Hi. It's Paul Andersen. And this is disciplinary core idea ETS1C. It's
on optimizing the design solution. So in engineering remember the goal is to come up with the best
solution to a problem. And so this is the first iPod that was ever created. So what
is an iPod? It basically is, it was a hard drive. And you had to have some way to look
through the music that was on there. And so there was a screen. And then the first one
actually had a wheel, a mechanical wheel that would move in a circle so you could go through
all of your songs. Now it's clearly changed over time. But this was the best solution
to an MP3 player that Apple could come up with at that time. And so in engineering,
remember, the idea is to brainstorm and come up with as many solutions as you can. But
then you need to come up with the one best solution. And so when you're designing a best
solution, how do you come up with that? And so let me give you an example. And this is
from engageengineering.org. I got this example. And so let's say we were to ask you which
is the best fruit? Apples or oranges? Well you might say it's an impossible question.
But if you were an engineer and you were to look at this as an engineer would, you would
start to identify as many criteria as you can. And so you could survey people. And you
could ask them for example, which of the following tastes better? You could give them a sample
of each. You could look at color appeal of the fruit. You could look at the healthiness
of the fruit. So these are now just different criteria. Ways of looking at which is the
best fruit. You could look at the edible mass of an apple and an orange. Or you could look
at the edible mass percentage. In other words what percent of that fruit are you actually
able to eat. And so now we can start to quantify the solution for this question, which is the
best fruit? Now that is kind of a silly example. And so let me give you some real examples.
Lets say I am designing a part. And so this is going to be a part that goes in an engine.
What is the best solution to this problem? Or what is the best design that could actually
solve the problem I'm looking for? Well we could look at a number of different criteria.
We could look at the strength of it. We could look at the cost. And maybe the weight. And
a good way to think about that is to think of these as sliders. And so we could look
at the strength from very weak to very strong. We could look at the cost from very cheap
or inexpensive to very expensive. And then we could look at the weight from very light
to very heavy. And so what we can do is we can say, alright, let's build a design that's
going to be really strong. And so if I move strong over, that's going to make it more
expensive. And it's also going to be heavier. Let's say I want to make it really cheap.
I could move that cost slider all the way down. But that's going to make a product that
would be less strong. And it's also going to be slightly lighter. And let's say I want
to go ultra light, well that's going to make it really, really weak. And it's also going
to be really really expensive. And so what I can do is I can move these sliders back
and forth until I optimize a best solution. So let me give you a real example of that.
When they were designing the lunar module on the Apollo 11 mission, they were trying
to figure out how many legs that lunar module should have. It ended up having four. And
so this is a way they would look at just this one problem from the idea of engineering design.
And so if we start with the number of legs being 1, well that's going to be very unstable.
But it's also going to be a real light module. And so what happens if we increase the leg
number to 2? Well it's not very stable still. It's just going to fall over. And it's increasing
the weight. Let's go to three. Now we get a huge increase is stability. We also see
an increase in weight. Let's go to four. You can see the stability jumps way up and we've
made it heavier. So let's go to 5 legs and you'll find that as we go to 5 legs it just
gets a little safer. And little more stable. But we're increasing weight. And when you're
traveling through space, weight is a huge deal. And so what they do is they settle on
four legs which is going to be optimizing the solution. In other words we're looking
at all the trade-offs to come up with the best solution that we possibly can. Now you
also have to look at the time and the place as another slider. And so let me give you
an example of that. How do we move products around on our planet today? We use these giant
cargo ships. These are the most efficient way to move material, for example, from Asia
to the States. And so if we were to look back in time that solution would be different.
We would have used giant clippers that use sails to move materials from one place to
another. And so that was the best solution at that time. It's not the best solution now,
but it was the best solution at that time. And what about in the future? Well ironically
were going to go back to sails. And so as fuel costs become bigger. As we start to get
restrictions on fossil fuels being released into the atmosphere, there's a lot of engineers
who are looking at solutions that actually contain computer controlled sails. They're
actually going to start to look like this. And if you're interested in that you can look
at one company that's starting a model of this. It's called B9 Energy. And that's kind
of a funny play on words. And you could look at some of their designs. And so how do we
teach this? In other words what's the teaching progression? Well in the lower elementary
grades you want your students building design. So here they're trying to build a little telephone
that you can communicate between two people. You can see it's not going to work very well
because it's not very taut. They string between them. You want them building designs. You
want the comparing those designs. And then you want them testing their designs. And so
how could you do this with this little telephone? We could do it with a very taut string. Or
we could have it very loose. We could use different things for the string. We could
use wire for example. And what you're students could do is look at strengths and weaknesses
of those different designs. As we move into upper elementary grades we want them thinking
about constraints and criteria. Remember the constraints are going to be the needs of a
project. And the criteria are going to be the wants. And so a famous project that's
used in schools, and it's good, is the building of wooden bridges. Usually you build these
out of balsa wood. And so what we could do is we could say, this is the wood that you
get. These are going to be all of the constraints. This is how far your bridge has to span. And
then I want you to build a bridge that can hold the largest amount of weight. As we move
into middle school then you want to start giving them different tests. And so generally
when the bridge building is given you're just testing how much weight you can have. But
there's other test you can do. You could do how much does your bridge weigh? That could
be one test. Who can make it the lightest? Who can make it the strongest? Who can do
it for the least amount of money? Who can spend the least amount of time actually building
it? And so once we start doing that, then you can see that we're starting to optimize
a best solution. And then as we move into high school we really want to start talking
about this process of optimization. In other words not just testing one thing, but testing
three things. And you want your students going through all of these different designs to
come up with the optimized solution. In other words the best solution at that time. And
so we do this in the real world as well. And you want them to understand that as we get
bigger and bigger projects we have to add additional criteria to that. So this the Golden
Gate Bridge. And when they were building the Golden Gate Bridge they had to come up with
a lot of different criteria. It had to span a certain distance. Carry a certain number
of cars over it. The fog is a big deal in San Francisco and so the color of the bridge
was a big deal. The military wanted to paint it with black and yellow stripes on its surface.
And so thankfully they didn't listen to that. They balanced the aesthetics, how does it
look? It's impacts on the environment. Social impacts. Even cultural impacts. And if we
look at all of those criteria we can come up with the best solution. And the Golden
Gate Bridge does that. It balances all these different criteria. And is was actually voted
as one of the wonders of the modern world. And so that's how we optimize solutions. Taking
all of these different tests. All of these different criteria. Using trade-offs to come
up with the best solution. And I hope that was helpful.