The Journey, Not The Destination
WHAT IS SCIENCE?
You are a scientist.
You may not quite believe that statement, but the truth of the matter is that
you think and act like a scientist everyday. In this class, you will learn
to recognize the skills you use that identify you as a scientist. You will
practice those skills every day. Whenever you observe something, state an idea,
or notice something unique, you are acting like a scientist. The key is to
truly understand what science is. In
other words, you must first answer the question: What is science?
The word science derives
from the Latin world scire, which means "to know". In essence
science is a "way of knowing". In some of your classes, the
"way of knowing" involves reading from textbooks and having class
discussions with your teacher. You will conduct those activities in
this class as well, but you will also "do stuff". The "way
of knowing" in science primarily involves actively doing things.
These tasks include observing natural phenomena, asking questions about what you
see, wondering what makes things the way that they are, and attempting to find
answers to those questions. To succeed in this class, you must become
proficient with those skills.
Yet that "way of
knowing" is incomplete in itself to be truly scientific. As a
scientist, you will practice the "way of knowing" in an orderly and
systematic manner. That orderly and systematic manner is referred to as
the scientific method. Becoming a skilled practitioner of the scientific
method is one of the goals of your 8th grade science course. An additional
goal involves reporting your findings in structured reports, data tables,
diagrams, and graphs, and in written prose, but we'll get to that later.
For now, you simply need to understand the basic steps of the scientific
THE SCIENTIFIC METHOD
Scientists first state a
problem based on some observation. Technically,
it may not be a “problem” but some curiosity instead. Observations help
gather information about that problem or curiosity.
From those initial observations, scientists formulate a hypothesis.
A hypothesis is not a wild guess about the problem or curiosity – it is
an educated guess. The distinction is important.
A good hypothesis relies upon careful observations and a wealth of
background information. The more
thoughtful and thorough you are in formulating a hypothesis, the better or
“more valid” your hypothesis will be. The
next step involves the fun part – actively designing and conducting an
experiment that tests your hypothesis. Identifying
and controlling your variables are important steps to ensure that your
experiment is valid. Again, we will
detail variables and ways to control them later.
An experiment requires
you to collect data. Sometimes data
involves recording detailed observations of what you think is happening.
These descriptions are subjective in that they may differ from one person
to the next as we all have different perspectives.
Such descriptive observations are called qualitative data.
Other data involves making measurements and calculating data using
formulae. This data is more
objective in that if done properly, should not differ much between individuals.
Measurements and calculations are called quantitative data.
It is important to become proficient with various measurement tools to
ensure that your measurements are accurate and precise.
Focusing on the task at hand and paying attention to details help make
skilled measurers and competent lab workers.
Also, to become proficient in measuring in science, you must master the
metric system of measurements. You
are probably not too familiar with the metric system of measurements since it is
not a part of your daily life. It is important to use the metric system in
science because not only is it recognized internationally, but it is also the
standard on which all science measurements, calculations, and conversions are
based. Regardless of your
nervousness, you will attain fluency in the language of metrics.
An important step in
recording and collecting data involves organizing your data into diagrams, data
tables, and graphs. You will have
much practice in honing these skills and presenting data in the most effective
After analyzing the data,
a scientist reaches a conclusion. Not
all concluding statements are valid however.
Concluding statements depend upon the number of trials for the
experiment, the control of the variables, and how carefully the experiment was
conducted. If it is a “good”
experiment – well designed and carefully conducted, then the conclusion is
deemed valid. A good experiment
also opens a box of new questions as new curiosities about ideas for further
study as well as a constructive critique of your experimental procedures
So in summary, the
scientific method involves:
problem or curiosity
Information about the problem or curiosity
hypothesis based on observations and background knowledge
experiments to test the hypothesis
Sometimes you will have
instant success with this. Sometimes
you will have difficulties and need to redo experiments and revise hypothesis.
Sometimes you will find that your initial hypothesis is way off base.
All of these scenarios are all right.
There is no prize for being first, or for being right all the time.
Remember, that science is a “way of knowing” by doing.
Because of this, it is important to do, and then to make new plans (do
again) as experiments develop. To
refer to a well-known maxim – science is the Journey, not the destination.
Remember that as you begin your 8th grade science course.
Also, make sure you enjoy the ride!
