The National Student Research Center
E-Journal of Student Research: Science
Volume 7, Number 6, August, 1999
The National Student Research Center
is dedicated to promoting student research and the use of the
scientific method in all subject areas across the curriculum,
especially science and math.
For more information contact:
- John I. Swang, Ph.D.
- Founder/Director
- National Student Research Center
- 2024 Livingston Street
- Mandeville, Louisiana 70448
- U.S.A.
- E-Mail: nsrcmms@communique.net
- http://youth.net/nsrc/nsrc.html
TABLE OF CONTENTS
- In A Controlled Environment, Will
The Addition Of Heat To A Layer Of Soils Act As A Catalyst For
Effective Water Flow?
- The Strength of Electromagnets
- How Friction Effects A Runner On
Different Surfaces
- Can Estimation Skills Improve With
Practice?
- Do Candy Bars Vary In Density?
- Do Different Types Of Cereal Vary
In Density?
- How Does Pollution Affect An Environment?
- Stained Carpet! What Should I Use?
- The Effect Of A Mild Acid On Colored
Chaulk
- How Well Can Boys and Girls Identify
Fruits By Taste Alone?
TITLE: In A Controlled Environment, Will The Addition Of Heat
To A Layer Of Soils Act As A Catalyst For Effective
Water Flow?
STUDENT RESEARCHER: Justin Pearce
SCHOOL ADDRESS: St. Martin High School
Ocean Springs, Mississippi
GRADE: 11
TEACHER: Ray Werdner
I. STATEMENT OF PURPOSE AND HYPOTHESIS:
These experiments are a continuation of previous research which
I've done over the past four years. In these experiments, I set
out to prove that there was a correlation between heat and water
movement through soils. The experiment was: adding heat to a
layer of soils, adding water, then measuring the differences in
the waters drainage. These experiments required that I build an
apparatus to test my hypothesis. In order to have a somewhat
controlled environment it was necessary that I use a heating
source of my design and a method of collecting results. Each
year I've improved my methods and proved my hypotheses.
My goals for this year were to:
·again prove that the addition of heat to a layer of sediments
will facilitate a more efficient water flow.
·test the same apparatus used last year after laying dormant
for a year.
·discover if adding more heating elements to the soil would
improve results.
·augment the heating source with the use of heat from the sun.
·collect more data with the addition of more experimental
runs.
·discover if there is a difference in results when warmer or
colder water is used in the experiments.
·measure the amounts of moisture in the soil after each
experiment, this data would determine how to further these
experiments beyond water flow.
·compare the results of these experiments to the results from
last year.
Each of these objectives were carried out with the goal of
proving empirically there is a direct correlation between heat
and water flow through soils.
Duplication of results and confirmation of my hypothesis are key
to this endeavor. In previous experiments, I hypothesized there
would be a significant difference in water flow when heat is
injected into soils. In order to prove this hypothesis, I
constructed an apparatus which enabled me to collect accurate
and consistent data. The control of heat input and water
collection are two important factors in performing controlled
experiments.
In order to strengthen my results, I must prove three questions.
1) Will the addition of more heating elements strengthen
previous results?
The heating element placement last year was on one level. The
elements this year are on three levels. I proved there is an
affect with heat insertion. Therefore, I hypothesize there will
be a greater effect with the additional heating elements.
2) Would there be a difference in the outcomes if the water used
in the experiments were of varying temperatures?
I've proved that the addition of heat to soils via heating
element does have an effect on water flow. Therefore, I can
hypothesize there will be a measurable affect when warmer water
is used as opposed to cooler water.
3) Are there differences in moisture content in soil samples
when each experiment is tested?
Collecting the moisture content of soil samples after each
experiment should show a measurable result. Therefore, I
hypothesize that adding heat (heating element or water
temperature) will have an affect on these outcomes as well.
II. METHODOLOGY:
The procedures this year are similar to last years with respect
to the comparisons of heat and no heat. This year, however,
there are new experiments involving the use of two water
temperatures.
The moisture content of a sample of soil is taken prior to each
set of experiments and compared against the average of six
samples.
Dormant soil tests: (heat and no heat)
Saturation tests- measure the amount of water that exits after
94 liters of water is pumped evenly on the top of the system.
Two pumps are used, one to evenly disperse the water over the
top of the system and one to pump the water into measuring
containers. A saturation test is run prior to each set of
experiments.
No heat tests- measure the amount of water which exits the
system after 94 liters of water is pumped on top of the system.
The heat is not turned on.
Heat tests- measure the amount of water which exits the system
after 94 liters of water is pumped on top of the system. The
heat is turned on.
