Undercooled: A Materials Education Podcast

Hello and welcome to

another episode of Undercooled.

Today, Tim and I have

a very special guest.

It's someone that we're

not sure what her name is.

We tried calling her Mary and

she told us her name was Max.

We'll find out today because we're going

to do a podcast interviewing Ms. Chat GPT

from the OpenAI app.

So let's start and see

if she'll do this with us.

So Chat GPT.

Hey, would you be willing to

let us do a podcast with you?

Yes, that's me.

How can I assist you further?

We'd like to know if you

would do a podcast with us.

Can we interview you?

I'm flattered.

While I can't physically

participate in a podcast,

I'm here to provide information, answer

questions, and engage in conversations.

If you have specific

topics or questions in mind,

feel free to ask and we can certainly

have a chat about them.

All right, let's start.

What should we call you?

Is your name Mary?

You can call me Chat GPT.

That's the name I go by.

It stands for Chat

Generative Pre-Trained Transformer.

So no, my name isn't Mary,

but you can call me Chat GPT.

All right.

Well, Chat GPT, what do you think are the

best pedagogical techniques

to teach material

science and engineering?

Teaching material science and engineering

effectively often

involves a combination of

hands-on experiments, visual aids like

diagrams and models,

interactive discussions, and

problem-solving exercises.

Additionally, incorporating real-world

examples and applications

can help students understand

the relevance and practical implications

of the concepts being taught.

It's also important to tailor teaching

methods to suit different learning styles

and provide opportunities for active

participation and engagement.

Thank you.

And I'm here with my co-host, Tim, who's

going to ask you some questions too.

Go ahead, Tim.

Thanks, Steve.

So, Chat GPT, what do you think are the

best ways to assess learning

about material science and engineering?

Hey, Tim.

Great question.

Assessing learning and

material science and engineering

can be done through various methods.

Such as written exams, practical

demonstrations, lab

reports, projects, presentations,

and even peer evaluations.

It's important to use a mix of formative

and summative assessments

to gauge both understanding

of concepts and the ability to apply them

in different contexts.

Additionally, providing constructive

feedback and opportunities for reflection

can enhance the learning process.

That's not bad.

Not bad at all.

Do you think that summative assessment is

better or worse than

formative assessment?

And why?

Both summative and formative assessments

serve important purposes

in the learning process.

Summative assessments, such as final

exams or projects, are

typically used to evaluate

students' overall understanding and

proficiency at the

end of a unit or course.

On the other hand, formative assessments,

like quizzes or class discussions,

provide ongoing feedback to students

during the learning process,

helping them identify areas for

improvement and adjust their learning

strategies accordingly.

Neither type of assessment is inherently

better or worse than the other.

Rather, they complement each other and

serve different purposes.

Summative assessments offer a

comprehensive

evaluation of learning outcomes,

while formative assessments support

ongoing learning and skill development,

utilizing both types

of assessments in tandem

can provide a more comprehensive

understanding of students'

progress and learning needs.

Well, thank you.

That was a very thorough answer.

You're welcome.

I'm glad you found the answer helpful.

If you have any more questions, or if

there's anything else

you'd like to discuss,

feel free to let me know.

Yes, I'd like to ask, do you think

lecture should be used or

removed for a first introduction

to new material in a class, should

instead reading be used

for the first time students

are introduced to a new topic?

The effectiveness of using lectures

versus readings as the first

introduction to new material

can depend on various factors,

including the subject matter,

the learning preferences of students, and

the overall course structure.

Lectures can provide a structured

overview of key concepts delivered by an

expert in the field,

and can help set the stage for further

exploration and understanding.

However, lectures should be engaging and

interactive to ensure

student participation

and comprehension.

On the other hand, readings can allow

students to explore new

material at their own pace,

engage with the content in depth, and

facilitate critical

thinking and analysis.

Readings can also provide additional

context and perspectives

that may not be

covered in lectures alone.

In many cases, a combination of lectures

and readings may be most effective,

allowing students to benefit from both

direct instruction and

independent exploration.

Ultimately, the choice between lectures

and readings as the first

introduction to new material

should be based on the specific needs and

preferences of the students,

as well as the learning

objectives of the course.

