Genes, proteins, and traits

WEBVTT
Kind: captions
Language: en

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- [Instructor] Hi, everyone.

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This video is all about
how the information

00:00:03.750 --> 00:00:07.110
in an organism's genes is
expressed as its traits.

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This occurs through the action
of molecules called proteins.

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But before we get into the details,

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let's start with the basics.

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What are traits?

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Well, traits are an organism's
observable characteristics,

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and there are some really weird

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but really cool traits out
there in the animal kingdom.

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Spiders, for example,

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can make seven different types of silk.

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Elephants have an amazingly
low risk of developing cancer.

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And some jellyfish have
the ability to glow.

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That's right!

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The crystal jelly can bioluminesce,

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or glow in the dark, all on its own.

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So now let's dive into the details

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of how these traits are expressed.

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Specifically, let's look at

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the jellyfish trait of bioluminescence.

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We know that an organism's
traits are affected by its genes.

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So let's travel into the nucleus

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of the crystal jelly's cells
to where its genes are found,

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on chromosomes.

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A chromosome shown here
is a cell structure

00:01:04.500 --> 00:01:07.590
that contains a coiled up DNA molecule.

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I personally like to think of chromosomes

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as the packaged and
organized version of DNA.

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A DNA molecule is made up of
subunits, called nucleotides.

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Nucleotides are often
called A, T, C, and G,

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which stand for adenine,
thymine, cytosine, and guanine.

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A gene is a specific stretch

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or a chunk of nucleotides
within a DNA molecule.

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So a chromosome and its
DNA are like a cookbook

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that contains recipes
for making an organism.

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Genes are the recipes.

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And just like how letters are
arranged in a specific order

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to form words in a recipe,

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the nucleotides in a gene

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are also arranged in a specific
order to convey information.

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So what does the cell make
with these gene recipes?

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The cell uses the information in genes

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to make other molecules called proteins.

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So our crystal jelly must
have genes on its chromosomes

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that are responsible for its
trait of bioluminescence.

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Because of work done by scientists,

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we now know that the jelly
fish's bioluminescence

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involves one gene in particular.

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The coding sequence of this gene

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is made up of roughly 700 nucleotides,

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all arranged in a specific order.

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And this gene acts like a
recipe for making a protein

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called green fluorescent
protein, or GFP, for short.

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Whenever you hear the word fluorescent,

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just think glowy.

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GFP is a glowy protein
that can emit green light.

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And it's this presence of
GFP in the jelly fish's cells

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that allows the jellyfish to bioluminesce.

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But proteins can do so
much more than glow.

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There are thousands of tasks

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that different proteins carry out

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in order for cells to function.

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Some proteins help provide structure,

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some help move substances
into and out of the cell,

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and others help carry
out chemical reactions.

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All proteins are made up of
subunits called amino acids

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which are connected in a chain.

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It's the order of nucleotides in a gene

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that determines the order
of amino acids in a protein.

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And the order of amino acids is important

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because it determines the 3D shape

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that the protein will take on.

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And a protein's shape, in
turn, affects its function.

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For the GFP protein,

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this protein has a special
sequence of three amino acids

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that end up in the middle
of a barrel-like structure

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when the protein takes on its 3D shape.

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These amino acids form
the part of the protein

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that can fluoresce.

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They can absorb energy

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and then emit that energy as green light.

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So to sum it all up, genes affect traits

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through the actions of the
proteins that they encode.

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The order of nucleotides in a gene

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determines the order of
amino acids in a protein.

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And a protein's amino acids
determines its structure

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and its function.

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The crystal jelly's bioluminescence

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and the discovery of GFP

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highlight why this
knowledge is so important.

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Scientists have used
the GFP gene and protein

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to make countless discoveries.

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Now, researchers can
attach GFP to other things,

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such as other proteins or viruses,

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making them visible
through bioluminescence

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and easy to track.

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GFP has made the invisible visible,

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and it's allowed researchers
to learn how neurons develop

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and how cancer cells spread.

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And all of this research started

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with wondering about a single trait

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observed in the crystal jelly.

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Similarly, scientists are
studying the properties

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of spider silk proteins

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in order to make new
biocompatible materials.

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And they're also studying elephants

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for clues about how to
prevent cancer in humans.

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What animal trait do you think will lead

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to the next big discovery?


Chromosome pairs

WEBVTT
Kind: captions
Language: en

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- [Instructor] - Hi, everyone.

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Today, we're gonna talk
about chromosome pairs.

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But first, I've got a question for you.

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Between a black mulberry plant,

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a Guinea pig, and a human being,

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which organism do you think
has the most chromosomes?

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The mulberry plant has green
leaves and delicious berries.

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The Guinea pigs are adorable, tiny mammals

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with multiple body systems

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and humans have incredibly powerful brains

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and the ability to form
complex social relationships.

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Before I tell you the answer,

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let's learn a little
more about chromosomes.

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Chromosomes are structures that
contain an organism's genes.

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And genes are the units of heredity

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passed from parent to offspring

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that affect an organism's traits.

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Chromosomes, and the genes they contain,

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are located inside an organism's cells.

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In multicellular organisms,

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the chromosomes are found
within the cell's nucleus.

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Many species have chromosomes
that come in matched pairs.

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For example, here's an image
taken with a microscope

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of chromosomes from a
typical human body cell.

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The chromosomes are laid
out in an organized way,

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allowing us to see that
humans have 46 chromosomes,

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which can be organized into 23 pairs.

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Each of these is a pair of chromosomes.

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This is one chromosome,

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and this is the second chromosome.

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These paired chromosomes are
called homologous chromosomes.

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Homologous chromosomes have
the same size and shape.

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They also contain the same
genes in the same locations.

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Remember, an organism's
genes affect its traits.

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Genes often come in different
variations, called alleles.

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Different alleles of a gene

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can cause different versions of a trait.

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In an organism, a pair
of homologous chromosomes

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may have the same allele for a gene,

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or they may have different
alleles for a gene.

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To help us understand this,

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let's take a look at
an illustrative example

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using pea plants.

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Pea plants can have
pink or purple flowers.

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These colors are determined
by two different variations,

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or alleles, of a single flower color gene.

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Pea plants have a copy
of this flower color gene

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on each of two chromosomes
in a homologous pair.

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A single pea plant may have
two copies of the pink allele,

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two copies of the purple
allele, or one copy of each.

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The color of flowers that
the pea plants end up with

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depends on how the alleles interact.

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But we'll cover that in another video.

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An image like this one,

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of an individual's chromosomes,

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lined up in an organized way,

00:02:23.670 --> 00:02:26.160
is called a karyotype.

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Scientists and medical professionals

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can examine an individual's
karyotype under the microscope

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to see if they might
have a genetic condition.

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This could show up as size differences

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between chromosomes within
each homologous pair

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or the presence of an extra chromosome.

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Now that you're a little more
familiar with chromosomes,

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let's return to the question I asked

00:02:46.170 --> 00:02:48.300
at the beginning of this video.

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Between black mulberry plants,
Guinea pigs, and humans,

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which organism has the most chromosomes?

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Any guesses?

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The black Mulberry plants do!

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These plants have a
whopping 308 chromosomes.

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Guinea pigs come in second
with 64 chromosomes.

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And like we said earlier,

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us humans only have 46 chromosomes.

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So we come in third.

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Are you surprised?

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Believe it or not,

00:03:13.620 --> 00:03:17.580
humans, with their big brains
and complex social structures

00:03:17.580 --> 00:03:19.440
actually have far fewer chromosomes

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than many seemingly
less complex organisms.

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Are black mulberry plants

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more complicated than we perceive?

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Perhaps.

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And perhaps there is more

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to understanding the role chromosomes play

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in determining traits.

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That's it for today, thanks for watching.


Chromosomes and genes

WEBVTT
Kind: captions
Language: en

00:00:00.240 --> 00:00:03.140
- [Lecturer] This is a super cute puppy.

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He has a pink tongue, black fur,

00:00:05.470 --> 00:00:08.040
and very friendly personality.

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We know that when this puppy grows up,

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he will have a healthy
weight of about 70 pounds,

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he will love to play fetch,

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and enjoy snuggles with his human family.

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We know this because these traits

00:00:21.410 --> 00:00:24.130
are typical of his breed, Labradors.

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But where do these traits come from?

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In this video, we're gonna find out.

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But first, let's start at the beginning.

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What exactly are traits?

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Traits are specific
observable characteristics.

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They can be physical, like
our puppy's eye color.

00:00:43.300 --> 00:00:44.630
They can be behavioral,

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such as a dog being
more or less aggressive

00:00:46.960 --> 00:00:48.410
towards strangers.

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Or they can be health
related, such as a dog's risk

00:00:51.470 --> 00:00:54.100
of developing a certain disease.

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Traits are passed from
parents to offspring.

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This is why our puppy looks
so similar to his parents

00:01:00.640 --> 00:01:03.020
who were also Labradors.

00:01:03.020 --> 00:01:05.080
But, how does this occur?

00:01:05.080 --> 00:01:09.350
Well, traits are passed on
from one generation to the next

00:01:09.350 --> 00:01:12.020
through the inheritance of genes.

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Genes are pieces of hereditary material

00:01:14.330 --> 00:01:16.733
that are passed from parents to offspring.

00:01:17.790 --> 00:01:20.520
Genes are found inside
of an organism's cells

00:01:20.520 --> 00:01:23.670
as part of structures called chromosomes.

00:01:23.670 --> 00:01:25.520
In multicellular organisms,

00:01:25.520 --> 00:01:29.290
chromosomes are found
inside the cell nucleus.

00:01:29.290 --> 00:01:32.610
Chromosomes are often shown
as X-shaped structures

00:01:32.610 --> 00:01:33.473
like this one.

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Each chromosome is a structure

00:01:37.060 --> 00:01:42.060
that contains one long molecule
of DNA, which stands for

00:01:43.581 --> 00:01:46.520
♪ Deoxyribonucleic acid ♪

00:01:46.520 --> 00:01:47.830
All right, sing it with me.

00:01:47.830 --> 00:01:51.210
♪ Deoxyribonucleic acid ♪

00:01:51.210 --> 00:01:53.670
Or DNA, for short.

00:01:53.670 --> 00:01:57.140
Here's a model showing a small
stretch of a DNA molecule.

00:01:57.140 --> 00:01:59.160
You can see that it's made up of lots

00:01:59.160 --> 00:02:03.220
of different atoms represented
by these colored balls.

00:02:03.220 --> 00:02:06.260
The DNA molecule in a
chromosome is like this,

00:02:06.260 --> 00:02:08.363
but much, much longer.

00:02:09.380 --> 00:02:11.640
A chromosome's DNA molecule is coiled

00:02:11.640 --> 00:02:13.750
up in an organized way.

00:02:13.750 --> 00:02:16.450
This diagram shows what
the DNA would look like

00:02:16.450 --> 00:02:18.560
if it were stretched out.

00:02:18.560 --> 00:02:19.760
This allows us to see

00:02:19.760 --> 00:02:22.780
where a chromosome's genes are located.

00:02:22.780 --> 00:02:27.003
Genes are specific stretches
of a chromosome's DNA molecule.

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Each chromosome's DNA can contain hundreds

00:02:31.270 --> 00:02:33.600
or even thousands of genes.

00:02:33.600 --> 00:02:35.740
And in multicellular organisms,

00:02:35.740 --> 00:02:38.950
each cell contains multiple chromosomes.

00:02:38.950 --> 00:02:41.200
It's the collection of
genes and chromosomes

00:02:41.200 --> 00:02:42.690
that contain the information

00:02:42.690 --> 00:02:45.793
about all of an organism's
inherited traits.

00:02:46.840 --> 00:02:49.940
Like our puppy here, his
chromosomes contain thousands

00:02:49.940 --> 00:02:53.820
of genes to help him determine
his coat color, eye color,

00:02:53.820 --> 00:02:57.160
and all the other traits he
inherited from his parents.

00:02:57.160 --> 00:03:00.530
So our puppy must have one or more genes

00:03:00.530 --> 00:03:02.760
that caused him to have black fur.

00:03:02.760 --> 00:03:04.560
If he had been born
with different versions

00:03:04.560 --> 00:03:07.350
of the fur colored genes,
he may have had yellow

00:03:07.350 --> 00:03:08.920
or brown fur.

00:03:08.920 --> 00:03:11.110
Heck, maybe one day
someone will figure out

00:03:11.110 --> 00:03:14.490
how to change a puppy's DNA
so that he has pink fur.

00:03:14.490 --> 00:03:15.380
And who knows?

00:03:15.380 --> 00:03:18.520
Maybe you'll be the
geneticist to make it happen.