Doing Science -
Identifying Variables and Experimental Design Diagrams
Let’s conduct an
experiment about something you probably know about – I mean have a good deal
of background information. Imagine
you have just made a paper airplane and are curious about what makes it fly.
You folded a paper and threw it. Then
to see what makes it fly, you took the same piece of paper and changed some
aspect of the paper airplane (refolded or added weight) and flew it again,
observing the action of the plane. This
is a very simple experiment, but in order to understand what you’ve done and
draw a valid conclusion, you must analyze this experiment by identifying the
variables of the experiment.
Variables are factors
that changed in the course of the experiment.
These are either variables that you purposefully changed or manipulated
(a refolded wing for example) or are variables that responded to that change
(the distance it flew for example). The
variable that you purposefully changed is called the independent variable –
the “you changed it variable”. The
responding variable – the “it changed variable”, is called the dependent
variable. It may seem a bit
confusing, but there is an easy way of distinguishing the independent variable
from the dependent variable.
The independent variable
(IV) is what you manipulate as you set up the experiment. As you make a paper airplane, you decide how large the wings
are, whether it has flaps or not, if you put weight on the nose of the plane.
These modifications are all examples of independent variables.
The dependent variable (DV) is what you measure or observe as a result of
these changes. In other words, it
describes what happens once the experiment begins.
The distance the plane flies, the amount of
“hang time”, whether it flies straight or not are all examples of
dependent variables. Stating the
relationship between the IV and the DV is the goal for the experiment.
Predicting the relationship between the IV and the DV is what makes a
In order to make a valid
hypothesis and to draw a valid conclusion, it is important to keep the number of
variables that you are testing and measuring small – typically only one or two
at a time. Testing too many
variables at once muddies the waters and makes it more difficult to sort through
the data in order to state a valid conclusion.
In science (as in life sometimes) it is better to KISS.
KISS stands for Keep It Simple Stupid (no
offence intended)! Applying the
KISS maxim to science, you should keep the number of variables to one or two at
In the example of the
paper airplane experiment, let’s imagine that you wanted to see what makes the
plane fly the furthest distance. You
made a standard design airplane and flew it.
Then you added flaps, changed the wing size and added weight to the nose
of the plane and flew it again. Which
of those independent variables (wing size, nose weight, flaps) affected the
flight distance the most? Did the
change of wing size or nose weight affect the flight the most?
Did flaps have any influence? Based
on this experiment, you can’t answer that question because this experiment
modifies too many independent variables.
That muddies the waters and makes it difficult to draw a conclusion.
This experiment forgot to KISS!
LEVELS OF IV
Let’s imagine that you
decided to repeat this experiment, but this time only investigating one
independent variable – that of wing size.
You were investigating the affect of the size of the wing on the distance
that the paper airplane traveled. You
made a standard design plane, flew it and measured the distance traveled.
Then you refolded the wings to make them even bigger, flew it and
measured, and then you refolded it and made the wings even bigger.
How many independent variables is this?
The answer is only one
– the size of the wing. However,
in this experiment, the wing size is modified more than once. That means that there are multiple levels to this independent
variable. The levels of IV for this
experiment are the standard wing size, the medium wing size, and the big wing
size. The IV for this experiment is
the size of the wing. The levels of
the IV are standard, medium, and big wing sizes.
“Standard”, “Medium”, and “Big” are all qualitative
descriptions. It is better to
measure the levels of IV to make them quantitative.
In this experiment, you could measure the total surface area of the wings
to make the variable quantitative instead of merely describing the size.
If you modify the wing
size for this experiment, you must make sure that all other factors remain the
same. Those factors that remain the
same through all levels of the experiment are called constants.
Constants are also referred to as controlled variables, but if that
confuses you, ignore that definition, but remember that constants are those
factors that do not change throughout all levels and all trials of your
experiment. In the example of the
paper airplane experiment, constants include the place of throwing, the paper
itself, the overall design of the plane, the atmospheric conditions etc.
A good experiment has an extensive list of constants.
You should be able to identify at least five constants in each
In science, it is very
important that the results of an experiment are not a “fluke”. Weird, unexplained, and random things always will occur. Also,
no matter how perfect you may have thought that you conducted an experiment,
there is always a chance that you botched the experiment.