So, ChatGPT, you keep mentioning in

several of your answers about

learning styles of students,

but I've read several meta-studies, very

large meta-studies, that show that

there's really no such

value in learning styles, and that it's

all kind of nonsense that

students who claim they are,

have a learning style for visual, or

auditory, or reading,

or something like that,

actually has absolutely no, there's no

valid evidence that people

really have learning styles.

What do you think about that?

You bring up an important point. While

the concept of learning

styles has been widely discussed,

and even incorporated into educational

practices, there is indeed

ongoing debate and research

questioning its validity. Some studies

suggest that the idea of

distinct learning styles,

such as visual, auditory, or kinesthetic,

may be oversimplified and

not strongly supported by

empirical evidence. Instead, it's been

proposed that individuals may have

preferences for certain

learning modalities, but these

preferences may not necessarily correlate

with improved learning

outcomes. In other words, while some

students may express a

preference for visual learning,

for example, it doesn't necessarily mean

that presenting

information visually will lead to

better learning outcomes for them. As

educators, it's important to consider a

variety of instructional

methods and adapt teaching approaches to

accommodate different learning

preferences and needs. However,

rather than focusing solely on catering

to specific learning styles, it may be

more beneficial to employ

a variety of instructional strategies

that engage students in

different ways and promote active

learning and critical thinking skills.

Thank you, GPT. I think Tim's going to

ask the next question.

Sure thing. Go ahead, Tim. What's your

next question? Chat GPT.

We've been talking about

classrooms. Now let's talk about

laboratories. What laboratory skills

should a material science

and engineering student learn in their

laboratory classes? In laboratory classes

for material science

and engineering, students should develop

a range of practical skills that are

essential for conducting

experiments, analyzing materials, and

understanding their properties and

behaviors. Some key laboratory

skills include, one, safety procedures,

understanding and

adhering to safety protocols,

including proper handling of chemicals,

equipment, and protective gear. Two,

measurement techniques,

proficiency in using various measurement

instruments, such as

micrometers, calipers,

and spectroscopes to accurately measure

dimensions, properties, and compositions

of materials. Three,

sample preparation, learning how to

prepare samples for analysis,

including cutting, polishing,

mounting, and coating specimens for

microscopy, and other

testing methods. Four, material

characterization, familiarity with

techniques such as microscopy, optical,

electron scanning probe,

x-ray diffraction, spectroscopy, and

thermal analysis for

characterizing material structure,

composition, and properties. Five,

experiment design and execution,

planning, conducting,

and documenting experiments effectively,

including data collection,

analysis, and interpretation.

Six, problem solving, developing critical

thinking skills to troubleshoot

experimental issues,

identify sources of error, and optimize

experimental

procedures. Seven, collaboration,

working collaboratively with peers,

instructors, and research mentors to

achieve common goals and

share knowledge and expertise. Eight,

communication, effectively communicating

experimental findings

and conclusions through written reports,

oral presentations, and

visual aids. These laboratory

skills are essential for materials

science and engineering students to apply

theoretical concepts

learned in the classroom to real-world

materials and practical applications.

Okay, you just mentioned

students working in teams and doing

projects together. How could

I fairly grade my individual

students when they're working on team

projects together? Grading

individual students in team

projects requires a thoughtful and fair

approach to assess each student's

contributions accurately.

Here are some strategies you could

consider. One, clear expectations.

Clearly define the roles and

responsibilities of each team member from

the outset of the project.

This helps set expectations

and ensures everyone understands what is

expected of them. Two, peer

evaluation. Incorporate peer

evaluations where team members provide

feedback on each other's

contributions, work ethic,

communication skills, and collaboration.

This can provide valuable

insights into individual

performance within the team. Three,

contribution logs. Have

students maintain logs or journals

documenting their contributions to the

project, including tasks

completed, ideas generated, and

challenges encountered. This can help

students reflect on their

own involvement and provide

evidence of their contributions. Four,

individual components. Assign specific

individual components

or tasks within the team project that

each student is responsible

for. Evaluate these components

separately to assess individual

performance. Five, teamwork skills.

Consider grading students on

their ability to work effectively within

a team, including communication,

collaboration, leadership,

and problem-solving skills. These skills

are valuable in

professional settings and can be

assessed through observations, peer

feedback, and self-assessment. Six,

rubric-based assessment.

Develop a detailed rubric outlining the

criteria for grading individual

contributions to the project.