00:03:18.520 --> 00:03:19.750
That's it for today.

00:03:19.750 --> 00:03:20.640
Thanks for watching.

00:03:20.640 --> 00:03:23.390
And I hope to be seeing some
pink puppies one day soon.


A Thermal Inversion Example in Donora

WEBVTT
Kind: captions
Language: en

00:00:00.810 --> 00:00:01.950
- [Instructor] Hey there, friends.

00:00:01.950 --> 00:00:03.960
Today we're gonna learn
about air pollution,

00:00:03.960 --> 00:00:06.360
and to start off, we're going back in time

00:00:06.360 --> 00:00:09.000
to the small town of Donora, Pennsylvania

00:00:09.000 --> 00:00:11.387
in October of 1948.

00:00:11.387 --> 00:00:13.920
(light music)

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Walking into this small industrial town,

00:00:16.500 --> 00:00:19.830
you can immediately sense
that something is wrong.

00:00:19.830 --> 00:00:20.910
It's the middle of the day,

00:00:20.910 --> 00:00:24.120
but there's a thick
yellowish smog everywhere,

00:00:24.120 --> 00:00:27.360
enveloping everything and
even blocking out the sun.

00:00:27.360 --> 00:00:31.410
It's so dark that streetlights
are on during the daytime.

00:00:31.410 --> 00:00:35.820
It stings your eyes and it's
hard, even painful, to breathe.

00:00:35.820 --> 00:00:38.880
What we're experiencing
is the Donora death fog,

00:00:38.880 --> 00:00:41.100
one of the worst air pollution disasters

00:00:41.100 --> 00:00:42.870
in the United States.

00:00:42.870 --> 00:00:45.060
Donora was an industrial town

00:00:45.060 --> 00:00:47.310
full of steel plants and mills,

00:00:47.310 --> 00:00:48.990
which released toxic emissions,

00:00:48.990 --> 00:00:51.990
such as hydrogen fluoride
and sulfur dioxide,

00:00:51.990 --> 00:00:54.840
when processing steel and other metals.

00:00:54.840 --> 00:00:57.480
Normally, these poisonous
gases would disperse

00:00:57.480 --> 00:00:58.950
into the atmosphere,

00:00:58.950 --> 00:01:02.250
but this time, there was
a temperature inversion,

00:01:02.250 --> 00:01:03.930
which caused a blanket of warm air

00:01:03.930 --> 00:01:06.360
to cover a layer of colder
air near the surface

00:01:06.360 --> 00:01:08.463
and right over Donora.

00:01:09.630 --> 00:01:12.570
Consequently, the toxic emissions
were essentially trapped

00:01:12.570 --> 00:01:14.400
under the warm air.

00:01:14.400 --> 00:01:17.550
Over the course of several
days from October 26th

00:01:17.550 --> 00:01:19.350
to October 31st,

00:01:19.350 --> 00:01:22.200
these toxic emissions
had accumulated so much

00:01:22.200 --> 00:01:25.770
that half of the 14,000
people living in Donora

00:01:25.770 --> 00:01:29.490
suffered from respiratory
problems, and 20 people died.

00:01:29.490 --> 00:01:32.310
Relief only came when the
steel mills were shut down

00:01:32.310 --> 00:01:34.683
and a rainstorm alleviated the smog.

00:01:36.240 --> 00:01:38.940
But, following the deadly Donora smog,

00:01:38.940 --> 00:01:41.340
the public began to
relieve just how dangerous

00:01:41.340 --> 00:01:43.770
and life-threatening
air pollution could be,

00:01:43.770 --> 00:01:46.380
and citizens demanded change.

00:01:46.380 --> 00:01:48.840
Donora became a turning
point in US history

00:01:48.840 --> 00:01:51.333
and was the start of
the Clean Air Movement.


Khan Academy Ed Talks with Professor Thomas Guskey, PhD

WEBVTT
Kind: captions
Language: en

00:00:00.330 --> 00:00:03.430
- Hello, and welcome to
EdTalks with Khan Academy.

00:00:03.430 --> 00:00:05.720
I'm Kristen DiCerbo, the
Chief Learning Officer

00:00:05.720 --> 00:00:06.553
at Khan Academy.

00:00:06.553 --> 00:00:08.510
And today I am looking forward to talking

00:00:08.510 --> 00:00:13.510
with Dr. Thomas Guskey about
many things learning related,

00:00:13.720 --> 00:00:17.800
but particularly grades and
grading and reporting systems.

00:00:17.800 --> 00:00:20.060
Before we get started,
I have a couple things

00:00:20.060 --> 00:00:21.030
to remind you of.

00:00:21.030 --> 00:00:23.720
First, Khan Academy is a
non-profit organization,

00:00:23.720 --> 00:00:27.130
and we are able to do our
work, thanks to donations

00:00:27.130 --> 00:00:27.963
from folks like you.

00:00:27.963 --> 00:00:31.660
If you go to khanacademy.org/donate,

00:00:31.660 --> 00:00:33.590
you can help us be able to continue

00:00:33.590 --> 00:00:35.480
to do the work that we do.

00:00:35.480 --> 00:00:37.400
Thank you for doing that.

00:00:37.400 --> 00:00:41.040
Second, I wanna recognize
some of our corporate sponsors

00:00:41.040 --> 00:00:45.130
who have particularly helped
us in the COVID 19 crisis,

00:00:45.130 --> 00:00:48.453
including AT and T,
General Motors and Fastly.

00:00:49.770 --> 00:00:53.740
And finally, if you want
to hear this conversation

00:00:53.740 --> 00:00:56.810
or other conversations
that Sal or I have had

00:00:56.810 --> 00:01:00.650
with folks in the education
industry or outside,

00:01:00.650 --> 00:01:02.640
talking about education related things,

00:01:02.640 --> 00:01:07.360
you can find us on your podcast
app at Homeroom with Sal,

00:01:07.360 --> 00:01:08.293
The podcast.

00:01:09.560 --> 00:01:14.550
So with that, I am glad to
welcome Dr. Thomas Guskey.

00:01:14.550 --> 00:01:17.290
He has written over 25
award-winning books,

00:01:17.290 --> 00:01:19.950
but his latest is Get Set, Go.

00:01:19.950 --> 00:01:23.130
Creating Successful Grading
and Reporting Systems.

00:01:23.130 --> 00:01:25.100
So we'll be talking about that.

00:01:25.100 --> 00:01:29.270
He's also the Professor Emeritus
in the College of Education

00:01:29.270 --> 00:01:30.480
at the University of Kentucky,

00:01:30.480 --> 00:01:32.910
where he served as Department Chair,

00:01:32.910 --> 00:01:35.320
Head of the Educational
Psychology Area Committee

00:01:35.320 --> 00:01:38.080
and President of the Faculty Council.

00:01:38.080 --> 00:01:41.470
He began his career in education
as a middle school teacher

00:01:41.470 --> 00:01:43.990
and earned his doctorate at
the University of Chicago

00:01:43.990 --> 00:01:46.480
under the direction of
Professor Benjamin Bloom,

00:01:46.480 --> 00:01:49.190
and served as an administrator
in Chicago Public Schools

00:01:49.190 --> 00:01:51.730
before becoming the first director

00:01:51.730 --> 00:01:54.540
of the Center for the Improvement
of Teaching and Learning

00:01:54.540 --> 00:01:56.300
at National Research Center.

00:01:56.300 --> 00:01:58.280
So welcome.

00:01:58.280 --> 00:01:59.830
Thank you for joining us today.

00:02:00.670 --> 00:02:01.910
- Thank you, Kristen.

00:02:01.910 --> 00:02:04.923
I've been a long admirer of
the work at the Khan Academy.

00:02:04.923 --> 00:02:06.580
So this is quite an honor for me.

00:02:06.580 --> 00:02:07.940
Thank you.

00:02:07.940 --> 00:02:10.920
- Oh, it is an honor for us to have you.

00:02:10.920 --> 00:02:13.480
I'd like to get started
in talking to folks

00:02:13.480 --> 00:02:15.600
a little bit about their career paths.

00:02:15.600 --> 00:02:20.520
So as you think about how you ended up

00:02:20.520 --> 00:02:22.730
being a professor and researcher,

00:02:22.730 --> 00:02:25.540
studying the things you
study, how did you get there?

00:02:25.540 --> 00:02:27.000
What did you say when you were a kid

00:02:27.000 --> 00:02:28.390
that what you wanted
to be when you grew up

00:02:28.390 --> 00:02:29.833
and how did that evolve?

00:02:31.270 --> 00:02:33.230
- Well, I had a very different career path

00:02:33.230 --> 00:02:34.960
than most people in education.

00:02:34.960 --> 00:02:37.820
My undergraduate major in college

00:02:37.820 --> 00:02:40.220
was actually physics and
electrical engineering,

00:02:41.140 --> 00:02:43.250
but I graduated from college
with my degree in that area

00:02:43.250 --> 00:02:47.617
to discover that I have no
talent in that field at all,

00:02:47.617 --> 00:02:50.560
which was a terrible
disappointment to my father,

00:02:50.560 --> 00:02:52.310
who is an engineer.

00:02:52.310 --> 00:02:56.040
And I was at a party one
night, which I did a lot

00:02:56.040 --> 00:02:59.800
at that time, talking
to a friend who told me

00:02:59.800 --> 00:03:01.210
about a teaching job.

00:03:01.210 --> 00:03:03.090
He had been looking for a teaching job

00:03:03.090 --> 00:03:04.640
and he was at private school,

00:03:04.640 --> 00:03:06.730
a middle school where they needed

00:03:06.730 --> 00:03:08.310
a seventh and eighth grade math teacher

00:03:08.310 --> 00:03:09.850
who would also coach.

00:03:09.850 --> 00:03:12.503
And this just happened to
be the third week of August.

00:03:16.470 --> 00:03:18.670
My father always claimed
that the only reason

00:03:18.670 --> 00:03:20.910
I was hired is I passed a mirror test.

00:03:20.910 --> 00:03:22.540
They put a mirror under my nose, it fogged

00:03:22.540 --> 00:03:23.590
and so I got the job.

00:03:24.650 --> 00:03:26.460
But I started teaching middle school

00:03:26.460 --> 00:03:28.460
and I just fell in love with it.

00:03:28.460 --> 00:03:30.980
I know a lot of people
struggle with that age

00:03:30.980 --> 00:03:33.840
of children, but I just
thought they were terrific.

00:03:33.840 --> 00:03:36.010
So as a continuency of me being hired,

00:03:36.010 --> 00:03:37.340
I had to gain my certification.

00:03:37.340 --> 00:03:39.820
So I began taking education classes

00:03:39.820 --> 00:03:41.543
then I gained my certification.

00:03:42.380 --> 00:03:44.101
And then after several years, decided

00:03:44.101 --> 00:03:46.130
that I really wanted to
go back to graduate school

00:03:46.130 --> 00:03:47.990
to learn how to become a better teacher.

00:03:47.990 --> 00:03:51.150
So I began in Boston and then ended up

00:03:51.150 --> 00:03:54.131
at the University of
Chicago, where my chair,

00:03:54.131 --> 00:03:56.630
my advisor and the chair of my Doctoral

00:03:56.630 --> 00:03:59.340
Dissertation Committee was Benjamin Bloom.

00:03:59.340 --> 00:04:02.470
So it was from that, that
I really became interested

00:04:02.470 --> 00:04:06.970
in the whole area of educational
measurements and valuation,

00:04:06.970 --> 00:04:09.010
learned about the taxonomy, learned about

00:04:09.010 --> 00:04:11.000
instruction and mastery learning

00:04:11.000 --> 00:04:13.270
and then began working with
Chicago Public Schools.

00:04:13.270 --> 00:04:16.790
Did that for several years
and decided after that,

00:04:16.790 --> 00:04:19.370
I really wanted to go into
a university position.

00:04:19.370 --> 00:04:22.990
So, accepted a position here
at the University of Kentucky

00:04:22.990 --> 00:04:25.540
in the department of Educational

00:04:25.540 --> 00:04:27.570
School and Counseling Psychology

00:04:27.570 --> 00:04:30.347
and where I spent most
of my academic career.

00:04:31.980 --> 00:04:33.290
- Fantastic.

00:04:33.290 --> 00:04:37.890
So as I alluded to, you
have written a lot of books

00:04:37.890 --> 00:04:39.023
and articles,

00:04:40.270 --> 00:04:42.650
an impressive library.

00:04:42.650 --> 00:04:47.130
So if you had to pick out some
of the areas that you think

00:04:47.130 --> 00:04:50.960
that you say, hey, I have a
lot to say about this topic.