The results are compared against one another and graphed.
Heat/no heat comparison tests:
Saturation tests- measure the amount of water that exits after
94 liters of water is pumped evenly on the top of the system.
Two pumps are used, one to evenly disperse the water over the
top of the system and one to pump the water into measuring
containers. A saturation test is run prior to each set of
experiments.
No heat tests- measure the amount of water which exits the
system after 94 liters of water is pumped on top of the system.
The heat is not turned on.
- warmer water is used in one set of experiments.
- cooler water is used in one set of experiments.
Heat tests- measure the amount of water which exits the system
after 94 liters of water is pumped on top of the system. The
heat is turned on.
The results are compared against one another and graphed.
- warmer water is used in one set of experiments.
- cooler water is used in one set of experiments.
Percent moisture tests
A soil sample is taken prior to each set of experiments. This
is done using a section of copper tubing. The tube is "plunged"
into the surface and the sample is weighed to the nearest 1/100
of a gram. The samples are taken just after the experiment in
each of the tests.
The samples are baked at 350 F for four hours to remove moisture
and is then weighed. The percentage of moisture in each sample
is found by dividing the difference by the pre-bake weight. The
percentages are averaged and compared against the sample taken
prior to each set.
III. ANALYSIS OF DATA:
DORMANT SOIL: (final averages)
No Heat- 66.11 liters exit the system - 79.81 liters year four
62.13 F soil temperature
68.00 F water temperature
Heat - 68.12 liters exit the system - 90.01 liters year four
103.50 F soil temperature
66.70 F water temperature
last year : 90.01-79.81 = 10.02 liters difference
this year : 68.12-66.11 = 2.01 liters difference
**shows system still had positive numbers after the soil lay
dormant for several months and became compacted.
HEAT/NO HEAT: WARMER WATER COMPARISONS: (final averages)
No Heat warmer water-
86.85 liters exit the system - 79.81 liters year four
60.85 F soil temperature
65.48 F water temperature
Heat warmer water-
97.11 liters exit the system - 90.01 liters year four
113.15 F soil temperature
80.25 F water temperature
last year : 90.01-79.81 = 10.02 liters difference
this year : 97.11-86.85 = 10.26 liters difference
** shows a replication of lasts years experiments and again
proves my hypothesis
HEAT/NO HEAT: COOLER WATER COMPARISONS: (final averages)
No Heat cooler water-
86.59 liters exit the system
64.90 F soil temperature
59.53 F water temperature
Heat cooler water-
88.69 liters exit the system
100.62 F soil temperature
51.70 F water temperature
this year: 88.69-86.59 = 2.1 liters difference
** shows less water flow but still positive when using heat
In analyzing the data, I again found a direct correlation
between heat and soil hydration. The analysis of water volume
comparisons both in the heat and no-heat tests showed a marked
difference, i.e. more water volume with heat.
IV. SUMMARY AND CONCLUSION:
The results show differences from year four and also show my
hypothesis correct.
One similar experiment I ran in year I showed differences in the
way water move through soil when it's temperatures vary. When
using two water temperatures in this year's experiments I found
that warmer water reacted differently when compared to cooler
water. Its volume was greater as it exited through the
apparatus.
Adding heat to soils show there is an increase in the volume of
water as it exits the system. The addition of more heating
elements in these experiments while using warm water showed no
significant changes in water volume, but it did again show a
positive affect when compared to cooler water. Since no tests
where made last year using "cooler" water, I cannot make a
judgment about the effectiveness of additional heating elements
on this variable.
I could not show any positive affects of heat augmentation with
a solar panel. The apparatus was positioned in a shaded area
and direct sunlight was unavailable; however, I feel this is a
possible way to help with energy conservation.
The moisture percentages of the soils show how there is an
affect when using heat and no heat. The results show less
moisture on top of the apparatus when the system uses heat,
either via water into the system or the heating element. The
use of no heat in either circumstance shows less moisture that I
cannot explain; however, it is clear there is effect while using
heat.
V. APPLICATION:
Future plans are to recreate these experiments using smaller
separate containers. The tests will be run simultaneously to
further control the experiments. The use of smaller containers
will allow for control of the heat variables. The tests will be
isolated in that all heat experiments will be in separate
containers and the no-heat experiments in separate containers.
TITLE: The Strength of Electromagnets
STUDENT RESEARCHER: Hannah Kaufmann-Swang
SCHOOL: Mandeville Middle School
Mandeville, Louisiana
GRADE: 5
TEACHER: Mrs. Santangelo
I. STATEMENT OF PURPOSE AND HYPOTHESIS::
I wanted to know how the number of coils of wire around an
electromagnet affects its strength. My hypothesis states that
the electromagnets with the most coils will be the most
powerful.