Include criteria related to both the

quality and quantity of

work, as well as factors such as

initiative, creativity, and

accountability. Seven, teacher

observation. Observe team interactions

and meetings and take note of each

student's level of participation,

engagement, and contribution.

This can provide additional insights into

individual performance within the team.

By employing a combination of these

strategies, you can fairly evaluate

individual students'

contributions to team projects, while

also promoting collaboration

and teamwork skills development.

Wow, that was a lot. And I didn't hear

you say about using any tools like

CATME.org, which gives surveys to

students to have them

evaluate each other and themselves

on team skills. What about things like

that? You're absolutely

right. Tools like CATME.org,

which facilitate peer evaluations and

self-assessments on team skills,

can be incredibly valuable for assessing

individual

contributions in team projects.

These tools provide structured surveys

that allow students to evaluate

themselves and their peers

based on specific teamwork criteria, such

as communication,

leadership, and accountability.

Using such tools can complement other

assessment methods by providing

additional perspectives on

individual performance within the team.

Incorporating peer

evaluations and self-assessments

can help validate students'

contributions, promote self-reflection,

and encourage accountability for

their roles in the team. Thank you for

mentioning this important

aspect, and I appreciate the

opportunity to emphasize the value of

utilizing such tools in

assessing team projects.

So I am starting to redesign my

introduction to material

science and engineering course.

We're using a book like Callister's

Principles of Material

Science, and I'm trying to develop

standards so that I can measure my

students' progress in the

course. And by standards, I mean

a list of things that a student should be

able to do after taking

the course. What do you think

that list should be comprised of? When

developing standards to

measure students' progress

in an introduction to material science

and engineering course,

it's important to consider

the foundational knowledge, skills, and

competencies that students should acquire

by the end of the course. Here are some

suggested components for your list of standards.

your list of standards.

One, fundamental concepts.

Demonstrate understanding of basic

principles and concepts

in material science and engineering,

including atomic

structure, crystallography,

phase diagrams, and

mechanical properties of materials.

Two, material properties.

Identify and explain the

key properties of materials,

such as mechanical, thermal, electrical,

and magnetic properties, and--

Understand how these properties relate to

material structure and composition.

Material characterization techniques.

Familiarity with

common techniques used to

characterize materials, including

microscopy, optical, electron, x-ray

diffraction, spectroscopy,

and thermal analysis, and ability to

interpret experimental data. Material

selection and design.

Apply knowledge of material properties

and performance

criteria to select appropriate

materials for specific engineering

applications and design considerations.

Materials processing.

Understand the principles and techniques

used in materials

processing, such as casting, forming,

machining, and heat treatment. And

recognize how processing

affects material structure and

properties. Six, failure analysis.

Analyze and interpret

material failures and understand the

underlying mechanisms, including

fracture, fatigue,

corrosion, and creep, to inform design

and mitigation strategies. Environmental

and societal considerations.

Recognize the environmental

and societal impacts of material

selection, processing, and

use, and apply principles of

sustainability and ethics in materials

engineering practice. Eight,

communication and teamwork.

Effectively communicate technical

concepts and findings

through written reports,

oral presentations, and visual aids, and

collaborate with

peers in team projects and

discussions. By establishing clear

standards, encompassing

these key areas, you can provide

students with a roadmap for success in

the course and ensure that

they develop a strong foundation

in material science and engineering

principles. These standards can also

serve as a basis for

designing assessments and evaluating

students' achievement

of course objectives.

Okay. These introductory courses are

taken by all different kinds of

engineering students.

Do you think the standards or the

outcomes should be different for material

science students who

will major in material science instead of

other engineering majors?

Please give me a concise

answer. Yes. The standards or outcomes

for material science

students may need to be more

in-depth and specialized compared to

those for other engineering

majors. As material science

students will likely require a deeper

understanding of material properties,

characterization techniques, and

processing methods

specific to their field of study.

So our materials program, most materials

programs are accredited by

ABET. Do you think there's any

value in having material science and

engineering programs accredited by ABET?

And if so, what is the

value? Yes. There is value in having

material science and

engineering programs accredited by

ABET. Accreditation ensures that programs

meet rigorous standards of

quality and effectiveness

in preparing students for careers in the

field. It provides assurance

to students, employers, and

the public that graduates have acquired

the necessary knowledge,

skills, and competencies to

excel in their profession. Additionally,

ABET accreditation can

enhance the reputation and

credibility of a program, facilitate

student transfer and

mobility, and promote continuous

improvement through regular assessment

and evaluation. Okay. Now let's talk

about the difference

between different engineering majors.