00:04:50.960 --> 00:04:52.400
What are some of those
areas that you feel like

00:04:52.400 --> 00:04:56.262
are important to, that you
have some important things

00:04:56.262 --> 00:04:58.010
to talk about?

00:04:58.010 --> 00:04:59.000
- Right.

00:04:59.000 --> 00:05:01.220
Well, my very first book was on

00:05:01.220 --> 00:05:03.250
Implementing Mastery Learning,

00:05:03.250 --> 00:05:05.050
and this was an extension
of what I had learned

00:05:05.050 --> 00:05:05.883
with Benjamin Bloom.

00:05:05.883 --> 00:05:08.460
He was the person who
developed the whole concept

00:05:08.460 --> 00:05:09.740
of mastery learning.

00:05:09.740 --> 00:05:12.980
And then when I began working
with Chicago Public Schools,

00:05:12.980 --> 00:05:17.740
we were leading a team of
people there really to implement

00:05:17.740 --> 00:05:21.000
Bloom's ideas into the public
school system in Chicago.

00:05:21.000 --> 00:05:22.920
So that was really my first interest,

00:05:22.920 --> 00:05:26.170
the instructional programs and
the idea of using assessments

00:05:26.170 --> 00:05:27.540
as learning tools.

00:05:27.540 --> 00:05:31.350
But my dissertation was
actually in the area of change,

00:05:31.350 --> 00:05:33.540
and teacher change in particular.

00:05:33.540 --> 00:05:36.880
So that led me into a
profound interest in,

00:05:36.880 --> 00:05:39.910
not only the change process,
but teacher learning

00:05:39.910 --> 00:05:42.080
and professional learning experiences

00:05:42.080 --> 00:05:43.340
for teachers.

00:05:43.340 --> 00:05:46.590
So developed a book,
developed an evaluation model

00:05:46.590 --> 00:05:49.710
for professional learning, looking at

00:05:49.710 --> 00:05:52.430
how we can translate professional
learning for educators

00:05:52.430 --> 00:05:54.873
into learning for students.

00:05:56.240 --> 00:05:58.930
Then that, from that

00:05:58.930 --> 00:06:01.460
got me interested in
sort of using assessments

00:06:01.460 --> 00:06:03.900
as learning tools as we had
through mastery learning.

00:06:03.900 --> 00:06:05.763
That took in the area of assessment.

00:06:06.960 --> 00:06:09.720
And then when we gather that information,

00:06:09.720 --> 00:06:11.920
we have to report it and communicate it

00:06:11.920 --> 00:06:13.170
to parents and to families.

00:06:13.170 --> 00:06:15.260
And that brought me into
the area of grading.

00:06:15.260 --> 00:06:16.670
And that's really what
I've been focusing on

00:06:16.670 --> 00:06:18.370
for the last several
years of grading issues

00:06:18.370 --> 00:06:21.110
and how to really enhance that,
understanding what we know

00:06:21.110 --> 00:06:24.140
about the grading process and
then how we can improve it

00:06:24.140 --> 00:06:27.723
to enhance the communication
between schools and homes.

00:06:29.200 --> 00:06:30.120
- That totally makes sense.

00:06:30.120 --> 00:06:32.190
And I see how things built on each other

00:06:32.190 --> 00:06:34.010
to get to where you are today.

00:06:34.010 --> 00:06:36.137
So before we get to the grading piece,

00:06:36.137 --> 00:06:38.400
I'd love to talk a little bit
more about mastery learning

00:06:38.400 --> 00:06:42.547
since it is, also at Khan
Academy, a foundational piece

00:06:42.547 --> 00:06:45.210
in terms of how we think about it.

00:06:45.210 --> 00:06:47.390
So for those who are
watching, who don't know,

00:06:47.390 --> 00:06:49.990
Dr. Benjamin Bloom is
considered one of the pioneers,

00:06:49.990 --> 00:06:52.696
and then Dr. Guskey has
taken many of those lessons

00:06:52.696 --> 00:06:56.960
and applied them and shared
them with the world as well.

00:06:56.960 --> 00:07:00.100
How do you, when you went
in and were first talking

00:07:00.100 --> 00:07:02.930
to teachers, or even now, when
you're talking to teachers

00:07:02.930 --> 00:07:05.610
who are just learning
about mastery learning,

00:07:05.610 --> 00:07:08.230
how do you introduce
it to them in terms of

00:07:08.230 --> 00:07:10.240
what are the main, the key points

00:07:10.240 --> 00:07:12.023
and the key elements of it?

00:07:13.470 --> 00:07:16.330
- Well, I always introduce
mastery learning to teachers

00:07:16.330 --> 00:07:19.803
as a way to solve the two biggest problems

00:07:19.803 --> 00:07:22.060
that teachers face.

00:07:22.060 --> 00:07:24.989
The first being, the whole
notion of motivation.

00:07:24.989 --> 00:07:28.010
How do I motivate students to learn things

00:07:28.010 --> 00:07:30.500
that they may not consider
important in their lives

00:07:30.500 --> 00:07:33.522
or don't seem as relevant?

00:07:33.522 --> 00:07:37.690
And the idea is that the key to motivation

00:07:37.690 --> 00:07:40.630
and what we know seems
to be the foundation

00:07:40.630 --> 00:07:43.180
of building motivation is success.

00:07:43.180 --> 00:07:45.360
I mean, students persist in activities

00:07:45.360 --> 00:07:48.550
which they're successful
and they avoid with passion,

00:07:48.550 --> 00:07:50.300
those things in which
they're not successful

00:07:50.300 --> 00:07:52.410
or believe they cannot be.

00:07:52.410 --> 00:07:55.583
I mean, I always use the
example of video games.

00:07:56.420 --> 00:07:59.208
I mean, the biggest selling
video game of all time

00:07:59.208 --> 00:08:01.060
is Pac-Man.

00:08:01.060 --> 00:08:03.740
I mean, nothing has ever outsold Pac-Man.

00:08:03.740 --> 00:08:08.740
It's like a 17, $18 billion industry.

00:08:08.980 --> 00:08:13.742
And the purpose of Pac-Man is
basically to gobble up dots.

00:08:13.742 --> 00:08:16.340
Now, what makes that interesting?

00:08:16.340 --> 00:08:18.190
What makes that relevant
to anybody's life?

00:08:18.190 --> 00:08:19.360
Nothing.

00:08:19.360 --> 00:08:21.440
And as people say, well,
maybe it's behavioral.

00:08:21.440 --> 00:08:23.700
Maybe it's based on the rewards you get,

00:08:23.700 --> 00:08:25.240
but that's not true.

00:08:25.240 --> 00:08:27.130
I mean, in Pac-Man, what do you get

00:08:27.130 --> 00:08:29.060
if you go up all the dots?

00:08:29.060 --> 00:08:31.032
You get more dots.

00:08:31.032 --> 00:08:32.260
That's a great world.

00:08:32.260 --> 00:08:34.570
I mean, that's like saying,
look, do these 10 problems,

00:08:34.570 --> 00:08:36.213
I'll give you 10 more to do.

00:08:37.460 --> 00:08:40.080
But what Pac-Man did is it showed people

00:08:40.080 --> 00:08:42.350
that they could be successful at this task

00:08:42.350 --> 00:08:44.730
and capitalized in that success.

00:08:44.730 --> 00:08:47.498
Every time they'd improve,
make the challenge

00:08:47.498 --> 00:08:50.210
a little bit greater and
show you could succeed it.

00:08:50.210 --> 00:08:53.400
So that's the same that what
we have to carry through

00:08:53.400 --> 00:08:55.060
in education, we have to find ways

00:08:55.060 --> 00:08:56.667
we can help students succeed

00:08:56.667 --> 00:09:00.330
and see that they can be
successful as learners.

00:09:00.330 --> 00:09:02.630
But that ties to the second major problem.

00:09:02.630 --> 00:09:05.885
And that problem is the
diversity the teachers face

00:09:05.885 --> 00:09:07.803
in group based instruction.

00:09:08.750 --> 00:09:11.060
I mean, it would be great to think about

00:09:11.060 --> 00:09:12.920
individualized instruction of programs,

00:09:12.920 --> 00:09:16.430
but we'll never be able to get
to a situation in our country

00:09:16.430 --> 00:09:18.910
where we have a class size of one.

00:09:18.910 --> 00:09:20.330
It's always going to be group based.

00:09:20.330 --> 00:09:22.440
And because of that
diversity in, there is,

00:09:22.440 --> 00:09:24.680
no matter what approach a teacher chooses,

00:09:24.680 --> 00:09:27.280
it works for some, it
doesn't work for others.

00:09:27.280 --> 00:09:29.980
And so teachers have to
find a way to provide

00:09:29.980 --> 00:09:33.780
for the diversity of needs
in a group based environment.

00:09:33.780 --> 00:09:37.580
And those are exactly the
two conditions under which

00:09:37.580 --> 00:09:41.510
Benjamin Bloom developed the
ideas of mastery learning.

00:09:41.510 --> 00:09:43.990
What could we do in a
group based environment

00:09:43.990 --> 00:09:47.330
to help more students learn
excellently the things we have

00:09:47.330 --> 00:09:49.690
to teach and gain the
many positive benefits

00:09:49.690 --> 00:09:51.470
of that success.

00:09:51.470 --> 00:09:54.830
So I think, it's approached
as a way of solving

00:09:54.830 --> 00:09:57.680
those two critical
problems that teachers face

00:09:57.680 --> 00:10:00.550
and giving them a solution to an issue

00:10:00.550 --> 00:10:02.400
with which they've always been familiar

00:10:02.400 --> 00:10:04.150
and probably have always struggled.

00:10:05.970 --> 00:10:09.110
- I continue to hear those as probably

00:10:09.110 --> 00:10:12.680
the two biggest questions
that we get from teachers.

00:10:12.680 --> 00:10:15.300
How do I help differentiate
for all the different levels

00:10:15.300 --> 00:10:18.380
I have in my class and how
do I motivate students?

00:10:18.380 --> 00:10:22.100
So that absolutely makes
sense in terms of the problems

00:10:22.100 --> 00:10:26.410
to be solved and where those
were and that it continues to,

00:10:26.410 --> 00:10:29.780
over years, that it continues
to be some of the issues

00:10:29.780 --> 00:10:31.530
that teachers face.

00:10:31.530 --> 00:10:33.560
When you were first starting,

00:10:33.560 --> 00:10:36.220
so, don't wanna make you feel old,

00:10:36.220 --> 00:10:38.377
but you've been doing this for a while.

00:10:38.377 --> 00:10:39.343
- Yes, that's true.

00:10:40.335 --> 00:10:43.830
- What were some of the conditions then

00:10:43.830 --> 00:10:46.718
and how do you see things
either changing or the same

00:10:46.718 --> 00:10:49.563
in the world, in the
school environments now?

00:10:50.790 --> 00:10:53.860
- Well, it certainly has changed a lot.

00:10:53.860 --> 00:10:58.770
I mean, I have the advantage
of, now with social media,

00:10:58.770 --> 00:11:01.213
many of my former students,
middle school students

00:11:01.213 --> 00:11:04.100
are now my friends on
Facebook and they write to me

00:11:04.100 --> 00:11:06.800
about their lives and what's going on.

00:11:06.800 --> 00:11:11.010
And the positive ways in
which education has changed,

00:11:11.010 --> 00:11:12.990
especially through the use of technology,

00:11:12.990 --> 00:11:16.670
it's just remarkable the things
that we're able to do today,

00:11:16.670 --> 00:11:19.900
but the social conditions
are really different.

00:11:19.900 --> 00:11:22.370
But teachers are, I think,
very sensitive to that

00:11:22.370 --> 00:11:25.890
and aware of the things that
our students bring to school

00:11:25.890 --> 00:11:29.660
and how we have to help them
use school as an environment

00:11:29.660 --> 00:11:31.600
in which they can feel safe.

00:11:31.600 --> 00:11:33.540
And in the safety of that environment,

00:11:33.540 --> 00:11:35.497
really become successful in learning.

00:11:35.497 --> 00:11:38.850
And I think that's where Benjamin Bloom,

00:11:38.850 --> 00:11:40.980
where they made a remarkable difference.

00:11:40.980 --> 00:11:45.430
And he said that, learning in
any subject area is infinite,

00:11:45.430 --> 00:11:47.430
and there's no limit to what you can learn

00:11:47.430 --> 00:11:50.823
in any subject area at all,
but a curriculum is finite.

00:11:51.830 --> 00:11:54.470
And when we identify a
curriculum, what we do,

00:11:54.470 --> 00:11:56.510
is we take that entire domain of learning

00:11:56.510 --> 00:11:59.185
in any academic discipline
or subject area,

00:11:59.185 --> 00:12:02.090
and we specify these
are the things we think

00:12:02.090 --> 00:12:04.730
all students should be
able to learn really well.