II. METHODOLOGY:
1. I gathered my materials: battery, electrical wire, nails,
screws, pins, and a data collection sheet.
2. My dad coiled the electrical wire around three nails. One
nail had 5 coils. One nail had 10 coils. One nail had 20 coils.
These nails were the electromagnets.
3. Then I hooked up each electromagnet to the battery and held
it close to a pile of small metal screws to see how many it
would pick up. I did this three times for all three
electromagnets.
4. Then I hooked up each electromagnet to the battery and held
it close to a pile of sewing pins to see how many it would pick
up. I did this three times for all three electromagnets.
5. I recorded the number of screws and pins that each
electromagnet picked up.
My control variables were the size of the battery, the diameter
of the wire, the size of the nails, the size of the screws and
the pins, and the way that I held the electromagnet next to the
screws and pins. My manipulated variable was the number of coils
of electrical wire around each nail. My responding variable was
the number of screws or pins that the electromagnet picked up.
I used the following materials: a six volt battery, electrical
wire, metal nails, metal screws, sewing pins, and a data
collection sheet.
III. DATA COLLECTION FORM:
The Number Of Metal Screws Picked Up
By The Electromagnets
Five Ten Twenty
Coils Coils Coils
Trial 1 1 5 5
Trial 2 1 3 7
Trial 3 1 1 5
Average 1 3 5.7
The Number Of Sewing Pins Picked Up
By The Electromagnets
Five Ten Twenty
Coils Coils Coils
Trial 1 2 8 11
Trial 2 3 7 10
Trial 3 3 7 12
Average 2.2 7.1 11
III. ANALYSIS OF DATA:
The electromagnet with five coils picked up an average of 1
metal screw. The electromagnet with ten coils picked up an
average of 3 metal screws. The electromagnet with twenty coils
picked up an average of 5.7 metal screws.
The electromagnet with five coils picked up an average of 2.2
sewing pins. The electromagnet with ten coils picked up an
average of 71 sewing pins. The electromagnet with twenty coils
picked up an average of 11 sewing pins.
IV. SUMMARY AND CONCLUSIC)N:
The electromagnet with the most coils picked up the most screws
and pins. Therefore, I accept my hypothesis which stated that
the electromagnets with the most coils will be the most
powerful.
V. APPLICATION:
If I want to use an electromagnet to pick up something heavy, I
now know that I will need an electromagnet with many coils.
Lighter objects don't need as many coils on the electromagnet to
be picked up.
TITLE: How Friction Effects A Runner On Different Surfaces
STUDENT RESEARCHERS: Danielle Thorp, Brandi Roe, and Jenna
Harold
SCHOOL: Alki Middle School
Vancouver, WA 98685
GRADE: 8th
TEACHER: Mr. Duncan
I. Statement of Purpose and Hypothesis:
Our purpose was to test a runner on four surfaces, gym floor,
track, grass, and sand. Our hypothesis was that the runner
would run farther in a certain amount of time on the track in
comparison to the gym floor, grass, and sand. We think that the
runner will go farthest on the track because it was made and
designed for running.
II. Methodology:
Our methodology was to have the runner run at about the same
speed on each surface for 2 seconds. We measured the length
with meter sticks and measured the time with a stopwatch. To
make the experiment as accurate as possible, the runner wore the
same shoes each time and the runner ran on each surface three
times.
III. Analysis of Data:
Track Gym Floor Grass Sand
1st 7.60m 4.81m 4.35m 5.54m
2nd 5.90m 6.00m 6.34m 5.44m
3rd 7.86m 7.02m 6.35m 5.44m
Average 7.12m 5.94m 5.68m 5.47m
The track was the fastest time with an average of 7.12m. The
gym floor came in second with an average of 5.94m. The grass
was third with an average of 5.68m. The sand obviously was last
place with an average of 5.68m.
IV. Summary and Conclusion:
Our data lead us to the conclusion that the runner ran the
farthest in 2 seconds on the track. The runner didn't run as
far on the gym floor, grass, and sand because they all have
different purposes than the track. The gym floor was designed
for all sports, not just running. The gym floor is also very
slick and the runner's shoes didn't grip as well on the surface.
The runner didn't run as far on the grass because it is a bumpy,
slick surface. It wasn't as easy to run on as the track because
of that. The runner didn't go as far on the sand because it is
a rough, uneven, bumpy surface and when the runners shoes were
pushing off, the sand moved underneath the runner's shoes.