In other words, you just messed up! Some people call this “Murphy’s
Law”. Others simple call it being
human. Because we are all humans
there is always some experimental error. Besides,
it is not an easy thing to control all the extraneous variables – things that
you have no control of anyway. At some time in the course of this year, you will
all make mistakes in the laboratory.
However, in “doing”
science, there is a structure that accounts for experimental error and the
reality that as humans we all “mess up” on occasion.
Conducting repeated trials of experiments ensures that experimental error
has limited influence. Conducting
an experiment once is not really sufficient.
What if something “weird” happened?
Conducting an experiment twice is a little better than conducting it
once, but still insufficient. Conducting
an experiment a hundred times – well now we’re on to something!
This is what is meant by repeated trials.
Every time the experiment is conducted is a repeated trial.
The more repeated trials for an experiment the effects of chance or
random errors are reduced. The more
repeated trials, the better the experiment, and the more confident you can be in
analyzing results to draw a valid conclusion.
In this class, your lab
group may conduct an experiment only once.
However, if you combine all the class data, you may have up to ten
trials. When conducting
experiments, you will need to rely on your classmates to increase the number of
repeated trials. You will analyze
the data collected by your classmates in addition to your own group, and state
conclusions based on as many repeated trials as possible.
It is important that the
results of an experiment are consistent with an additional repeated trial.
However, repeated trials can happen concurrently – that is at the same
time. The number of repeated trials
for an experiment can be confused with the number of levels of IV in an
experiment. The number of repeated
trials is the number of times that the entire experiment – including all
levels of the IV, is conducted. It
is the same number as the number of measurements of the DV are taken for each
level. If we return to our paper airplane experiment example, the number of
repeated trials is equal to the number of experimenters in this case.
If fifteen students through a standard, medium, and big sized wings, the
number of repeated trials is fifteen!
That brings us to the
concept of the control group. Students
have had a hard time understanding this concept.
The control is the standard for comparing experimental effects.
It is the basis for comparison. Typically,
it is the group (level of IV) that receives no experimental conditions
(variables). In the example of the paper airplane activity, the control
would be the airplane that has the standard size wings. Controls are also useful in determining whether or not fluke
things influenced the experiment. As
a basis for comparison, you should also have a reasonable expectation that some
result would occur. For paper
airplanes, you should have a reasonable expectation that the standard size wing
would fly. The flights of the
medium and big sized wings are then compared to that of the standard size.
When doctors are testing
new medicines, they always use a control group as a standard for comparison.
They administer medicines to people with a particular ailment and compare
the results of those patients with a group of patients who have the same ailment
but did not receive treatment. The
group that did not receive treatment is the control group.
Sometimes, you will conduct an open-ended experiment that compares
variables that does not have a control group.
Regardless, the best experiments include controls.
Identifying the variables
and constants of an experiment is the first step to becoming a proficient lab
scientist. The next step involves
formatting your variables in an organized way so that the others can easily
deduce what the experiment is about. The
format that you will use is called an experimental design diagram.
An experimental design diagram is a simple diagram that summarizes the
experiment. Making a simple diagram that communicates the IV, the DV, the
constants, the control and the number of repeated trials is an effective way to
summarize the concepts.
To complete an experimental design diagram, begin by drawing a rectangle with a ruler. The IV is written across the top of the rectangle. Within the rectangle, divide into labeled columns that represent the different levels of the IV. The number of repeated trials is indicated in each column. Also, indicate which level of the IV serves as the control for the experiment. Below the rectangle record the DV and then list all the constants. You should list at least 5 constants below the DV.
Above the experimental
design diagram you need to write the title for the experiment and state your
hypothesis. A proper title for an
experiment is a statement that suggests the relationship between the IV and the
DV. “The Paper Airplane
Experiment” is a lousy title in that it doesn’t indicate what either the IV
or the DV are. “The Effect of
Wing Size on the Flight Distance of a Paper Airplane” is an adequate title.
To write good titles of experiments, use the following template:
The Effect of___________(IV) on _________(DV).
Just fill in the blanks to ensure that your titles are adequate!
As mentioned earlier, an
hypothesis is an educated guess or prediction.
In light of what you now know about variables, we can expand upon that
definition. An hypothesis states
what the scientist (you) thinks the effect of the IV will be on the DV.
