solving
to spread out the
problem-solving on some of the other days
so that it's more timely of
where we're learning about it
or you're getting
students to start a problem
and think about the hard concepts.
And then once they've
thought about those hard concepts,
letting them go work
on the problem overnight
and come back so that
we can not spend the time
actually solving the problem.
It's interesting you have
distance learning students
in the same class.
Do they attend
synchronously but just over Zoom
or is it asynchronous?
So this is a program
we've had at UC Davis
for about, I don't know,
longer than I've been here.
I'd say at least 20 years
with Lawrence Livermore National
Lab where they used to watch
class would be video recorded
or sent over there.
And so now the program, what
it is, is the classes are--
because it's a special agreement, the
classes are in a special
room that is set up for live--
where they can attend
live but they're not
required to attend live.
You can require them to
attend presentations live,
things like that.
But some colleagues used
to make them come to campus
for presentations.
Now I think pretty much we're OK with
virtual presentations
but occasional live attendance.
Otherwise they're just
expected to sort of stay up
on the content on a weekly basis.
But you could say break away from
lecturing for 15, 20 minutes
and have small teams of
students work together on Zoom
in like a breakout room.
And even if they're
sitting in a sloped lecture hall,
they're still in a more intimate setting
and that would be very inclusive with
your distance learning
because everyone's
getting the same experience.
And then you can hop from room to room
and see how they're doing.
Have you ever tried something like that?
I haven't tried the Zoom rooms because
that would make the students
then have to actually sign
into Zoom when they're there
as opposed to just being in the same room
where I stop by the different groups.
But I fiddle with the thing.
Do I have them work on homework problems
where they present their homework
problems to each other on Fridays
where they sort of need a set day?
Instead of do this Friday thing, do I
break it up on different days?
And so we only do like half the class.
That's something I'm just actively trying
and just trying to figure out what
structure works for this class.
And again, because this has the
additional complication
of the distance learning students,
what I do in this class
isn't necessarily going to be
the exact same structure that I do.
If I teach an upper division,
if I taught our
undergraduate thermal class,
I wouldn't necessarily
keep everything the same way.
I see.
So something I've been wondering about
with the graduate courses,
which to be clear, I
don't teach any grad courses,
so my opinion here is purely hearsay.
But I'm aware, at least at Michigan,
that our grad students come from many
different undergraduate fields,
different engineering majors, different
chemistry, physics, math even.
And so there's really not
a lot of shared experience
or maybe really any
formal education at all in MSC
that students have in their foundation
when they start grad school
in material science.
So is that similar at Davis?
And if so, how do you handle that?
How do you handle the
fact that you're teaching,
like for example, grad thermo
and some of these students maybe never
even saw a phase diagram before?
How does that work?
Yeah, you know, it's
definitely a problem here at Davis
and I think is a
problem at many, you know,
many graduate programs in material
science sort of across the board
from, you know, the top programs on down.
We talked at one point about doing like a
pre-grad school like boot camp
where in one day or in two days,
we were going to like tell them
everything they were
going to need to know.
I felt like that wasn't going to work.
We replaced it last year with a
programming boot camp instead.
That one's more broadly applicable.
And so what I've had to do is,
or what I've chosen
to do is I've created,
it helped a lot because I
got a lot more comfortable
with making short
videos during the pandemic.
But on my Canvas page, I
have like review pages of
here's the things that I expect my
undergrads to know about a phase diagram.
This is like intro level.
Here's what a phase diagram is, you know,
and so pointing students to those
and making it clear in
the first week of class,
like if you, you know,
watch these videos for review.
The other thing we see even
with material science students
is their comfort and
knowledge of math is not very good.
And so in thermodynamics,
like knowing what the triangle,
the triangle is a difference
delta versus like, you know,
whether you're
integrating like versus, you know,
the D, you know, the
lowercase VD and the delta,
like knowing that these,
and how do you like, you know,
how do you take a partial derivative?
Like knowing some of these
things are actually like we,
they should know it from math, but they
sort of glossed over it.
And so just making sure that like there
are these resources there
that students can go to.
And then also I realized this year, I
need to find ways to not force,
like you can't force
the students to go there,
but how do you really encourage them?
I had some supplemental
videos early in the quarter
where since I was doing
some more problem solving,
I was like, watch this video, watch this
practice problem outside of class.
I don't have to do this
practice problem in class.
Go watch it.
And like some students would get to the
homework and they're like,
I don't know how to do it.