Therefore, our hypothesis was correct. The runner did go
farther on the track compared to the other surfaces. This was
the information that we got from our data and performing the
experiment.
V. Application:
I think that our finding applies to the real world because this
same experiment could be used on testing tennis shoes or tires.
It would be valuable to the economy because the researchers
could test the product before it was marketed.
Title: Can Estimation Skills Improve With Practice?
Student Researcher: Caitlin Masci
School Address: Chambersburg Area Middle School
Chambersburg, PA
Grade: 7
Teacher: Dr. Torri
I. STATEMENT OF PURPOSE AND HYPOTHESIS:
I wanted to know if estimation skills improve with practice? My
hypothesis stated that estimation skills will improve with
practice.
II. METHODOLOGY:
Materials: Triple beam balance
salt
Steps:
1. Student stands behind triple beam balance.
2. Student pours salt until they think they are at ten grams.
3. Measure amount poured.
4. Record data.
5. Repeat all steps four times.
6. Graphed this information.
III. ANALYSIS OF DATA:
Student # Best Estimation Worst Estimation
1 8.5 g .5 g
2 11.5 g 5.0 g
3 11.5 g .3 g
4 8.5 g 16.0 g
5 9.9 g 6.0 g
6 10.0 g 6.5 g
IV. SUMMARY AND CONCLUSION:
Our class just conducted our third experiment. We weighed salt
using a triple beam balance. As usual we recorded our data. We
made a table and a chart. We measured in grams. Six students
were taken from the class. They were each given 5 tries. Most
people improved. Some people were able to reach ten grams or
around that.
My hypothesis proved to be correct. I thought that estimation
skills would improve.
V. APPLICATION
I think in future experiments you could choose more than 6
students. You could give each person less tries. I think this
will make the experiment easier to conduct.
Title: Do Candy Bars Vary In Density?
Student Researcher(s): Daniel Stoner and Kristi Smith
School Address: Chambersburg Area Middle School
Chambersburg, PA
Grade: 7
Teacher: Dr. Torri
I. STATEMENT OF PURPOSE AND HYPOTHESIS:
We wanted to know if candy bars vary in density? Our hypothesis
stated that candybars do vary in density.
II. METHODOLOGY:
Materials: variety of candy bars
triple beam balance
graduated cylinder
Steps:
1. Find the mass of the candy bar.
2. Find the volume.
3. Record data.
4. A graph was produced using these numbers.
III. ANALYSIS OF DATA:
Candy Bar Density
5th Avenue 1
Butterfinger 1
Reese Sticks .72
Hershey 1
Reese cup 1
Twix 1.1
Milky Way 1.2
Snickers .93
Jeff Coy Bar 1.4
Kit Kat .88
Nutrageous 1.2
Cookies and Cream 1
(Some of the candy bars had irregular shapes so we couldn't
measure them. We had to use a graduated cylinder which
automatically gave us the candy bar's volume.)
IV. SUMMARY AND CONCLUSION:
We found the density of many different candy bars. First, we
took the measurements of the candy bar. We then found it's
volume. We used a triple beam balance to find the mass.
We charted our data. There was a range in density from .72 to
1.4. The least dense bar was a Reese Stick. The bar with the
most density was the Jeff Coy Bar.
The whole class had to make a hypothesis. I guessed that
candy bars do vary in density. My hypothesis proved to be
correct.
V. APPLICATION:
I think in future experiments you could use a graduated
cylinder to find the volume of each bar. You might want to use
less candy bars if you want the experiment to be shorter. This
might make the experiment easier to conduct.
Title: Do Different Types Of Cereal Vary In Density?
Student Researcher: Caitlin Masci
School Address: Chambersburg Area Middle School
Chambersburg, PA
Grade: 7
Teacher: Dr. Torri
I. STATEMENT OF PURPOSE AND HYPOTHESIS:
I want to know if different types of cereal vary in density? My
hypothesis stated that cereals do vary in density.
II. METHODOLOGY:
Materials: - variety of cereal
- triple beam balance
- graduated cylinder
- piece of paper
- marker
Steps:
1. Crush a small amount of cereal using a marker into powder.
2. Measure out 10ml of crushed cereal using the graduated
cylinder.