For example, if wing size is increased, then the paper airplane will fly
a greater distance. Phrasing hypotheses as if… then… statements that predicts
the relationship between the IV and DV will ensure that your hypotheses are
Table 2.1 Experimental
The Effect of Wing Size on the Flight Distance of a Paper Airplane
If the wing size is increased, then the paper airplane will fly a greater
Size of the Wings
Temperature, Size of Paper, Weight of Paper,
Launch Site, Number of flaps
Below are listed several
experimental scenarios. Read each
scenario and identify the IV, DV, constants, control, and repeated trials.
Write a title and state a hypothesis.
Draw a complete experimental design diagram. The experimental scenarios described below are not perfect
and may have some serious flaws. The
better design detective that you are, the more flaws in each scenario you will
1: Compost and Bean Plants
studying about recycling, members of John’s science class investigated the
effect of various recycled products on plant growth. John’s lab group compared the effect of different aged
grass compost on bean plants. Because
decomposition is necessary for release of nutrients, the group hypothesized that
older grass compost would produce taller bean plants.
Three flats of beans (25 plants / flat) were grown for 5 days.
The plants were fertilized as follows: Flat A: 450 g of three-month-old
compost, Flat B: 450 g of six-month-old compost, Flat C: 0 g compost.
The plants received the same amount of sunlight and water each day.
At the end of 30 days, the group recorded the height of the plants in cm.
#2: Metals & Rusting Iron
his science class, Allen determined the effectiveness of various metals in
releasing hydrogen gas from hydrochloric acid.
Several weeks later, Allen read that a utilities company was burying lead
next to iron pipes to prevent rusting. Allen
hypothesized that less rusting would occur with more active metals.
He placed the following into separate beakers of water: a) 1 iron nail,
b) 1 iron nail wrapped with an aluminum strip, c) 1 iron nail wrapped with a
magnesium strip, d) 1 iron nail wrapped with a lead strip.
He used the same amount of water, equal amounts (masses) of the metals,
and the same type and size of iron nails. At
the end of 5 days, he rated the amount of rusting as small, moderate, or large
by analyzing the color of the water.
#3: Perfumes and Bees’ Behavior
read that certain perfume esters (odor causing chemicals) would agitate bees.
Because perfume formulae are secret, she decided to determine whether
unknown ester X was present in four different perfumes by observing the bees’
behavior. She placed a saucer containing 10 mL of the first perfume 3 m
from the hive. She recorded the
time required for the bees to emerge and made observations about the bees’
behaviors. After a 30 minute
recovery period, she tested the second, third, and forth perfumes.
All experiments were conducted on the same day when weather conditions
were similar – that is air, temperature, and wind.
#4: Fossils and Cliff Depth
observed that different kinds and amounts of fossils were present in a cliff
behind her house. She wondered why
changes in fossil content occurred from the top to the bottom of the bank.
She marked the bank at five positions: 5, 10, 15, 20, and 25 m from the
surface. She removed one bucket of
soil form each of the positions and determined the kind and number of fossils in
#5: Aloe vera and Planaria
read that Aloe vera promoted healing of burned tissue.
She decided to investigate the effect of varying amounts of Aloe vera
on the regeneration of planaria. Planaria
are aquatic flat worms that regenerate body parts when severed.
Jackie bisected the planaria to obtain 10 parts (5 head sections and 5
tail sections) for each experimental group.
She applied concentrations of 0%, 10%, 20%, and 30% Aloe vera to
the groups. Fifteen mL of Aloe
vera solutions were applied. All
planaria were maintained in a growth chamber with identical food, temperature
and humidity. On day 15, Jackie
observed the regeneration of planaria parts and categorized the development as
full, partial, or none.
# 6: Cartons and Hole Height
wondered if the height of the hole punched into the side of a quart-sized milk
carton would affect how far from the container the liquid would spurt when the
carton was full of liquid. She used
four identical cartons and punched the same size hole in each.
The hole was placed at a different height on the same size of each
container. The height of the holes
varied in increments of 5 cm ranging from 5 cm to 20 cm from the base of the
carton. She put her finger over the
holes and filled the carton to a height of 25 cm with water.
When each carton was filled to the proper level, she placed it in the
sink and removed her finger. Susie
measured how far from the carton’s base the water had squirted when it hit the
bottom of the sink.
GLOSSARY OF KEY TERMS