Undercooled: A Materials Education Podcast

[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.