3. Weigh the cereal using a triple beam balance.
4. Find the density by dividing the mass by the volume.
5. Record and graph data.
III. ANALYSIS OF DATA:
Cereal Density
Lucky Charms .26
Cinnamon Grahams .38
Special K .38
Kellogs .39
Cornflakes .40
Fruit Loops .29
Reese Cups .25
Honey Comb .21
Fruity Pebbles .43
French Toast Crunch .24
IV. SUMMARY AND CONCLUSION:
We found the density of ten different types of cereal. The
least dense cereal was Honey Comb and the cereal with the most
density was Fruity Pebbles. This gave us a range from .21 to
.43 g/cm cubed.
I made the hypothesis that cereal does vary in density. It
proved to be correct.
V. APPLICATION:
In future experiments you could use more of a variety of
cereals. This might make the experiment more exciting.
Title: How Does Pollution Affect An Environment?
Student Researcher: Jeffrey C. Chen
School Address: Edgemont Jr/Sr High School
White Oak Lane
Scarsdale, New York 10583
Grade 7
Teacher: Ms. Russo
I. Statement of Purpose and Hypothesis:
Don't you remember when people said dumping waste could destroy
an environment? Well, I wanted to see what exactly happens. By
using a bottle greenhouse, I decided to simulate an enclosed
environment and observe what happens when different pollutants
are introduced. I added motor oil to simulate an oil spill and
lemon juice to simulate acidic rain, air freshener which
contains harmful chemicals to simulate air pollution, Drano as a
chemical waste, and water to act as a control.
My hypotheses are that air freshener will slow down plant growth
and kill it slowly and Drano will do a lot of damage to the
plant in under a week, but it will not kill the plant. Motor
oil will be similar to Drano, but it will take longer to cause
damage.
II. Methodology:
In this experiment, I used five large soda bottles, soil, and
fifteen Sonnet pink snapdragons plants of the same species,
small enough to fit three into one bottle. The different
substances used as pollutants were motor oil, Drano, lemon
juice, water, and Wizard vanilla air freshener.
The procedure for testing my hypothesis is as follows:
Cut open the bottles 5cm from the bottom. Plant three plants in
each bottle. Add 10 cc of water to each bottle.
For the treatment for each group, prepare a solution of each
different pollutant as described below. Check and maintain the
pH of each solution using litmus paper.
Bottle One: Control group (orange label) - add 10 cc of plain
water to get a pH of 5.5.
Bottle Two: Lemon Juice group (yellow label) - add 1 cc of
freshly squeezed lemon juice to 9 cc of water to make a solution
with a pH of 2.5.
Bottle Three: Motor Oil group (green label) - add 1 cc of Mobil
super high performance motor oil 10W-40 to 9cc of water to make
a solution with a pH of 8.0.
Bottle Four: Air Freshener group (light blue label) - spray 1 cc
of the substance without adding water, onto the plants every
other day. The pH is already 8.0.
Bottle Five: Drano group (red label) - add 1 cc of Drano to 9 cc
of water to make a solution with a pH of 12.0.
On Day one, before sealing the bottles, for each bottle except
bottle number four, spray 10cc of the pollutant solution into
the soil and another 10cc onto the plant itself. Beginning on
Day 3, spray 5cc to both soil and plants each day. After each
treatment, reseal the bottle with masking tape.
Every other day, take off the upper part of the greenhouse
(bottle). Measure the heights of each plant and also count the
number of dead or damaged leaves.
The controlled variables for this experiment are the bottle
colors, size, type of plant, size of plant at start of
experiment, and the amount of water. The manipulated variables
are the additives to simulate various pollutants. The
responding variables are the heights and damage to the leaves.
III. Analysis of data:
Table 1: Average Heights of plants in Centimeters
Control Lemon Motor Air Drano
Juice Oil Freshener
Day 1 10.00 9.70 9.30 9.80 9.50
Day 5 10.07 9.90 9.80 10.20 9.80
Day 21 14.00 10.70 10.50 11.00 10.30
Table 2: Number of Damaged/Dead Leaves
Control Lemon Motor Air Drano
Juice Oil Freshener
Day 1 0.00 0.00 0.00 0.00 0.00
Day 5 0.00 2.00 0.00 0.00 6.00
Day 21 0.00 13.00 0.00 48.00 65.00
Looking at the data, all the pollutants stunted the growth of
the plants after five days of treatment. They grew only one-two
cm over twenty-one days. However, the control plants grew 4 cm
(from 10 cm to 14 cm)
The pollutants have different effects on the damage of the
leaves of the plants. Drano acted the quickest, it was the
first to slow down the growth of the plant and it also killed
leaves and the plant itself in the shortest number of days. At
Day 21, it had killed 65 leaves and the plants grew to a low
height of 10.3 cm. Therefore, Drano is proven to be the
deadliest out of the five substances used.