And you're like, did you
watch any of the practice problems
that I told you to watch?
And so just making sure not only that the
students can find those resources,
like I've tried to make my, you know,
canvas page clearer,
but, you know, really trying
to tell them like at this point,
you know, I'm not going to do this, but
there is a video for you.
There are some resources here.
There are some practice problems.
I've posted my intro to material science,
like how to do the lever rule.
Go do those practice problems.
I have plenty of them.
And so getting students to do that and
especially trying to do it early in the
early in the quarter, just because before
things really get busy, you know,
they have the first week or two, it's,
you know, week and a half.
It's slow anyway.
So that's a great opportunity if you
haven't learned those things to spend
some time and go, you know, catch up on
what you do, what you need.
And some students do
really great with that.
And some others just need a little bit
more, you know, push and check ins.
And so, you know, it's funny you talk about math.
Our last episode is all about our
problems with our students with math.
And Tim has the solution.
He's going to teach a new sophomore level
math course for our students.
So you can listen to
that to hear about that.
I have the nucleus of
a potential solution.
Let's not oversell this too much.
But I think it's really good.
Yeah, I think in talking to our
department chair, Liz Holm,
who's been meeting with other chairs of
the materials community,
you know, at the UMC, she told me that
every single program is facing this
problem that they don't know whether it's
because of COVID and students
just didn't learn as much math or if this
has just always been a problem.
But it's a real problem across all of our
materials programs that our
students just aren't at the level of math
that we really think they need to be
to understand the concepts and thermo and
kinetics and things like that
where you need partial
differential equations.
So I feel your pain.
My other comment related to that, Steve,
is I'll put a shout out,
not a shout out, a
call out to the community.
I think that someone should create a
series of like an
online class or something
that's intro to
material science for like.
So Jim Shackelford has 10 things every
engineer should know
about material science.
And I've looked at that,
but that's like to applied.
We need 10 things every new graduate
student in material science should know
about material science.
Like here's the concepts that you might
have missed if you were a chemistry
student or mechanical engineering.
We're going to give you some fundamentals
so you can get started.
That's a great idea.
MIT used that idea for
math in graduate school.
So they have a boot camp for math.
And I went and enrolled
in it and I looked at it.
And in 10 minutes I realized this is
terrible because you couldn't read any
of the writing.
They used some weird
script that got pixelated.
You couldn't even read it.
And then they had these people who were
teaching it who just didn't sync with me
at all.
And they were writing on the fancy light
boards behind the glass and all of that.
But their handwriting was terrible and I
couldn't understand what they were
writing.
And I was like, oh,
I'm going to write this.
I'm going to write this. It was a great idea.
But it has to be
implemented well to be useful.
So I think that's a great idea.
You should write a research proposal and
start soliciting people to help you
out.
That would be great.
See if anyone would actually give me
money or if it just
becomes another one of
my projects that I work on.
And I'm not even sure if it's a good idea to do that.
You could.
And it's hard to do.
I tried to have an open source textbook.
And the logistics.
I'm not even sure if
textbook is the right thing to do.
Maybe a series of
videos would be a lot better.
I just don't know.
Maybe we need to train a personal
coaching AI model on
fundamentals of material
science.
And I'm happy to not volunteer.
I'm happy to not volunteer.
Oh, you are asking a fun question.
I just got back from a workshop, an NSF
sponsored workshop on using large
language models in chemistry and
materials education.
I have to admit, it is one of those that
seemed like an interesting conference to
go to.
I didn't have a lot of experience.
And then they asked me to
give a three minute update.
They are asking a bunch of people to give
updates on what is going on on campus.
And I'm like, you know, we are not
actually doing that much.
But it was actually interesting.
There were two camps.
There were people doing a lot or had more
of a programming background and thinking
about fancy tools we could develop.
And then there was all of us who were
like, we even think about how we should
use it more.
And so it was really great, though.
It was a two-day workshop.
And so the second day was
just breaking people into groups.
And so the first day we had brainstormed
different deliverables or things that we
could develop the second day.
And then breaking up into groups to
develop some of those things.
And so to start playing with
the tools a little bit more.
So some people were proposing how you
could use a chat GPT
tool to sort of create
study things for students or to give
automated feedback on their writing.
And so we started looking at the group I
was in was looking at
how do you use it to
help do a better job with figures.
And so we specifically then started
looking at how you
could use it to generate
Python code for you to do
some of this data analysis.
And so just to really think about in this
case, I got fiddling with stress strain
curves that I do in my intro class.