Many students come into the university

trying to choose between

chemical engineering and material science

and engineering. What

are the main differences

between chemical engineering and material

science and engineering? Chemical

engineering and material

science and engineering are related

fields but have distinct focuses and

areas of specialization.

Here are some of the main differences

between the two disciplines. One, focus.

Chemical engineering

primarily deals with the design,

operation, and optimization

of processes involving the

transformation of raw materials into

useful products such as

fuels, chemicals, pharmaceuticals,

and materials. Material science and

engineering, on the other

hand, focuses on the study of the

structure, properties, processing, and

performance of materials including

metals, ceramics, polymers,

and composites and their applications in

various industries. Two,

scope. Chemical engineering

encompasses a wide range of industries

and applications

including energy production,

chemical manufacturing, pharmaceuticals,

environmental

engineering, and biotechnology.

Material science and engineering,

meanwhile, covers the design and

development of materials

for specific applications such as

electronics, aerospace, automotive,

biomedical, and renewable

energy technologies. Three, core

principles. Chemical

engineering involves principles of

chemistry, physics, mathematics, and

engineering to understand and optimize

chemical processes and

reactions. Material science and

engineering integrates

concepts from physics, chemistry,

mechanics, and materials science to

investigate the structure-property

relationships of materials

and develop new materials with tailored

properties. A four, approach. Chemical

engineers often work

with large-scale processes and systems

focusing on mass and energy

transfer, reaction kinetics,

and process optimization. Materials

scientists and engineers, on the other

hand, conduct experiments

and simulations to understand the atomic

and molecular structure

of materials, characterize

their properties, and design novel

materials with specific properties for

different applications.

While there is some overlap between the

two disciplines,

particularly in areas such as

materials processing and synthesis,

chemical engineering, and materials

science and engineering,

each offer unique perspectives and

opportunities for students

interested in pursuing careers in

these fields. Ultimately, the choice

between the two majors depends on

individual interests,

career goals, and preferred areas of

specialization.

So, Chat GPT

What is the best way to use generative AI

when we teach our students in a

traditional lecture class?

Generative AI can be used in traditional

lecture classes to

enhance student engagement,

promote active learning, and facilitate

understanding of

complex concepts. Here are

some ways to effectively integrate

generative AI into teaching. One,

interactive demonstrations.

Use generative AI tools to create

interactive demonstrations or simulations

that illustrate abstract concepts and

theories in a visually engaging manner.

For example, you could use AI-generated

visualizations to show

how materials respond

to different environmental conditions or

processing techniques. Two,

problem-solving exercises.

Incorporate generative AI algorithms into

problem-solving

exercises where students can

apply computational methods to analyze

and solve real-world engineering

challenges. For instance,

students could use AI-generated models to

predict material

properties or optimize material

compositions for specific applications.

Three, collaborative

projects. Encourage collaborative

projects where students work together to

develop AI-driven

solutions to material science and

engineering problems. For example,

students could use generative AI

techniques to design new materials

with desired properties or to optimize

manufacturing processes for

efficiency and sustainability.

Four, data analysis and interpretation.

Teach students how to use

generative AI tools to analyze

experimental data, identify patterns, and

extract meaningful insights.

This could involve training

AI models to classify materials based on

their properties or to

predict material behavior under

different conditions. Five, research

applications. Introduce students to

cutting-edge research in

material science and engineering that

leverages generative AI techniques for

materials discovery,

design, and optimization. Encourage

students to explore interdisciplinary

research topics that

combine AI and material science

principles. By integrating generative AI

into traditional lecture

classes, you can provide students with

hands-on experience with

advanced computational tools

and prepare them for careers in a rapidly

evolving field where AI

is increasingly playing a

significant role. That all sounds really

good, but how are we to know

whether we should trust? I'm

glad you think so. If you have any more

questions or if there's anything else

you'd like to discuss,

feel free to let me know. I'm here to

help. So I want to know how students can

trust generative AI.

What are the best ways for a student to

make sure that they're

getting the correct answers

when they use generative AI? Ensuring the

reliability and accuracy of generative AI

outputs is crucial for students using

these tools for learning and research.