The air freshener destroyed the second largest number of leaves
and it also slowed the growth of the plants used. The air
freshener group lost 48 leaves and the plant grew to a height of
11 cm after 21 days.
The lemon juice group had 13 leaves dead and grew to a height of
10.67 cm by day 21.
Motor oil stunted the growth of the plants, but killed none of
them. I thought something worse would happen with the motor
oil.
Finally the control group treated with water grew the tallest
with a height of 14 cm and no damaged leaves after 21 days.
IV. Summary and Conclusion:
From all the data I have collected in my experiment, I conclude
that substances with a high pH are more deadly than acidic
substances. All the substances used as pollutants have damaging
effects on the plants. If Drano, Motor oil, acids, and air
freshener are put into an environment, they would be very
destructive.
My hypotheses that Drano would destroy the plant the quickest
and air freshener would damage the plants at a slower rate than
the other substances was pretty accurate. My hypothesis that
lemon juice will not kill plants and only stunt the growth was
disproved because lemon juice killed some leaves. My prediction
that motor oil would kill the plants was also disproved because
it did not damage any leaves and only stunted growth.
V. Application:
Now I know what effect these pollutants have on the growth of
plants. My experiment needs to be repeated and expanded to
verify the results. We need to protect our environment from
these and other chemicals to preserve plant life, which is
critical for our survival. One solution would be to avoid
dumping any substances with a very high or very low pH level
into sewers or a living environment. Motor oils should be
recycled by a local gas station and not dumped. By doing this,
the Earth will probably have a brighter future.
TITLE: Stained Carpet! What Should I Use?
STUDENT RESEARCHER: Kit Salo and Sara Edwards
SCHOOL: Mandeville Middle School
Mandeville, Louisiana
GRADE: 6
TEACHER: Tammy Gendusa
I. STATEMENT OF PURPOSE AND HYPOTHESIS:
Which liquid (vinegar, liquid soap, vegetable oil, club soda,
ammonia, and milk) works best on stains? We want to do this
project to help frustrated moms. We think that club soda will
remove a stain the best.
II. METHODOLOGY:
1. We decided on a topic after hard consideration.
2. Then we began researching for our review of literature.
3. When all the information was collected we wrote our review
of literature.
4. After that, we put together our bibliography.
5. We then composed our hypothesis.
6. When we finished that we worked on our methodology, stating:
a. Collect materials.
b. Take 1 strip of carpet.
c. Pour 10 ml. of grape juice into a measuring cup.
d. Press cup into carpet labeled "vinegar" and hold down
for 5 seconds.
e. Let go, measure diameter at the smallest point of the
shape, and record.
f. Pour 10 ml. of vinegar into a measuring cup.
g. Press cup onto grape juice stain for 5 seconds.
h. Let go and dab with a paper towel for 5 seconds.
i. Measure the shape's diameter at its smallest point and
record.
j. Subtract the new shape's diameter from the old shape's
diameter to find how much the stain's size decreased.
k. Do this 2 more times on the same strip of carpet.
l. Find the average of the difference between the new and
old diameters.
m. Repeat steps 8-18 with tap water, liquid soap,
vegetable oil, club soda, ammonia, and milk, making sure
that when these liquids are poured, they're poured on a
carpet labeled with the same name.
7. After writing our methodology, we identified our variables.
8. Later, we figured out what we needed and wrote our list of
materials.
9. Then we performed our experiment and put together a data
collection form.
10. Using the data collection form, we wrote our analysis of
data.
11. After looking through our data, we composed our summary and
conclusion.
12. Our final step was to apply our findings to the world
outside the classroom.
Our responding variable was how well the different liquids
decreased the size of the stains. Our variables held constant
were that 10 ml. were always poured in the measuring cup, the
measuring cup was always held on the carpet for 5 seconds, the
diameter of the stain was always measured at its smallest point,
the paper towel was always dabbed for 5 seconds, the pre and
post diameters were always subtracted to find how much the stain
size decreased, and averages were always found. Our manipulated
variable was the different liquids.
Materials needed for the experiment include 21 ml. of grape
juice, 30 ml. of vinegar, 30 ml. of tap water, 30 ml. of liquid
soap, 30 ml. of vegetable oil, 30 ml. of club soda, 30 ml. of
ammonia, 30 ml. of milk, carpet, a measuring cup, a pencil,
paper, and paper towels.