00:12:04.730 --> 00:12:07.500
Then, once we do that,
our job as educators

00:12:07.500 --> 00:12:09.870
becomes doing everything within our power

00:12:09.870 --> 00:12:12.450
to ensure that all students, not just some

00:12:12.450 --> 00:12:15.740
but really all, learn that excellently.

00:12:15.740 --> 00:12:19.030
And so where Bloom really
differed in his orientation

00:12:19.030 --> 00:12:21.370
compared to others, is that at that time

00:12:21.370 --> 00:12:23.957
when he developed these
ideas and the late 1960s

00:12:23.957 --> 00:12:27.250
and early 1970s, people were talking about

00:12:27.250 --> 00:12:29.670
equality of educational opportunity

00:12:29.670 --> 00:12:31.670
and doing things to
make sure that all kids

00:12:31.670 --> 00:12:35.080
had similar opportunities
when they entered school.

00:12:35.080 --> 00:12:38.730
And Bloom saw that as just
an impossible sort of thing

00:12:38.730 --> 00:12:42.330
that no matter what we did, our
society was going to dictate

00:12:42.330 --> 00:12:46.250
that kids would come to
school dramatically different.

00:12:46.250 --> 00:12:49.440
And what we needed to do was
not concern ourselves so much

00:12:49.440 --> 00:12:52.000
with the quality of
opportunity, but equity

00:12:52.000 --> 00:12:55.070
in terms of the outcomes
and what could we do

00:12:55.070 --> 00:12:58.480
to ensure that all students,
regardless of the conditions

00:12:58.480 --> 00:13:01.020
they brought with them to school,

00:13:01.020 --> 00:13:02.700
were able to learn excellently.

00:13:02.700 --> 00:13:05.460
And so they would master that curriculum,

00:13:05.460 --> 00:13:09.340
gain the benefits of success
and be able to carry that over

00:13:09.340 --> 00:13:11.540
to what they then would
have in their lives.

00:13:13.460 --> 00:13:16.160
- That absolutely makes sense
as we think about equity

00:13:17.099 --> 00:13:20.340
and equality and those
are certainly themes

00:13:20.340 --> 00:13:23.233
that we're seeing playing
out in schools today,

00:13:24.530 --> 00:13:28.113
as salient as they were then,
I think they continue to be.

00:13:29.060 --> 00:13:32.900
As we think about that equality,
I know one of the struggles

00:13:32.900 --> 00:13:36.330
that teachers have in
classrooms is thinking about,

00:13:36.330 --> 00:13:39.350
when students have those
gaps that need to be filled

00:13:39.350 --> 00:13:41.280
in their foundational knowledge.

00:13:41.280 --> 00:13:44.310
And they also have the pressure,
teachers have the pressure

00:13:44.310 --> 00:13:48.220
of meeting those grade level standards.

00:13:48.220 --> 00:13:51.620
And I have to cover all
this material this year.

00:13:51.620 --> 00:13:54.453
How do you help teachers
think about that tension?

00:13:55.480 --> 00:13:58.440
- Well, I think one of the
things that I try to emphasize

00:13:58.440 --> 00:14:03.280
in my work is that we're never
going to be able to overcome

00:14:03.280 --> 00:14:07.300
all those gaps that students
might have when they come in.

00:14:07.300 --> 00:14:11.070
And I think it's really a
folly to try to look back

00:14:11.070 --> 00:14:13.290
and think about all that
they might have missed.

00:14:13.290 --> 00:14:16.160
What's much more
productive is to look ahead

00:14:16.160 --> 00:14:18.660
and with each learning
unit, try to identify

00:14:18.660 --> 00:14:21.810
the maybe two or three things
that students need to have

00:14:21.810 --> 00:14:23.793
in order to succeed in this next unit.

00:14:24.870 --> 00:14:26.730
They don't, you're not going to remedy

00:14:26.730 --> 00:14:28.710
like three years of learning deficits

00:14:28.710 --> 00:14:31.320
in the first six months of school.

00:14:31.320 --> 00:14:32.710
But what you can do is look ahead

00:14:32.710 --> 00:14:35.180
to that first instructional unit and say,

00:14:35.180 --> 00:14:38.000
in order for the students
to really be successful,

00:14:38.000 --> 00:14:40.062
to start at a level playing field,

00:14:40.062 --> 00:14:42.980
here are the two or three things
they really need to learn.

00:14:42.980 --> 00:14:44.540
These are the things
they really need to have.

00:14:44.540 --> 00:14:47.860
This would establish a baseline for them.

00:14:47.860 --> 00:14:49.970
This would be the prerequisite for it.

00:14:49.970 --> 00:14:52.640
And then what we do is we
teach those two or three things

00:14:52.640 --> 00:14:55.690
to a level of mastery, and then,

00:14:55.690 --> 00:14:57.950
everybody's starting on
that level playing field.

00:14:57.950 --> 00:14:59.200
And when you get everybody starting

00:14:59.200 --> 00:15:02.100
in a level playing field,
then you can guarantee

00:15:02.100 --> 00:15:04.160
success in that first unit.

00:15:04.160 --> 00:15:05.870
And typically, success in the first unit

00:15:05.870 --> 00:15:08.360
is prerequisite for
success in the second unit.

00:15:08.360 --> 00:15:10.150
Although in the second
unit, you might again,

00:15:10.150 --> 00:15:12.640
look ahead and identify
if there were any things

00:15:12.640 --> 00:15:15.640
that I would expect students
to know and be able to do

00:15:15.640 --> 00:15:17.170
to really succeed in this one.

00:15:17.170 --> 00:15:19.280
And it could take a little bit of time.

00:15:19.280 --> 00:15:23.060
And what we find is that,
if teachers can do that,

00:15:23.060 --> 00:15:25.729
to look ahead, rather than looking back

00:15:25.729 --> 00:15:27.440
and take a little bit of time

00:15:27.440 --> 00:15:29.220
at the beginning of
every instructional unit

00:15:29.220 --> 00:15:32.861
to really emphasize those prerequisites.

00:15:32.861 --> 00:15:36.570
Not only does it mean their
instruction can increase

00:15:36.570 --> 00:15:39.860
in its pace later, but it gives kids

00:15:39.860 --> 00:15:43.500
the necessary preconditions for success.

00:15:43.500 --> 00:15:46.780
So it's the idea that
instead of remedying promise

00:15:46.780 --> 00:15:49.430
in the past, we look
ahead to what kids need

00:15:49.430 --> 00:15:52.410
and then provide that in a
really structured environment

00:15:52.410 --> 00:15:54.860
and then be able to build
on that as we go along.

00:15:55.736 --> 00:15:56.569
- All right.

00:15:56.569 --> 00:15:59.520
I rarely, I don't like
to use these (indistinct)

00:15:59.520 --> 00:16:02.360
Khan Academy things, but I
just wanted to run this by you.

00:16:02.360 --> 00:16:06.420
So we have what we call get
ready for grade level courses.

00:16:06.420 --> 00:16:08.210
Which essentially your sixth,

00:16:08.210 --> 00:16:09.410
you have your sixth grade course.

00:16:09.410 --> 00:16:13.040
Say you have a unit on decimals,
the get ready for course,

00:16:13.040 --> 00:16:15.490
has the get ready for decimals unit,

00:16:15.490 --> 00:16:18.070
which has those two or three prerequisites

00:16:18.070 --> 00:16:19.620
that you need to do decimals.

00:16:19.620 --> 00:16:22.710
And that we want teachers
to use in that way

00:16:22.710 --> 00:16:24.390
and leaving them in.

00:16:24.390 --> 00:16:27.830
So we have read what you're suggesting

00:16:27.830 --> 00:16:31.190
and taken that in and built on that.

00:16:31.190 --> 00:16:32.333
So--

00:16:32.333 --> 00:16:33.166
- Kristen,

00:16:33.166 --> 00:16:34.720
it's one of the reasons
I'm such an admirer

00:16:34.720 --> 00:16:36.450
of the Khan Academy work because

00:16:36.450 --> 00:16:39.440
it's so thoughtfully structured and you do

00:16:39.440 --> 00:16:43.380
such a very good job of
building on exactly those ideas.

00:16:43.380 --> 00:16:46.520
Those get ready things are
just absolutely on target

00:16:46.520 --> 00:16:49.320
and just precisely what
we would need to do

00:16:49.320 --> 00:16:52.299
to ensure that higher level
success for our students.

00:16:52.299 --> 00:16:53.333
- Yeah.

00:16:54.920 --> 00:16:57.330
Always excited to hear folks saying,

00:16:57.330 --> 00:16:59.570
talking about the things and I can say,

00:16:59.570 --> 00:17:01.260
yes, we're trying to do that.

00:17:02.367 --> 00:17:04.567
- It was so thoughtful in design.

00:17:06.380 --> 00:17:07.213
- Absolutely.

00:17:07.213 --> 00:17:09.520
Let's move into talking a
little bit about grading

00:17:09.520 --> 00:17:12.990
and where you've been writing
and thinking about grades

00:17:12.990 --> 00:17:14.150
and grading.

00:17:14.150 --> 00:17:19.020
What would you say are the big factors

00:17:19.020 --> 00:17:21.283
in effective and accurate grading?

00:17:22.539 --> 00:17:27.407
- Well, we actually did a
very large project in 2016

00:17:28.270 --> 00:17:31.570
where the American Educational
Research Association

00:17:31.570 --> 00:17:34.600
was celebrating its
100th year anniversary.

00:17:34.600 --> 00:17:36.260
And as a part of that celebration,

00:17:36.260 --> 00:17:39.900
they put out a call to the field
to researchers and scholars

00:17:39.900 --> 00:17:43.780
to ask if they would take on the challenge

00:17:43.780 --> 00:17:47.410
of really reviewing all the
research being conducted

00:17:47.410 --> 00:17:48.880
in these different areas of education

00:17:48.880 --> 00:17:51.210
over that 100 year period.

00:17:51.210 --> 00:17:53.350
So together with my
friend, Susan Brookhart,

00:17:53.350 --> 00:17:58.350
we put together an amazing team
of really important scholars

00:17:58.690 --> 00:18:00.732
that had looked into the grading area

00:18:00.732 --> 00:18:02.750
and asked them to take on that challenge.

00:18:02.750 --> 00:18:04.018
And we developed our paper,

00:18:04.018 --> 00:18:07.100
which was published in Review
of Education and Research,

00:18:07.100 --> 00:18:10.760
and then actually extended that
into the practical vocations

00:18:10.760 --> 00:18:13.410
of that work and a book we did for ASCD

00:18:13.410 --> 00:18:15.430
called What We Know about Grading,

00:18:15.430 --> 00:18:19.130
but what surprised us most
in getting into this area

00:18:19.130 --> 00:18:23.710
was to discover how much we
know, how long we've known it

00:18:23.710 --> 00:18:26.610
and how little of that has found its way

00:18:26.610 --> 00:18:27.988
into practice today.

00:18:27.988 --> 00:18:30.080
I mean, I've grown absolutely convinced

00:18:30.080 --> 00:18:32.680
there's just not another
area in all of education

00:18:32.680 --> 00:18:35.330
where the gap between our
knowledge base and our practice

00:18:35.330 --> 00:18:38.090
is greater than in the area of grading.

00:18:38.090 --> 00:18:40.280
And so we've got an
amazing knowledge base.

00:18:40.280 --> 00:18:43.220
It gives us guidance
on how to do this well.

00:18:43.220 --> 00:18:46.080
It's just that we are
so bombed by tradition

00:18:46.080 --> 00:18:49.170
that it's very difficult to
challenge those traditions

00:18:49.170 --> 00:18:51.070
and implement change in this area.

00:18:51.070 --> 00:18:54.000
That is so sort of conformed

00:18:54.000 --> 00:18:57.723
in our practices in the past
that it's hard to break.

00:18:59.860 --> 00:19:01.420
- So what are some of those things

00:19:01.420 --> 00:19:04.180
that you would do differently
or that we need to change

00:19:04.180 --> 00:19:05.980
in how we're thinking about grading?

00:19:06.860 --> 00:19:08.630
- Well, there are three
things in particular

00:19:08.630 --> 00:19:09.540
that we need to do.

00:19:09.540 --> 00:19:13.550
Number one, we really need
to do have educators sit down

00:19:13.550 --> 00:19:15.500
and establish the purpose.

00:19:15.500 --> 00:19:17.910
Why are we doing this in the first place?

00:19:17.910 --> 00:19:19.520
Researchers have asked that question

00:19:19.520 --> 00:19:22.200
in studies that they've
conducted and find that

00:19:22.200 --> 00:19:23.460
we are all over the place

00:19:23.460 --> 00:19:25.570
and why are we're doing
it in the first place?