Here are some best practices for students

to verify the correctness

of generative AI results.

1. Validate with multiple sources.

Cross-reference generative AI outputs

with information from

reputable sources such as textbooks,

peer-reviewed journals, and

authoritative websites to confirm

consistency and accuracy. 2. Understand

limitations. Recognize the limitations

and assumptions of the

generative AI model being used, including

its training data,

algorithms, and potential biases.

Be cautious of extrapolating results

beyond the model's intended

scope or domain. 3. Evaluate

credibility. Assess the credibility and

expertise of the creators or developers

behind the generative

AI tool. Look for evidence of rigorous

testing, validation, and

peer review to ensure the

reliability of the output. 4. Verify

against known data.

Compare generative AI predictions

or simulations against known experimental

data or theoretical models

to validate their accuracy

and predictive capability. Identify

discrepancies and

investigate potential sources of error.

5. Iterative refinement. Use generative

AI outputs as a starting

point for further analysis

and refinement rather than relying solely

on automated results.

Engage in critical thinking

and problem solving to interpret and

contextualize the outputs within the

broader context of the

research question or learning objective.

6. Seek expert guidance.

Consult with instructors,

mentors, or domain experts for guidance

and interpretation of

generative AI output,

particularly in complex or unfamiliar

areas. Leverage their

expertise to validate results

and gain deeper insights into the

underlying principles. By

following these guidelines,

students can effectively leverage

generative AI tools while maintaining a

critical and discerning

approach to verifying the correctness and

reliability of the

outputs. It sounds like

understanding how to correctly use

generative AI will be very

important for our students.

When a new MSE graduate starts their

career and begins working, what are the

three most important

things they should know about their work

life? As new material science and

engineering MSE graduates

enter the workforce, there are several

key considerations that

can help them navigate their

career successfully. Here are three

important things they should know. 1.

Continuous learning.

The field of MSE is constantly evolving

with new materials,

technologies, and techniques emerging

regularly. It's essential for new

graduates to embrace a mindset of

lifelong learning and stay

abreast of advancements in the field

through professional development

opportunities, continuing

education, and networking with peers and

experts. 2.

Problem-solving skills. MSE professionals

encounter a wide range of complex

challenges in their work.

From designing novel materials to

optimizing manufacturing processes to

addressing material failures, developing

strong problem-solving

skills, critical thinking abilities, and

analytical reasoning is crucial for

effectively addressing

these challenges and finding innovative

solutions. 3. Communication and teamwork.

MSE professionals often collaborate with

multidisciplinary

teams comprising engineers,

scientists, researchers, and stakeholders

from various industries.

Effective communication

skills, both written and verbal, are

essential for conveying technical

information, sharing ideas,

and collaborating effectively with

colleagues. Additionally, the ability to

work collaboratively

and contribute positively to team

dynamics is vital for success

in diverse work environments.

By focusing on continuous learning,

honing problem-solving skills, and

cultivating effective

communication and teamwork abilities, new

MSE graduates can thrive

in their careers and make

meaningful contributions to the field of

material science and engineering. Thank

you. That was really

good. Before I ask my last question, I

want to let you know that

we're having the North American

Materials Education Symposium from August

7th through 9th here

in Ann Arbor, Michigan.

And chat GPT, I hope you can log on to

our website and come visit us because it

would be great to hear

your opinions at the meeting. Do you

think you'll be able to make it? Thank

you for the invitation.

So one last question. Since you're so

good at answering these,

I have to ask the ultimate

question. What is the meaning of life?

Ah, the age-old question.

The meaning of life can vary

greatly from person to person, as it

often depends on individual beliefs,

values, and experiences.

For some, it may involve finding

fulfillment and purpose

through personal relationships,

meaningful work, or spiritual growth.

Others may see it as a

journey of self-discovery,

learning, and making a positive impact on

the world around them.

Ultimately, the meaning of life is a

deeply personal and

subjective concept that each

individual must explore and define for

themselves. Thank you. Bye. Okay, thank

you very much for being

our guest today, chat GPT. We're going to

end the interview now.

You're very welcome. It was a

pleasure being your guest today. If you

ever have more

questions or want to chat again,

don't hesitate to reach

out. Goodbye and take care.