III. DATA COLLECTION FORM:
Vinegar
Diameter Diameter Of
|Of stain |New Stain |Difference|
|Trial 1| 1.5 in. | 1 in. | .50 in. |
|Trial 2| 1.5 in. | .3 in. | 1.20 in. |
|Trial 3| 1.5 in. | 0 in. | 1.50 in. |
| Average Difference | 1.06 in. |
Vegetable Oil
Diameter Diameter Of
|Of stain |New Stain |Difference|
|Trial 1| 1.5 in. | 1.25 in. | .25 in. |
|Trial 2| 1.5 in. | 1.25 in. | .25 in. |
|Trial 3| 1.5 in. | 1.5 in. | 0 in. |
| Average Difference | .16 in. |
Ammonia
Diameter Diameter Of
|Of stain |New Stain |Difference|
|Trial 1| 1.5 in. | 1 in. | .5 in. |
|Trial 2| 1.5 in. | 1.5 in. | 0 in. |
|Trial 3| 1.5 in. | .5 in. | 1 in. |
| Average Difference | .5 in. |
Liquid Soap
Diameter Diameter Of
|Of stain |New Stain |Difference|
|Trial 1| 1.5 in. | 1.5 in. | 0 |
|Trial 2| 1.5 in. | 1.5 in. | 0 |
|Trial 3| 1.5 in. | 1.5 in. | 0 |
| Average Difference | 0 |
Tap Water
Diameter Diameter Of
|Of stain |New Stain |Difference|
|Trial 1| 1.5 in. | .5 in. | 1 in. |
|Trial 2| 1.5 in. | .1 in. | 1.4 in. |
|Trial 3| 1.5 in. | 0 in. | 1.5 in. |
| Average Difference | 1.3 in. |
Milk
Diameter Diameter Of
|Of stain |New Stain |Difference|
|Trial 1| 1.5 in. | .25 in. | 1.25 in. |
|Trial 2| 1.5 in. | .25 in. | 1.25 in. |
|Trial 3| 1.5 in. | .1 in. | 1.4 in. |
| Average Difference | 1.3 in. |
Club Soda
Diameter Diameter Of
|Of stain |New Stain |Difference|
|Trial 1| 1.5 in. | 0 in. | 1.5 in. |
|Trial 2| 1.5 in. | 0 in. | 1.5 in. |
|Trial 3| 1.5 in. | 0 in. | 1.5 in. |
| Average Difference | 1.5 in. |
IX. ANALYSIS OF DATA:
The average length that the diameter of a grape juice stain
decreased for vinegar was 1.06 inches. The average
decrease with vegetable oil was .16 inches. The average
decrease with ammonia was .5 inches. The average decrease with
liquid soap was 0 inches. The average decrease with tap water
was 1.3 inches. The average decrease with milk was 1.3 inches.
The average decrease with club soda was 1.5 inches.
X. SUMMARY AND CONCLUSION:
We accept our hypothesis that club soda will remove a stain the
best. Liquid soap, in last place, didn't even remove the stain.
We think that the carbonation in the club soda caused the stain
to disappear so quickly.
XI. APPLICATION:
This experiment applies to the real world because if grape
juice was spilled on a carpet, the person cleaning it up would
need to use club soda.
TITLE: The Effect Of A Mild Acid On Colored Chaulk
STUDENT RESEARCHER: David Nolan
SCHOOL: Urbandale Middle School
Urbandale, Iowa
GRADE: 6
TEACHER: Carmen Crump
I. STATEMENT OF PURPOSE AND HYPOTHESIS
The purpose of this project was to see if brand, color, and
density affect how quickly chalk dissolves in vinegar. My
hypothesis stated that the less dense chalk is, the quicker it
would dissolve. Do different colors of the same brand affect
outcome because some brands make chalk differently than others?
I thought the darker chalk would be more dense.
II. METHODOLOGY
I used 1 gallon of vinegar, 2 brands of colored and white chalk,
1 liquid measuring cup, 1 timer, an area of constant
temperature, a gram scale, a thermometer, 1 pair of rubber
gloves, and a sharp knife.
My procedure included the following steps:
1. Put on the rubber gloves.
2. Take two brands of chalk in red, blue, and white and weigh
them in grams.
3. Cut the chalk pieces into 5.5 grams each.
4. Pour 1 cup of vinegar into a measuring glass.
5. Take the vinegar's temperature and record it.
6. Drop the chalk gently into the vinegar. Record the time it
takes for the chalk to dissolve (in seconds).
7. If the chalk does not dissolve, record what happens and how
long the chalk remained in the vinegar.