00:19:25.570 --> 00:19:29.040
And that means that there's
great diversity then,

00:19:29.040 --> 00:19:30.510
in policies and practices,

00:19:30.510 --> 00:19:33.080
because teachers believe they're

00:19:33.080 --> 00:19:35.150
doing it for different reasons.

00:19:35.150 --> 00:19:38.650
And then when we study parents
or students and ask them

00:19:38.650 --> 00:19:41.660
their greatest concerns
about fairness and grading,

00:19:41.660 --> 00:19:44.630
the number one problem
that they always identify

00:19:44.630 --> 00:19:49.033
is the inconsistency among
teachers in the same school.

00:19:50.170 --> 00:19:52.180
The only way to establish that consistency

00:19:52.180 --> 00:19:54.870
is to start by defining your purpose.

00:19:54.870 --> 00:19:57.820
And so it means that school
leaders need to sit down

00:19:57.820 --> 00:20:01.890
with their faculty and really
hash out these differences

00:20:01.890 --> 00:20:04.890
and come up with a
consistent, purpose statement

00:20:04.890 --> 00:20:07.860
upon which we can all have consensus.

00:20:07.860 --> 00:20:09.870
And then we look at our
policies and practices

00:20:09.870 --> 00:20:11.800
and see if it aligns with that purpose.

00:20:11.800 --> 00:20:13.220
Then second,

00:20:13.220 --> 00:20:16.970
we need to recognize that we combine

00:20:16.970 --> 00:20:20.030
all these diverse elements
when we grade students.

00:20:20.030 --> 00:20:22.390
We've found that there
are three different types

00:20:22.390 --> 00:20:25.590
of criteria that teachers
use in grading students.

00:20:25.590 --> 00:20:30.590
So we've labeled those,
product, process and progress.

00:20:30.741 --> 00:20:34.300
Product criteria are sort
of common in administrations

00:20:34.300 --> 00:20:35.133
of learning.

00:20:35.133 --> 00:20:36.540
You don't worry about how they get there.

00:20:36.540 --> 00:20:38.160
You worry about what they've learned

00:20:38.160 --> 00:20:39.970
and what they're able to do.

00:20:39.970 --> 00:20:42.590
Process criteria are actually behaviors

00:20:42.590 --> 00:20:44.370
that enable learning.

00:20:44.370 --> 00:20:45.840
And so if you count homework,

00:20:45.840 --> 00:20:47.490
you're grading in terms of process.

00:20:47.490 --> 00:20:49.391
If you count class participation,

00:20:49.391 --> 00:20:51.360
if you count formative assessments,

00:20:51.360 --> 00:20:53.630
all of those are process criteria.

00:20:53.630 --> 00:20:55.320
And finally, we have progress.

00:20:55.320 --> 00:20:58.630
With progress, you don't worry
so much about where they are,

00:20:58.630 --> 00:21:01.940
but how far they've come, how
much improvement they've made.

00:21:01.940 --> 00:21:04.100
So it would be possible for a student

00:21:04.100 --> 00:21:05.240
to make excellent progress,

00:21:05.240 --> 00:21:08.640
but still be achieving below grade level.

00:21:08.640 --> 00:21:11.358
Now we know that all three
of those are important.

00:21:11.358 --> 00:21:13.760
What gets us into trouble is when teachers

00:21:13.760 --> 00:21:16.570
combine all three into a single grade,

00:21:16.570 --> 00:21:19.830
because then, the grade is
impossible to interpret.

00:21:19.830 --> 00:21:20.940
I mean, she got a high grade.

00:21:20.940 --> 00:21:21.822
What does that mean?

00:21:21.822 --> 00:21:24.290
Does it mean she learned everything well?

00:21:24.290 --> 00:21:25.440
Maybe.

00:21:25.440 --> 00:21:27.490
Maybe it just means she tried really hard.

00:21:27.490 --> 00:21:29.350
Or if you know where she started,

00:21:29.350 --> 00:21:31.730
she's come so far during this time.

00:21:31.730 --> 00:21:35.030
And so the second thing,
is we need to move away

00:21:35.030 --> 00:21:39.060
from a single grade to multiple grades.

00:21:39.060 --> 00:21:40.860
We need to give students multiple grades

00:21:40.860 --> 00:21:42.760
to represent these
different types of criteria.

00:21:42.760 --> 00:21:44.630
So they'll get an achievement grade

00:21:44.630 --> 00:21:46.550
and we can still use that for GPA

00:21:46.550 --> 00:21:48.710
and all the kind of
things that are important,

00:21:48.710 --> 00:21:51.020
but maybe give a separate
grade for homework

00:21:51.020 --> 00:21:53.650
or a separate grade for
class participation.

00:21:53.650 --> 00:21:54.483
Now,

00:21:55.580 --> 00:21:57.940
although that sounds
like a lot of extra work,

00:21:57.940 --> 00:22:00.000
what's amazing is if
you go to other places

00:22:00.000 --> 00:22:03.050
around the world, if you
go to Northern Europe

00:22:03.050 --> 00:22:07.179
and the Scandinavian countries,
if you go to places in Asia,

00:22:07.179 --> 00:22:09.940
if you go to schools in Canada,

00:22:09.940 --> 00:22:11.440
they have done it for decades.

00:22:12.300 --> 00:22:14.860
We are one of the few
developed nations in the world

00:22:14.860 --> 00:22:16.370
that persists in this idea of combining

00:22:16.370 --> 00:22:18.660
everything into a single grade.

00:22:18.660 --> 00:22:21.850
And when I ask the Canadians,
with whom I worked about

00:22:21.850 --> 00:22:24.540
the extra work, they said,
actually, it's easier

00:22:24.540 --> 00:22:27.240
than what you silly
people do in the states.

00:22:27.240 --> 00:22:29.570
I mean, we collect the
same information as you.

00:22:29.570 --> 00:22:32.120
We just don't worry about
combining it at the end.

00:22:32.120 --> 00:22:35.280
So all those arguments you
have about weighting things,

00:22:35.280 --> 00:22:37.050
we don't do it, we keep it separate.

00:22:37.050 --> 00:22:40.510
The teachers love it because
they find it's so much easier

00:22:40.510 --> 00:22:42.820
to explain students'
performance in the school

00:22:42.820 --> 00:22:45.250
when these things are separate,

00:22:45.250 --> 00:22:47.510
they find that kids pay
a lot more attention

00:22:47.510 --> 00:22:50.130
to things like homework
and class participation

00:22:50.130 --> 00:22:53.460
when it's not disguised
in an overall sort of

00:22:53.460 --> 00:22:56.430
conglomerate grade, the
parents like it, 'cause again,

00:22:56.430 --> 00:22:58.610
provided that promotes their kids.

00:22:58.610 --> 00:23:00.813
College and universities
love it because all grades

00:23:00.813 --> 00:23:03.400
are carried over to the transcript.

00:23:03.400 --> 00:23:07.850
And so you get a bunch more
interesting, much more,

00:23:07.850 --> 00:23:11.290
sort of complete picture of a
stats performance in school.

00:23:11.290 --> 00:23:14.860
And third, what we wanna
do is, we need to get down

00:23:14.860 --> 00:23:18.160
to fewer grade categories,
we need in particular,

00:23:18.160 --> 00:23:20.140
get rid of the percentage grade system.

00:23:20.140 --> 00:23:24.050
It's just impossible for us to
get any consistency in grades

00:23:24.050 --> 00:23:27.453
with 101 discrete categories
of student performance.

00:23:28.310 --> 00:23:30.170
Just doesn't make sense.

00:23:30.170 --> 00:23:31.240
And I know a lot of people think,

00:23:31.240 --> 00:23:34.240
well, but it's giving you
a fine discrimination,

00:23:34.240 --> 00:23:36.380
allows us to finely discriminate

00:23:36.380 --> 00:23:37.840
among students' performance.

00:23:37.840 --> 00:23:40.210
But what we have to
understand is that's only true

00:23:40.210 --> 00:23:42.400
when you have direct measures.

00:23:42.400 --> 00:23:45.090
Direct measures are things
like height or weight,

00:23:45.090 --> 00:23:46.940
where if I have a fine tuned scale,

00:23:46.940 --> 00:23:48.940
then I can measure it more precisely.

00:23:48.940 --> 00:23:52.480
But most of what we measure
in school is indirect.

00:23:52.480 --> 00:23:55.380
And that means we give
kids a series of tasks

00:23:55.380 --> 00:23:57.810
and a series of questions to answer.

00:23:57.810 --> 00:24:01.010
And then we infer, from their performance,

00:24:01.010 --> 00:24:03.950
what level of achievement that represents.

00:24:03.950 --> 00:24:05.080
So we move for indirect.

00:24:05.080 --> 00:24:07.010
And when you move to indirect measures,

00:24:07.010 --> 00:24:10.020
then 101 levels, just impossible to do

00:24:10.020 --> 00:24:12.300
in any meaningful way.

00:24:12.300 --> 00:24:14.060
The average amount of
variation among teachers

00:24:14.060 --> 00:24:16.476
with a percentage grade system
looking exactly the same

00:24:16.476 --> 00:24:20.043
(indistinct) of evidence, is
10 to 15 percentage points.

00:24:20.043 --> 00:24:21.598
No, and it's huge.

00:24:21.598 --> 00:24:23.520
And so--
- That's huge, yeah.

00:24:23.520 --> 00:24:24.353
- Yeah.

00:24:24.353 --> 00:24:26.690
To get consistency, we
need to get down to a more,

00:24:26.690 --> 00:24:29.390
much more reasonable number of categories

00:24:29.390 --> 00:24:31.010
of student performance so we can defend

00:24:31.010 --> 00:24:33.170
and we can do much more consistency.

00:24:33.170 --> 00:24:35.680
So those three things,
be clear about purpose,

00:24:35.680 --> 00:24:38.763
multiple grades, fewer
categories of performance.

00:24:40.130 --> 00:24:40.963
- That makes sense.

00:24:40.963 --> 00:24:44.260
We have a question from Jorge
Leo on Facebook that says,

00:24:44.260 --> 00:24:46.700
what are the assessment implications

00:24:46.700 --> 00:24:48.075
of this kind of grading?

00:24:48.075 --> 00:24:51.210
What does that reveal and
what we should be doing

00:24:51.210 --> 00:24:53.325
in terms of assessment practices?

00:24:53.325 --> 00:24:56.430
- Well, it does imply
that if you're going to

00:24:57.950 --> 00:25:01.160
actually evaluate or judge
students' performance

00:25:01.160 --> 00:25:03.820
in these non-academic areas,

00:25:03.820 --> 00:25:06.520
that we have to have a clear
rubric of what that means.

00:25:06.520 --> 00:25:09.510
If you choose collaboration,
is one thing you want students

00:25:09.510 --> 00:25:12.850
to be able to develop, then number one,

00:25:12.850 --> 00:25:15.000
you're going to have
to deal with the parent

00:25:15.000 --> 00:25:17.540
who comes to you and says,
you gave my kid at two

00:25:17.540 --> 00:25:20.020
in collaboration, how can he get a four?

00:25:20.020 --> 00:25:21.270
And we need to be able to say,

00:25:21.270 --> 00:25:24.240
this is what level four
collaboration looks like.

00:25:24.240 --> 00:25:26.570
This is what an example of
level four collaboration

00:25:26.570 --> 00:25:30.330
would be, here is how I would
distinguish between those.

00:25:30.330 --> 00:25:33.350
And when many schools are
doing, is after the teachers

00:25:33.350 --> 00:25:36.950
determine among these sort
of non-academic factors

00:25:36.950 --> 00:25:41.680
they're going to consider,
that they turn the job

00:25:41.680 --> 00:25:44.390
of developing rubrics
over to the students.

00:25:44.390 --> 00:25:47.580
And the students actually
develop these rubrics

00:25:47.580 --> 00:25:49.640
where they say, okay, how
could I show the teachers

00:25:49.640 --> 00:25:51.940
that I can be collaborative?

00:25:51.940 --> 00:25:54.060
How can I show the teacher
that I'm responsible?

00:25:54.060 --> 00:25:57.570
How can I show the teacher
that I accept responsibility

00:25:57.570 --> 00:26:01.720
and can be acting in a responsible way?

00:26:01.720 --> 00:26:06.020
And what we find is that they
are tremendously talented

00:26:06.020 --> 00:26:07.490
in being able to define that,

00:26:07.490 --> 00:26:09.250
especially when the teachers
give them some guidance

00:26:09.250 --> 00:26:10.590
and direction there.