And so just thinking through things like
how could we, rather than thinking about
how do we use it to like, for good.
And so in my intro class, you know, it's
important for them to
be able to they collect
data, they do tensile tests in lab, but
they need to be able to like, you know,
determine not only the tensile strength,
that one's easy, but
they have to figure out
how do you select the points for the
elastic modulus and fit a line.
How do you determine the yield strength
and that like the
cognitive load of having to
try and figure out how to do that when I get some students in this class every year.
Who don't know how to use Excel.
And so we're having to like, you know,
get them up into the
basics of here's how to
use Excel.
Here's how to like insert equations.
Here's how to import data, you know, and
then like, that's just
a big jump that we're
really expecting in this intro level
class of having to fit
a line to only a subset
of points, move that line over by 0.2%
and look at where that line intersects.
Sorry.
In theory, intersects interpolates, you know, more than one point.
In theory, intersects interpolates, you
know, discrete data points.
It never intersects some nice pretty
curve, but these are
discrete data points.
And like, that's a lot of things that
we're having tasks that
we're having to get students
to do just to analyze this data.
And so, you know, are there things like
that that we should maybe consider about
lowering the cognitive load so that
students can focus on
the material science or the
things that we want them to learn and
less about this like
data analysis and maybe if
they could generate some Python code for
them to do it and they
want to do it that way,
like maybe there are
some opportunities there.
As long as you test whether or not it's
telling you the truth.
Oh, I mean, I could not.
I spent a while trying to get it to give
me the yield strength
correctly and it gave me
a lot of wrong yield strength.
And it's very polite when you tell.
That one didn't make it into our examples
that we were putting
in, you know, but it's
just realizing, I think, you know,
realizing I need to take
my head out of the sand.
You know, I can't sort of sit here and
pretend that it doesn't,
you know, chat GPT isn't
a thing.
I know it's here and it's
just going to get better.
And so, like, are there opportunities
rather than to see, say,
it's just going to be here
for bad, but like, are there
opportunities for it to
like critique figures and, you
know, give students some of that feedback
to help, like, you
know, manage our workload
but also give students, you know, just in
time, timely feedback.
One way.
So that was just interesting
discussions to have about that.
One way to get better quality answers is
to only use a curated data set.
So at Michigan, they've got this thing
where they can scrape
your Canvas website, pick
up all your recorded lectures, and that's
the only place where
the large language model
looks for answers.
So it's your own material.
And so we've just set that up.
And, of course,
students can ask any question.
And then at first, I was very critical of
it because it's like, come on, that's not
a very active learning activity to just
ask a question and get an answer.
And they said, no,
no, no, no, it's coming.
It's not there yet, but it's coming that
we're going to be able to respond with a
question to a student's question and give
them places to look.
Well, that day has already come.
They told me this two months ago, and
they just set me up for it yesterday.
And it is amazing.
I ask a question like,
what is an edge dislocation?
And it comes back and says, ah,
dislocations are a
very interesting topic.
They're used to describe, you know,
deformation in materials.
But to answer your question, you should
consider the following few
things and think about it.
And that's a much
better answer for a student.
It won't give them the answer, but guides
them on a path to discover it themselves.
So I'm very excited that that's here.
So we'll see.
But I agree with you.
You cannot put your head in the sand.
It's here.
The box is open.
It's out in the wild.
We either learn how to use
it or it could consume us all.
Yep.
We didn't throw away calculators.
We didn't throw away computers.
We didn't throw away.
Well, OK, some people
threw away their slide rules.
But, you know, it's a tool.
We have to figure out how to use it well.
Exactly.
As students said, let's use it for good.
My biggest fear with it is if it's going
to end up turning assessments into, you
know, because we need to
make sure that students are
mastering concepts.
My biggest fear is how do we keep it from
turning assessments and just being like,
well, we'll only do in person, in class
exams or, you know,
assessments like that.
Whereas I used to give a lot of my
ability to give assignments, they say
read and summarize a paper as a part of
their homework decreases.
And so how do I, you know, assess some of
that as well and get students to do those
those learning activities?
While it's fraught with problems, my
dream is that we can use generative A.I.
to actually do the assessment for our
students in terms of, say, an oral exam,
like we talked about.
Have you played with the OpenAI Apple,
you know, the OpenAI app?
You push the little headphones and you
can talk to it and it talks back to you.
It can hear.
It can understand what you're saying.
And very soon you get into a
conversation, you forget that it's a bot.
You think it's a human.