8. Chart or graph the data.
Variables, controllable: quantity of vinegar, weight from brand
to brand of the chalk, size of the chalk within a brand, method
of chalk insertion into vinegar, acidity of vinegar in brand,
minimizing skin oil contact with chalk, and shape of chalk
within brand.
Variables, uncontrollable: Humidity, density of color in chalk,
crumble factor of chalk when cutting, density of each chalk
piece, imperfect cylindrical shape of chalk due to
manufacturing, shipping, and handling.
III. ANALYSIS OF DATA
DENSITY:
The data showed that Crayola chalk varied more in density. It
ranged from .0029 to .0034 compared to Mead's .0029 to .0030
scale of density.
COLOR:
The data showed density in colors of chalk varied. Density
didn't favor darker/lighter colors. Blue within Mead took
longer to react than Mead red and Mead white. Red and blue in
Crayola had the closest reaction time compared to white Crayola
reaction time. White in Crayola dissolved and took about 18
times longer than any others to show a chemical reaction.
BRAND:
When mass, volume, and temperature of vinegar are controlled and
two brands of chalk (Crayola and Mead) are dissolved in vinegar,
Crayola dissolves while Mead only bubbles. White Crayola was
the only piece of chalk to dissolve. All other colors of both
brands just bubbled.
IV. SUMMARY AND CONCLUSION
I researched how long it would take for chalk to dissolve in
vinegar, depending on color, brand, and density. My hypothesis
was the less dense the chalk, the quicker to dissolve; colors in
one brand would make a difference; and darker chalk was denser.
I took three colors of chalk from two brands, dissolved them in
vinegar, and recorded the results. The only brand that
dissolved was Crayola White, but others bubbled from four to ten
minutes. Crayola had a wider horizon of density than Mead. The
density in colored chalk varied, but didn't favor lighter/darker
colors. Mead blue took longer to react than Mead red or white.
Density of chalk doesn't favor darker/lighter colors, nor how
quickly it dissolves in vinegar. Color affects how quickly
chalk dissolves in vinegar, depending on how heavy the dye is.
White Mead chalk didn't dissolve because it had protective
agents that gave it a yellowish tinge. I think that the less
dye there is in chalk, the more it dissolves. Chalk density
varies because of ingredients in chalk, not because of color
darkness.
V. APPLICATION
This research would be a real help to street chalk artists.
Rain is often acidic (like vinegar) so I'd recommend using
Crayola colored chalk and Mead white because they dissolved
least in vinegar. Artists could use Mead colored chalk, too.
Crayola colored chalk has richer color and would be more visible
after a rainstorm.
TITLE: How Well Can Boys and Girls Identify Fruits By Taste
Alone?
STUDENT RESEARCHERS: Amber Williams and Francesca Lee
SCHOOL: Mandeville Middle School
Mandeville, Louisiana
GRADE: 6
TEACHER: Tammy Gendusa
I. STATEMENT OF PURPOSE AND HYPOTHESIS:
We would like to do a scientific research project on how well
the two genders (boys/girls) can identify fruits by taste. We
hypothesize that girls would be better able to identify the
fruit by taste because they would be able to tell the acid level
in each fruit.
II. METHODOLOGY:
1) We decided on a topic.
2) We wrote a statement of purpose.
3) We researched the topic we picked and wrote a review of
literature.
4) We wrote our methodology to test our hypothesis. We had
four boys and four girls taste a piece of the fruit while
blind-folded. They were to identify the fruit. We recorded
their responses. We also tested the pH of the fruit juices
with litmus paper to see which one had the highest acidity.
5) We then gathered our data and conducted our analysis of
data.
6) We wrote a summary and conclusion.
7) Last, we wrote our application.
The variables held constant were the litmus paper, genders used,
and the fruit type. Our responding variable was the acid level
of the fruits and how well the boys and girls could tell the
fruits apart. Our manipulated variables were the different
type of citrus fruit used the fact that there are boys and girls
in the study.
III. DATA COLLECTION FORM:
Percent of Boys and Girls Correctly Identifying Fruit
Grapefruit Lemon Orange
Boys: 75 % 100 % 75 %
Girls: 100 % 100 % 100 %
IV. ANALYSIS OF DATA:
In this project we found that girls are able to identify the
fruits by taste alone better than boys. Also the lemon had a
higher acid level than the other fruit.
V. SUMMARY AND CONCLUSION:
We found that the more sour the fruit is, the higher the level
of acid. We also noticed that girls had a better ability to
identify the fruit by taste.
VI. APPLICATION:
This experiment helped us understand what fruits have more of an
acid level. It also helped us to realize that girls are able to
tell which fruit is which better than boys.