00:26:10.590 --> 00:26:12.610
And so you make a really good point.

00:26:12.610 --> 00:26:15.930
We need to be able to
specify that clearly,

00:26:15.930 --> 00:26:18.358
it's not something we can
just make some judgment of

00:26:18.358 --> 00:26:21.180
and have it be out there, we
need to be able to do that.

00:26:21.180 --> 00:26:23.240
Now, when it comes to
these process elements,

00:26:23.240 --> 00:26:25.150
there are three different times.

00:26:25.150 --> 00:26:27.310
There is, first of all,

00:26:27.310 --> 00:26:28.800
what we call these learning enablers.

00:26:28.800 --> 00:26:30.200
That's what I described earlier.

00:26:30.200 --> 00:26:32.993
And that would include
things like homework,

00:26:34.000 --> 00:26:38.140
class participation, effort,
formative assessments in life.

00:26:38.140 --> 00:26:40.670
A third area, or a second
area is what we call

00:26:40.670 --> 00:26:43.780
the social and emotional learning
skills that would include

00:26:43.780 --> 00:26:47.963
things like grit,
perseverance, growth mindset,

00:26:49.496 --> 00:26:51.510
all these kind of things that we associate

00:26:51.510 --> 00:26:53.050
with social-emotional learning.

00:26:53.050 --> 00:26:54.050
And here's the third area.

00:26:54.050 --> 00:26:56.460
The third area is just compliance.

00:26:56.460 --> 00:26:59.970
The compliance is, did you do
what I told you you had to do?

00:26:59.970 --> 00:27:02.760
Now, again, we don't know at this time

00:27:02.760 --> 00:27:05.890
among those, what's most
important for students.

00:27:05.890 --> 00:27:07.350
We're just starting to study that now.

00:27:07.350 --> 00:27:08.640
A new center has been established

00:27:08.640 --> 00:27:11.000
at the University of
Chicago to look into this,

00:27:11.000 --> 00:27:12.850
Harvard University has
established a center

00:27:12.850 --> 00:27:15.180
to look into social-emotional
learning skills.

00:27:15.180 --> 00:27:18.000
We do know this, you can't do it all.

00:27:18.000 --> 00:27:20.970
And so that means the faculty
again, has to sit down

00:27:20.970 --> 00:27:22.980
and decide their priorities.

00:27:22.980 --> 00:27:26.630
And among those things, what
they consider most important,

00:27:26.630 --> 00:27:29.530
then you have to develop
meaningful rubrics for it.

00:27:29.530 --> 00:27:31.460
You have to be able to
communicate that rubric

00:27:31.460 --> 00:27:34.560
to all the stakeholders, parents
and students in particular,

00:27:34.560 --> 00:27:37.150
and then, make sure that you include that

00:27:37.150 --> 00:27:39.060
on your report card in a meaningful way.

00:27:39.060 --> 00:27:40.283
And in your purpose statement

00:27:40.283 --> 00:27:44.937
that you're going to report
those things separately.

00:27:44.937 --> 00:27:47.400
- That absolutely makes sense.

00:27:47.400 --> 00:27:49.710
In terms of thinking
about all of the pieces

00:27:49.710 --> 00:27:52.000
that need to fall into place.

00:27:52.000 --> 00:27:54.400
We are already almost at time.

00:27:54.400 --> 00:27:59.350
I wanna do, make the circle
back to mastery learning.

00:27:59.350 --> 00:28:01.890
I know you've also have a book,

00:28:01.890 --> 00:28:05.830
Implementing Mastery Learning
and what that looks like.

00:28:05.830 --> 00:28:09.150
How do these grading
practices and mastery learning

00:28:09.150 --> 00:28:14.130
all come together to
make that implementation

00:28:14.130 --> 00:28:17.603
of mastery learning happen
through these grading practices?

00:28:18.640 --> 00:28:20.030
- Well, it's certainly true.

00:28:20.030 --> 00:28:22.550
This new version of our book

00:28:22.550 --> 00:28:23.934
on Implementing Mastery Learning

00:28:23.934 --> 00:28:26.940
is actually a third edition.

00:28:26.940 --> 00:28:29.460
It was my very first
book and Benjamin Bloom

00:28:29.460 --> 00:28:32.940
actually wrote the initial
foreword to the book.

00:28:32.940 --> 00:28:37.310
And so we're taking those
ideas and adapting them now

00:28:37.310 --> 00:28:42.130
to a 21st century format.

00:28:42.130 --> 00:28:44.040
And one of the things we
talk about in the book

00:28:44.040 --> 00:28:46.630
is the use of technology
within mastery learning,

00:28:46.630 --> 00:28:50.340
especially as a sort
of instructional vice,

00:28:50.340 --> 00:28:52.950
when you have a, sort of flip classroom

00:28:52.950 --> 00:28:55.080
or especially in corrective activities

00:28:55.080 --> 00:28:57.370
where teachers have tried their best

00:28:57.370 --> 00:28:59.730
to teach particular concept
and skills in one way,

00:28:59.730 --> 00:29:01.420
they need other options.

00:29:01.420 --> 00:29:04.010
And the availability of
instructional alternatives

00:29:04.010 --> 00:29:07.500
through technology now is
so wonderful and so broad

00:29:07.500 --> 00:29:10.060
that it gives teachers much more latitude

00:29:10.060 --> 00:29:12.600
and much more flexibility
in what they can provide

00:29:12.600 --> 00:29:13.433
for students.

00:29:13.433 --> 00:29:16.370
So it's trying to interpret
that in the modern context,

00:29:16.370 --> 00:29:18.310
in which teachers are now working,

00:29:18.310 --> 00:29:20.840
and be able to use these
new tools that we have

00:29:20.840 --> 00:29:22.610
in good and productive ways.

00:29:22.610 --> 00:29:26.060
So we're hoping that this
book will allow teachers

00:29:26.060 --> 00:29:29.495
to take those ideas of all students

00:29:29.495 --> 00:29:30.822
(indistinct) excellently.

00:29:30.822 --> 00:29:33.170
The practical ways of accomplishing that,

00:29:33.170 --> 00:29:37.730
as Benjamin Bloom described,
interpreted in a modern context

00:29:37.730 --> 00:29:41.140
and in giving them lots
of ideas and examples

00:29:41.140 --> 00:29:43.880
from what successful teachers
who are using mastery learning

00:29:43.880 --> 00:29:46.910
have found to work pretty well for them.

00:29:46.910 --> 00:29:47.743
- That sounds great.

00:29:47.743 --> 00:29:51.000
We definitely, not surprisingly,
feel like technology

00:29:51.000 --> 00:29:55.630
can help teachers scale
the kinds of practices

00:29:55.630 --> 00:29:58.380
around mastery learning
that, where it's difficult

00:29:58.380 --> 00:30:01.440
even for one teacher in
a classroom of 30 to do,

00:30:01.440 --> 00:30:04.800
and that technology can
be a tool to help them

00:30:04.800 --> 00:30:07.980
scale some of these ideas
to their classroom sizes.

00:30:07.980 --> 00:30:11.110
So I look forward to reading more.

00:30:11.110 --> 00:30:13.370
- Yeah, absolutely true Kristen.

00:30:13.370 --> 00:30:14.783
In fact, that's, I
think, one of the things

00:30:14.783 --> 00:30:19.215
that all educators have
learned through the pandemic,

00:30:19.215 --> 00:30:23.200
is that, if you were unwilling to consider

00:30:23.200 --> 00:30:26.650
the viability of technology
before, now it's a must.

00:30:26.650 --> 00:30:29.120
And what that did is it opened the door

00:30:29.120 --> 00:30:31.420
to all kind of different possibilities.

00:30:31.420 --> 00:30:33.640
It certainly increased the demand

00:30:33.640 --> 00:30:35.270
for those kind of services,

00:30:35.270 --> 00:30:38.470
but I think it made
educators more sophisticated

00:30:38.470 --> 00:30:40.493
in determining quality of those as well.

00:30:41.340 --> 00:30:43.560
There's a lot out there on the internet

00:30:43.560 --> 00:30:45.350
that is not very good.

00:30:45.350 --> 00:30:46.950
And to be able to distinguish those

00:30:46.950 --> 00:30:48.810
in terms of the quality programs.

00:30:48.810 --> 00:30:51.412
And I think that's the
other thing that, I mean,

00:30:51.412 --> 00:30:53.710
I don't mean to be an
advertisement for the Khan Academy,

00:30:53.710 --> 00:30:56.420
but I think you have
done a really good job

00:30:56.420 --> 00:30:58.920
of looking at equality
control for these things

00:30:58.920 --> 00:31:02.520
and really trying to ensure,
through various devices,

00:31:02.520 --> 00:31:04.990
that the kind of things
that you put out there

00:31:04.990 --> 00:31:06.280
are things that are going to help students

00:31:06.280 --> 00:31:07.860
in ways that are meaningful to them.

00:31:07.860 --> 00:31:10.160
I think that's a tremendous,
tremendous asset.

00:31:11.230 --> 00:31:12.063
- Yeah.

00:31:12.063 --> 00:31:14.230
That is fundamentally what we are about.

00:31:14.230 --> 00:31:18.380
It is already past time
for us to close up.

00:31:18.380 --> 00:31:21.320
Thank you so much for joining
us today and for sharing

00:31:21.320 --> 00:31:23.810
your views about mastery
learning and grading

00:31:23.810 --> 00:31:25.363
with the audience today.

00:31:27.100 --> 00:31:29.150
- Kristen, it's been my
pleasure to be with you.

00:31:29.150 --> 00:31:30.760
Thank you for this wonderful honor.

00:31:30.760 --> 00:31:31.730
I do appreciate it.

00:31:31.730 --> 00:31:35.005
And I hope that we'll have
other conversations again.

00:31:35.005 --> 00:31:36.170
- Absolutely.

00:31:36.170 --> 00:31:38.360
And thanks to all of you
listening for joining us.

00:31:38.360 --> 00:31:39.810
Do stay tuned tomorrow.

00:31:39.810 --> 00:31:44.420
We have Chase Nordengren
who will be joining us

00:31:44.420 --> 00:31:48.550
from NWEA to talk about
goal setting, motivation

00:31:48.550 --> 00:31:52.070
and how to start and
reset learning routines,

00:31:52.070 --> 00:31:55.180
which are good things to think
about as we head into summer.

00:31:55.180 --> 00:31:57.280
Thank you all and we'll see you next time.


Humans and ecosystems: how do vultures provide ecosystem services?

WEBVTT
Kind: captions
Language: en

00:00:00.740 --> 00:00:04.140
- [Instructor] Can you imagine
eating bones for breakfast?

00:00:04.140 --> 00:00:07.110
It sounds crunchy and pretty gross,

00:00:07.110 --> 00:00:10.350
but that's exactly what
the lammergeier eats.

00:00:10.350 --> 00:00:12.300
The lammergeier is a scavenger,

00:00:12.300 --> 00:00:14.580
which means it eats the decaying flush

00:00:14.580 --> 00:00:16.860
and bones of dead animals.

00:00:16.860 --> 00:00:20.990
Rotting animal carcasses can
be full of harmful substances,

00:00:20.990 --> 00:00:24.100
including toxins produced by bacteria.

00:00:24.100 --> 00:00:28.150
These toxins can cause serious
health issues in humans.

00:00:28.150 --> 00:00:30.910
However, the vultures
have evolved an incredibly

00:00:30.910 --> 00:00:33.440
acidic digestive system, allowing them

00:00:33.440 --> 00:00:36.780
to eat deceased carcasses
without becoming sick.

00:00:36.780 --> 00:00:39.520
The lammergeier's
stomach acid is so acidic

00:00:39.520 --> 00:00:43.830
that it can digest most
bones in about 24 hours.

00:00:43.830 --> 00:00:46.950
Vultures are essential
to keeping our ecosystems

00:00:46.950 --> 00:00:50.400
and us healthy by getting
rid of harmful substances

00:00:50.400 --> 00:00:53.740
that could contaminate
soil, water or food.

00:00:53.740 --> 00:00:55.810
Carcass cleanup by vultures is something

00:00:55.810 --> 00:00:58.640
we call an ecosystem
service, which is a way

00:00:58.640 --> 00:01:02.090
that we humans benefit from ecosystems.

00:01:02.090 --> 00:01:05.200
There are many different
kinds of ecosystem services,

00:01:05.200 --> 00:01:08.090
which can be sorted into four categories.

00:01:08.090 --> 00:01:11.470
First, we have provisional
ecosystem services,

00:01:11.470 --> 00:01:14.550
which are the resources
that are provided by nature

00:01:14.550 --> 00:01:18.680
that we can use or eat, like
fruits, vegetables\ and fish.