In fact, Tim and I were playing with it
and we said, what's your name?
I was like, no answer.
And we said, can we call you Mary?
And all of a sudden she says, well, you
can call me Mary if you
like, but my name is Max.
And if it could get to the point where
you could in the prompts that set it up,
interact with the student to assess
learning based on rubrics that you put
into it, it might make
an oral exam scalable.
Of course, it's going to take a lot of
work to make sure that it's telling you
the truth and not just hallucinating.
In fact, in the thing I just got from the
university or Mazey, they call it,
there's a little temperature slider.
And they said, you can think of it as
temperature, but we like to think of it
as the hallucination meter.
If you put it up to two,
it really hallucinates.
If you say, what's the color of the sky?
It'll say purple if you're
on this planet or something.
Yeah. And you can adjust how
creative you're going to let it be.
And this is happening so fast.
And, you know, they're
going to learn how to that.
They're not quite there
for figures and graphs.
They're not quite there with Greek and
equations, but it's going to happen soon.
So who knows?
I mean, it can already take your exam.
Liz Holm told us she gave
us her advanced thermo exam.
And this was then this
was almost a year ago.
Well, yeah, almost a year ago.
And it scored like eighty seven percent
on her really hard thermal exam.
So who knows?
I think it's going to
be very interesting.
You know, I saw the data of how they're
bragging how well it can do on the AP
exams and the bar exam and other.
On the other hand, a lot of
times it gets things dead wrong.
Like if you ask it to explain the
pedagogical value of midterms midterm
exams, it'll just go off and talk about
how wonderful they are.
And nothing's better than an exam. And then when you ask it, what about the
research that, you know, people forget
everything that they just presented two
days after they take the exam, it'll go,
well, there are a few
studies that say that.
But it's very funny.
People also at the workshop got talking
about different, you know,
everyone here is a chat G.B.T.
But there are other like
A.I. tools that can be useful.
I don't have them.
I don't remember them.
But, you know, in terms of
like, oh, you know, chat G.B.T.
Very bad at doing a literature review.
But there are sort of, you know, we're
identifying papers on a topic, but there
are other tools that are out there that
are more developed for
helping you find that.
And so, you know, again, opportunities to
use some of those tools to identify, you
know, key pieces of literature or help us
as researchers when we're, you know, we're trying to find out what we're doing.
You know, doing a literature review, you
know, so there are sort of,
you know, multitude of tools.
And so not just necessarily having to
think about, oh, it's
chat G.B.T. or nothing.
And so it's not just, well, chat G.B.T.
versus Google Gemini
versus, you know, this and that.
But other tools that are using some of
these these technologies.
I think that's a great approach when I'm
thinking about what tools do I want to
use or teach with my students.
The question is always, do I use this in
my own life, like my own professional
life? If so, yeah, it's probably worth
teaching because there are some tools
that have helped me out and saved me, you
know, a lot of wasted hours.
So may as well start
the conversation there.
Looking at the clock, though, we've had a
great conversation here.
I think it's time to wrap up.
Susan, before we call it a day, we always
like to offer the guests if there's
anything you want to brag about any plugs
you want to make just any any info you
want to get out there.
This is your free advertising platform.
So take it away if there's anything you
want the audience to know.
I don't know that I
have anything to advertise.
I just encourage you to get involved with
the materials community.
You know, there's a variety of
conferences and and things I'm involved
in the American Society
for Engineering Education.
We have a materials division.
There is the North American Materials
Education Symposium NAMES that, you know,
Steve was talking about at the beginning.
I'm also on the TMS Education Committee,
you know, so just opportunities for those
who are looking to to reach out and just
to get more connected and learn more
about teaching tools and teaching
opportunities in material science.
Fantastic. So I'm not going to be at the
TMS meeting, but I think Tim
is. Are you going to be there?
No, I'm not going to be there. I'm not
presenting and it's the
last week of the quarter.
Yeah, I'll be there next year when they
move the Judson Symposium there.
But at any rate, I hope we're going to
see you this summer at
NAMES. Are you coming?
I am planning an excuse to come out to
Ann Arbor. I think in August
is free. So yeah, that's great.
We're working very hard to keep the
registration costs low. It's going to be
250 bucks for the early bird.
So that should make it
easier for people to get here.
Well, great. Well, thank you so much. And
thank you to all of those who are
listening to this. And so I think with
that, we'll say goodbye. So thank you,
Susan. And talk to you later.
Yeah, see you next time.
Bye.