00:01:18.680 --> 00:01:21.480
Provisional ecosystem
services also include

00:01:21.480 --> 00:01:24.750
clean drinking water, timber, oils,

00:01:24.750 --> 00:01:28.300
some medicines and natural energy sources.

00:01:28.300 --> 00:01:31.770
We also have regulating
ecosystem services,

00:01:31.770 --> 00:01:33.860
which are all the processes that help

00:01:33.860 --> 00:01:36.820
keep ecosystems healthy and functional.

00:01:36.820 --> 00:01:40.460
These include bacteria and
invertebrates decomposing

00:01:40.460 --> 00:01:43.810
or breaking down waste,
bees and hummingbirds

00:01:43.810 --> 00:01:46.405
pollinating all kinds of plants and trees

00:01:46.405 --> 00:01:49.070
and other plants holding soil together

00:01:49.070 --> 00:01:50.570
with their root systems to help

00:01:50.570 --> 00:01:53.870
with flood control and
to stop soil erosion,

00:01:53.870 --> 00:01:57.040
and, of course, regulating
ecosystem services

00:01:57.040 --> 00:01:59.700
also include our friends, the vultures,

00:01:59.700 --> 00:02:03.440
who help with carcass
removal and disease control.

00:02:03.440 --> 00:02:04.970
Ecosystems wouldn't work

00:02:04.970 --> 00:02:07.870
without supporting ecosystem services.

00:02:07.870 --> 00:02:10.330
These are the underlying natural processes

00:02:10.330 --> 00:02:12.300
that are the foundation of ecosystems

00:02:12.300 --> 00:02:15.290
and without them, we wouldn't
be able to breathe air,

00:02:15.290 --> 00:02:17.750
drink clean water or grow food.

00:02:17.750 --> 00:02:20.210
Take photosynthesis for example.

00:02:20.210 --> 00:02:21.980
When plants use sunlight, water

00:02:21.980 --> 00:02:25.030
and carbon dioxide to
make sugars and oxygen.

00:02:25.030 --> 00:02:28.120
Without photosynthesis, we
wouldn't have enough oxygen

00:02:28.120 --> 00:02:30.500
in our atmosphere to
breathe, and we wouldn't

00:02:30.500 --> 00:02:32.010
have all the foods that we get

00:02:32.010 --> 00:02:35.270
from plants, like fruits, seeds, and nuts.

00:02:35.270 --> 00:02:37.520
Other supporting
ecosystem services include

00:02:37.520 --> 00:02:40.100
the water cycle, the nutrient cycle

00:02:40.100 --> 00:02:43.490
and even soil formation and finally,

00:02:43.490 --> 00:02:46.570
we also have cultural ecosystem services.

00:02:46.570 --> 00:02:50.030
Have you ever visited or seen
photos of the Grand Canyon,

00:02:50.030 --> 00:02:53.880
the Redwoods in California
or Yellowstone National Park?

00:02:53.880 --> 00:02:56.350
These are incredible
landscapes that provide

00:02:56.350 --> 00:02:59.240
a lot of meaning and inspiration to us.

00:02:59.240 --> 00:03:00.730
Think about the art and music

00:03:00.730 --> 00:03:03.240
that gets made about different ecosystems.

00:03:03.240 --> 00:03:04.957
Maybe you've heard Dolly Parton's

00:03:04.957 --> 00:03:07.080
"My Tennessee Mountain Home."

00:03:07.080 --> 00:03:08.560
She couldn't have written that song

00:03:08.560 --> 00:03:10.990
about any other part of the country.

00:03:10.990 --> 00:03:14.350
You might have hobbies that
you enjoy doing outside too.

00:03:14.350 --> 00:03:17.220
For me, I love bird-watching and learning

00:03:17.220 --> 00:03:19.030
about all of the different bird species

00:03:19.030 --> 00:03:20.980
that I can see where I live,

00:03:20.980 --> 00:03:23.770
and that's a cultural ecosystem service.

00:03:23.770 --> 00:03:26.960
Plus, ecosystems have religious, spiritual

00:03:26.960 --> 00:03:30.260
and historical value for
diverse groups of people.

00:03:30.260 --> 00:03:33.670
For example, American-Indian
tribes have deep ancestral

00:03:33.670 --> 00:03:37.660
and spiritual connections to
many North-American ecosystems.

00:03:37.660 --> 00:03:40.800
So ecosystems also play an important role

00:03:40.800 --> 00:03:42.980
in maintaining the richness and diversity

00:03:42.980 --> 00:03:46.083
of people's cultures and
societies of our world,

00:03:46.930 --> 00:03:51.400
but a loss of biodiversity can
make ecosystems less healthy,

00:03:51.400 --> 00:03:54.060
which makes it harder for
us to get the resources

00:03:54.060 --> 00:03:57.000
and ecosystem services we rely on.

00:03:57.000 --> 00:04:00.530
Vultures might be able to eat
all kinds of nasty toxins,

00:04:00.530 --> 00:04:04.270
but they can get sick and die
from human-made chemicals.

00:04:04.270 --> 00:04:08.500
For example, diclofenac,
a common veterinary drug

00:04:08.500 --> 00:04:11.900
used to treat cattle, will
unfortunately kill vultures

00:04:11.900 --> 00:04:14.240
if they eat it from a cow carcass.

00:04:14.240 --> 00:04:17.310
Vulture populations have declined by 95%

00:04:17.310 --> 00:04:19.680
in parts of the world, and that's caused

00:04:19.680 --> 00:04:22.490
some pretty big problems in ecosystems.

00:04:22.490 --> 00:04:25.630
With fewer vultures around
to clean up carcasses,

00:04:25.630 --> 00:04:29.210
diseases can quickly spread,
and bacteria from the carcasses

00:04:29.210 --> 00:04:32.450
can contaminate
surrounding soil and water.

00:04:32.450 --> 00:04:35.160
In turn, people can get
very sick when vultures

00:04:35.160 --> 00:04:36.920
and others scavengers aren't around

00:04:36.920 --> 00:04:38.900
to keep the ecosystem healthy.

00:04:38.900 --> 00:04:42.990
So the next time you see a
vulture gliding through the sky,

00:04:42.990 --> 00:04:45.880
take a moment to think about
how that species is helping

00:04:45.880 --> 00:04:49.130
to keep the ecosystem
clean and healthy for all.

00:04:49.130 --> 00:04:52.090
Through cleaning up
carcasses and eating bones,

00:04:52.090 --> 00:04:54.640
vultures play an important
role conserving the health

00:04:54.640 --> 00:04:58.823
of our ecosystems by transforming
death and decay into life.


Biodiversity and ecosystem health: a Hawaiian Islands case study

WEBVTT
Kind: captions
Language: en

00:00:00.432 --> 00:00:03.350
(waves splashing)

00:00:03.350 --> 00:00:04.650
- [Narrator] When you think of islands,

00:00:04.650 --> 00:00:07.790
you might think of pristine
beaches and palm trees

00:00:07.790 --> 00:00:10.810
gently swing along with a warm breeze.

00:00:10.810 --> 00:00:12.380
Sounds like paradise.

00:00:12.380 --> 00:00:13.800
And as a scientist,

00:00:13.800 --> 00:00:16.810
islands are my kind of place for research.

00:00:16.810 --> 00:00:18.510
Islands are very beautiful

00:00:18.510 --> 00:00:21.200
and they also have a lot of biodiversity.

00:00:21.200 --> 00:00:23.040
Biodiversity can be described

00:00:23.040 --> 00:00:26.330
as the variety of species in an ecosystem.

00:00:26.330 --> 00:00:30.150
Now, some ecosystems have
higher biodiversity than others,

00:00:30.150 --> 00:00:32.380
but all ecosystems have a variety

00:00:32.380 --> 00:00:34.760
of species that interact in specific ways

00:00:34.760 --> 00:00:36.200
with one another.

00:00:36.200 --> 00:00:38.290
Islands have such a variety of species

00:00:38.290 --> 00:00:41.730
that they're often called
biodiversity hotspots.

00:00:41.730 --> 00:00:44.330
They're home to so many diverse species,

00:00:44.330 --> 00:00:46.750
much more so than the continents.

00:00:46.750 --> 00:00:49.710
There are nearly half a million
islands around the world,

00:00:49.710 --> 00:00:53.450
but they only make up about
5% of the Earth's land area.

00:00:53.450 --> 00:00:57.150
Yet, islands are home to 20%
of the world's plant species

00:00:57.150 --> 00:01:01.810
and 15% of all mammal,
bird and amphibian species.

00:01:01.810 --> 00:01:04.640
Many of these island
species can only be found

00:01:04.640 --> 00:01:08.020
on one island or within
a group of islands.

00:01:08.020 --> 00:01:11.320
For example, you can only find the 'i'iwi,

00:01:11.320 --> 00:01:13.890
a honeycreeper bird species,
in the main Hawaiian islands

00:01:13.890 --> 00:01:15.759
in the North Pacific Ocean.

00:01:15.759 --> 00:01:19.120
(birds chirping)

00:01:19.120 --> 00:01:21.770
The 'i'iwi are important
pollinator species

00:01:21.770 --> 00:01:24.157
for Hawaiian plants, including the 'opelu

00:01:24.157 --> 00:01:25.680
and and the 'ohi'a.

00:01:25.680 --> 00:01:28.780
Pollination is an essential
part of plant reproduction

00:01:28.780 --> 00:01:32.060
allowing plants to produce
their fruits and seeds.

00:01:32.060 --> 00:01:35.640
While the 'i'iwi feeds on the
sweet nectar of these plants,

00:01:35.640 --> 00:01:38.470
this bird also helps to
support the next generation

00:01:38.470 --> 00:01:40.700
of 'opelu and 'ohi'a.

00:01:40.700 --> 00:01:42.500
These and other types of interactions

00:01:42.500 --> 00:01:44.000
are happening all the time

00:01:44.000 --> 00:01:46.340
between species in an ecosystem.

00:01:46.340 --> 00:01:49.430
You can think of biodiversity
as a sort of safety net,

00:01:49.430 --> 00:01:51.450
with each species as a knot,

00:01:51.450 --> 00:01:54.620
and the ropes between knots
as their interactions.

00:01:54.620 --> 00:01:57.330
The diversity of species
and their interactions,

00:01:57.330 --> 00:01:58.950
hold the net together

00:01:58.950 --> 00:02:01.450
allowing the ecosystem to function.

00:02:01.450 --> 00:02:05.640
Plus, the relationships between
species are often unique.

00:02:05.640 --> 00:02:09.160
For example, the 'i'iwi
has a special curved bill,

00:02:09.160 --> 00:02:11.210
and it's evolved to feed on the nectar

00:02:11.210 --> 00:02:14.540
of very specific flowers
that are similarly curved.

00:02:14.540 --> 00:02:16.020
Like the 'opelu.

00:02:16.020 --> 00:02:18.040
Now, even though the 'i'iwi

00:02:18.040 --> 00:02:21.420
is highly adapted to its
environment, if something happens

00:02:21.420 --> 00:02:25.160
to the 'opelu or 'ohi'a and
the plants start to decline,

00:02:25.160 --> 00:02:27.882
it can spell disaster for the 'i'iwi.

00:02:27.882 --> 00:02:30.310
When an ecosystem changes so much

00:02:30.310 --> 00:02:32.760
that a species can no longer survive?

00:02:32.760 --> 00:02:35.820
That species may become
extinct or die out,

00:02:35.820 --> 00:02:38.440
causing biodiversity to decrease.

00:02:38.440 --> 00:02:41.550
And unfortunately, many
of Hawaii's honeycreepers

00:02:41.550 --> 00:02:45.150
and overall biodiversity have
been lost through extinction.

00:02:45.150 --> 00:02:48.120
In the past, there were
at least 20 other species

00:02:48.120 --> 00:02:50.630
of honeycreeper found across Hawaii,

00:02:50.630 --> 00:02:53.470
but many of them have
become extinct over time.

00:02:53.470 --> 00:02:56.090
If we return to our
analogy of biodiversity

00:02:56.090 --> 00:02:57.280
as a safety net?

00:02:57.280 --> 00:02:59.290
Whenever a species goes extinct

00:02:59.290 --> 00:03:01.000
it's like a knot becomes undone

00:03:01.000 --> 00:03:03.700
and parts of the net start to fall apart.

00:03:03.700 --> 00:03:05.500
A decrease in biodiversity

00:03:05.500 --> 00:03:07.810
is often a result of human activities

00:03:07.810 --> 00:03:11.090
which is especially clear
in the Hawaiian Islands.

00:03:11.090 --> 00:03:14.210
In the last few hundred
years, agriculture, grazing,

00:03:14.210 --> 00:03:16.890
logging and development
have taken almost half

00:03:16.890 --> 00:03:18.690
of Hawaii's forest cover.

00:03:18.690 --> 00:03:22.070
And along with it, a big
part of its biodiversity.

00:03:22.070 --> 00:03:25.090
Humans have also brought
non-native animals like rats

00:03:25.090 --> 00:03:26.960
and feral pigs to Hawaii,

00:03:26.960 --> 00:03:29.910
which have changed or
destroyed native habitats.

00:03:29.910 --> 00:03:32.210
Plus, new diseases and climate change

00:03:32.210 --> 00:03:35.370
have led to the extinction
of many Hawaiian species.

00:03:35.370 --> 00:03:37.960
When an ecosystem loses biodiversity,

00:03:37.960 --> 00:03:40.030
it doesn't function as well.

00:03:40.030 --> 00:03:43.080
If 'ohi'a starts to disappear
from Hawaiian forests?

00:03:43.080 --> 00:03:44.440
It's not just the 'i'iwi

00:03:44.440 --> 00:03:46.770
that loses an important food source,

00:03:46.770 --> 00:03:48.770
but the entire ecosystem is affected.

00:03:48.770 --> 00:03:51.200
In fact, scientists often look

00:03:51.200 --> 00:03:53.970
at how complete an
ecosystem's biodiversity is

00:03:53.970 --> 00:03:56.780
in order to measure
the ecosystem's health.

00:03:56.780 --> 00:03:58.970
The safety net of
biodiversity is supported

00:03:58.970 --> 00:04:00.970
by having lots of different species,

00:04:00.970 --> 00:04:02.690
which allows the ecosystem to cope

00:04:02.690 --> 00:04:06.480
with natural disasters like
drought, storms and disease.

00:04:06.480 --> 00:04:09.260
With more biodiversity,
ecosystems are stronger

00:04:09.260 --> 00:04:12.300
and more resilient so
they can recover quickly.

00:04:12.300 --> 00:04:14.230
But, with less biodiversity,

00:04:14.230 --> 00:04:16.780
ecosystems become more vulnerable.

00:04:16.780 --> 00:04:20.257
I told you a lot about how
Hawaii is losing biodiversity,

00:04:20.257 --> 00:04:23.110
however, there is cause for some hope.

00:04:23.110 --> 00:04:26.860
The nene, or Hawaiian
goose, nearly went extinct.

00:04:26.860 --> 00:04:30.210
There were less than 30 birds
in the wild 50 years ago.

00:04:30.210 --> 00:04:32.780
Now, thanks to lots of conservation work

00:04:32.780 --> 00:04:34.890
to improve the habitat for those species,

00:04:34.890 --> 00:04:38.750
there are over 3,000 nene
throughout the islands.

00:04:38.750 --> 00:04:42.020
We humans are part of
earth's biodiversity too.

00:04:42.020 --> 00:04:44.810
We are components of
the ecosystems we touch.

00:04:44.810 --> 00:04:47.389
So if we have the power
to hurt these ecosystems,

00:04:47.389 --> 00:04:50.364
we have the power to
protect and heal them too.

00:04:50.364 --> 00:04:51.197
Aloha.


Ecosystem dynamics: Clark’s nutcrackers and the white bark pine

WEBVTT
Kind: captions
Language: en

00:00:00.250 --> 00:00:03.160
(bird caws)

00:00:03.160 --> 00:00:05.110
- [Instructor] What's that? That sound?

00:00:05.999 --> 00:00:07.270
(bird caws)

00:00:07.270 --> 00:00:09.810
That call sounds like
something a crow would make,

00:00:09.810 --> 00:00:11.690
but not quite.

00:00:11.690 --> 00:00:14.330
That's actually the call of
a really interesting bird

00:00:14.330 --> 00:00:16.210
called Clark's nutcracker.

00:00:16.210 --> 00:00:18.760
These birds are cousins
of the American crow,

00:00:18.760 --> 00:00:21.630
which you might see and
hear around where you live,

00:00:21.630 --> 00:00:23.890
except that the Clark's
nutcrackers like to live

00:00:23.890 --> 00:00:26.570
up in the mountains in alpine ecosystems

00:00:26.570 --> 00:00:28.360
in the Western United States,

00:00:28.360 --> 00:00:31.160
where the winters are pretty
harsh with lots of snow

00:00:31.160 --> 00:00:34.570
and there are lots of evergreen
trees, like pine trees,

00:00:34.570 --> 00:00:37.330
which keep their leaves
all throughout the year.

00:00:37.330 --> 00:00:39.730
But what would this bird possibly eat

00:00:39.730 --> 00:00:41.640
in this kind of ecosystem?

00:00:41.640 --> 00:00:43.940
I'll give you a hint.
It's in the bird's name.

00:00:44.860 --> 00:00:48.020
Turns out that Clark's
nutcrackers love eating seeds,

00:00:48.020 --> 00:00:49.610
and not just any seeds,

00:00:49.610 --> 00:00:52.560
but mainly the seeds of
pine trees, like this one,

00:00:52.560 --> 00:00:54.040
the whitebark pine.

00:00:54.040 --> 00:00:56.190
And it's actually good for the trees

00:00:56.190 --> 00:00:58.350
that nutcrackers eat those seeds.

00:00:58.350 --> 00:01:00.020
Wait. What?

00:01:00.020 --> 00:01:02.410
Let's take a look at the whitebark pine.

00:01:02.410 --> 00:01:05.630
These trees have cones,
which hold their seeds.

00:01:05.630 --> 00:01:08.160
Other pine-tree species
have cones that will open

00:01:08.160 --> 00:01:09.624
when the temperature is warm enough

00:01:09.624 --> 00:01:11.850
or if the air is especially dry

00:01:11.850 --> 00:01:14.432
or when the cone is exposed to fire,

00:01:14.432 --> 00:01:16.320
but for the whitebark pine,

00:01:16.320 --> 00:01:18.590
their cones don't open on their own.

00:01:18.590 --> 00:01:21.910
Instead, the cones have to be pried open,

00:01:21.910 --> 00:01:24.230
and the Clark's nutcracker that does this

00:01:24.230 --> 00:01:26.400
as it looks for seeds to eat.

00:01:26.400 --> 00:01:29.030
But the nutcracker doesn't
just eat the seeds.

00:01:29.030 --> 00:01:32.690
It stores them in what's called
a cache, or a safe place,

00:01:32.690 --> 00:01:35.040
where they store the
seeds to eat them later.

00:01:35.040 --> 00:01:38.080
Remember, these birds live
in an alpine ecosystem,

00:01:38.080 --> 00:01:40.140
where the spring and
summer are pretty warm

00:01:40.140 --> 00:01:41.600
and there's lots to eat,

00:01:41.600 --> 00:01:45.460
but the winters are cold and
long with very little to eat.

00:01:45.460 --> 00:01:48.180
So the nutcrackers have to stock up.

00:01:48.180 --> 00:01:52.350
In fact, the nutcrackers will
cache up to 100,000 seeds

00:01:52.350 --> 00:01:53.750
in a single year.

00:01:53.750 --> 00:01:56.560
I can't remember where I
put my phone half the time.

00:01:56.560 --> 00:01:59.580
But the nutcrackers don't
retrieve all of these seeds.

00:01:59.580 --> 00:02:02.430
Many of the caches won't
be used by the nutcrackers,

00:02:02.430 --> 00:02:06.220
so those seed germinate and
grow into new whitebark pines,

00:02:06.220 --> 00:02:07.993
and the cycle continues.

00:02:09.070 --> 00:02:11.090
Nutcrackers rely on whitebark pines

00:02:11.090 --> 00:02:12.410
as an important food source,

00:02:12.410 --> 00:02:14.530
and the whitebark pines
rely on nutcrackers

00:02:14.530 --> 00:02:15.910
to plant their seeds.

00:02:15.910 --> 00:02:19.730
And on top of that, more
than 100 other alpine species

00:02:19.730 --> 00:02:22.280
of plants and animals benefit
from that relationship

00:02:22.280 --> 00:02:25.180
between the Clark's nutcracker
and the whitebark pine.

00:02:25.180 --> 00:02:28.450
For example, Douglas
squirrels will also eat seeds

00:02:28.450 --> 00:02:31.320
from whitebark pine cones
and mountain bluebirds

00:02:31.320 --> 00:02:34.430
and northern flickers may nest
in the whitebark pine, too.

00:02:34.430 --> 00:02:36.470
When you look at it, all
of these interactions

00:02:36.470 --> 00:02:39.620
that occur in this all pine
ecosystem are like a web.

00:02:39.620 --> 00:02:42.700
Each population interacts
with many other populations,

00:02:42.700 --> 00:02:44.480
and each population is affected

00:02:44.480 --> 00:02:46.730
by non-living parts of the environment

00:02:46.730 --> 00:02:48.750
like temperature and snowfall.

00:02:48.750 --> 00:02:51.850
So a change in any one
part of an ecosystem

00:02:51.850 --> 00:02:55.490
can lead to changes in many of
the ecosystem's populations.

00:02:55.490 --> 00:02:58.420
For example, if something
happens to the nutcrackers

00:02:58.420 --> 00:03:00.920
and their population starts to decline,

00:03:00.920 --> 00:03:03.100
that could cause some big
problems for the pines

00:03:03.100 --> 00:03:05.590
that need these birds
to plant their seeds.

00:03:05.590 --> 00:03:08.910
In turn, if the whitebark
pine starts to decline, too,

00:03:08.910 --> 00:03:10.270
that can have negative impacts

00:03:10.270 --> 00:03:12.700
on all the other species
that rely on this tree,

00:03:12.700 --> 00:03:15.540
like squirrels, bluebirds, and flickers.

00:03:15.540 --> 00:03:17.930
Even though it seems like
a perfect relationship

00:03:17.930 --> 00:03:21.710
between the nutcracker and the
pine in the alpine ecosystem,

00:03:21.710 --> 00:03:23.500
every ecosystem is dynamic,

00:03:23.500 --> 00:03:25.480
meaning that parts of the ecosystem,

00:03:25.480 --> 00:03:27.405
both living and non-living,

00:03:27.405 --> 00:03:30.560
can and probably will change over time.

00:03:30.560 --> 00:03:33.940
Sometimes, ecosystems might
experience a negative change,

00:03:33.940 --> 00:03:35.280
like a disruption.

00:03:35.280 --> 00:03:38.100
Maybe it's a particularly
harsh and cold spring,

00:03:38.100 --> 00:03:40.250
and there aren't as many cones and seeds

00:03:40.250 --> 00:03:42.280
for the nutcrackers to cache.

00:03:42.280 --> 00:03:44.160
Changes like that can make it harder

00:03:44.160 --> 00:03:47.690
for individual nutcrackers
to survive and raise chicks,

00:03:47.690 --> 00:03:51.120
which can cause nutcracker
populations to get smaller.

00:03:51.120 --> 00:03:53.330
But on the other hand,
other types of changes

00:03:53.330 --> 00:03:55.790
can help individuals in a population.

00:03:55.790 --> 00:03:56.623
For example,

00:03:56.623 --> 00:03:59.820
if the ecosystem experienced
a particularly warm spring

00:03:59.820 --> 00:04:03.550
after a wet winter, there would
be lots of available food.

00:04:03.550 --> 00:04:06.120
These types of changes
can cause more individuals

00:04:06.120 --> 00:04:10.500
to survive, have offspring,
and increase their population.

00:04:10.500 --> 00:04:12.690
Clark's nutcrackers and their relationship

00:04:12.690 --> 00:04:15.330
to the hard-to-open cones
of the whitebark pine

00:04:15.330 --> 00:04:18.020
are just one example of
the kind of relationships

00:04:18.020 --> 00:04:20.090
that drive many different ecosystems.

00:04:20.090 --> 00:04:22.750
Just like how a decrease
in nutcracker populations

00:04:22.750 --> 00:04:24.597
could cause problems
for the whitebark pine

00:04:24.597 --> 00:04:26.824
and other species in the ecosystem,

00:04:26.824 --> 00:04:29.850
a change to one species in any ecosystem

00:04:29.850 --> 00:04:33.260
can impact a whole web of
interconnected organisms.

00:04:33.260 --> 00:04:36.790
So next time you're outside
and hear the call of a bird,

00:04:36.790 --> 00:04:39.410
think about all of the
interactions that bird has

00:04:39.410 --> 00:04:41.600
with other parts of its ecosystem.

00:04:41.600 --> 00:04:44.830
These relationships are all
part of the complicated web

00:04:44.830 --> 00:04:46.652
that is life on Earth.

00:04:46.652 --> 00:04:48.481
(bird caws)