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This page gives activities
and resources for collecting experimental data and comparing it with computer
models of that data derived from scientific theories.
- introduction
- structure
of the activities
- cooling
curves
- simple harmonic
motion
- reaction
of acid and marble
- reaction
of acid and alkali
- motion
sensor/timer
- sound
map
- background
books and datalogging links
Introduction
The activities below
are designed to meet three objectives:
- to give you sufficient
familiarity with the hardware used for datalogging for you to
feel confident to use it on your own
- to give you sufficient
familiarity with the software used for datalogging for you to
know which features to use for a given purpose
- to give you an
understanding of the ways in which datalogging and modelling can be
used to develop pupils' IT capability.
These activities
can be used with any interface but were designed to demonstrated features
of two interface boxes - the DL plus
from Philip Harris and the
EcoLog
from Data Harvest. Whatever
interface you use, you need to spend time exploring its features so that
you can meet the first objective.
In additiona to a
box to link your computer with the sensors which measure the data, you
need software to display and help the interpretation of that data. Again,
two products were in mind when these activities were devised - DataDisc
Pro from Philip Harris
and Insight
from Logotron. If other software packages
are used it may be necessary to export your data to a spreadsheet in order
to do the modelling activities.
Two additional points:
- The Philip Harris
site also contains details
of a new, cheaper datalogging system which I have not yet had the chance
to use
- Other people have
uses the 'Sense
and Control' datalogging system.
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Structure
of the activities
- Each of the activities
has the same four-part structure:
- What the science
says - this is a brief overview of the scientific ideas behing
- Capturing the
data - this lists questions you will need to consider when planning
your data collection
- Modelling the
data - this lists questions you will need to consider when comparing
the captured data with the scientific model
- Extensions - this
gives some possible extensions for each of the experiments.
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Cooling
Curves
What science says
- The scientific
model (Stefan's Law) says that the rate at which a black body cools
by radiation is proportional to the temperature.
- Rate of cooling
= C.T^4
- Where:
- T is the difference
between the temperature of the object and that of the surroundings and
- C is a constant
which depends on the substance
Capturing the data
- What temperatures
do you need to measure?
- Over what period
of time?
- What assumptions
are you making in taking these measurements?
- What shape do
you expect the cooling curve to have?
Modelling the data
- What variable
will you use for your model?
- What variable(s)
will you empirically adjust?
- Why might the
model not fit your data?
Extensions
- What might you
(or children) expect to affect the rate of cooling that does not appear
in the model?
- How could you
test whether this/these variables really do have no effect?
- Use the model
to make a prediction - then test this empirically.
- What would you
expect the effect of using 'forced cooling' (i.e. a fan) to have?
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Simple
Harmonic Motion
What science says
- The scientific
model says that the time taken for one oscillation of the spring is
dependent only on the mass of the spring and its 'springiness'. The
heavier the mass, the longer the time.
- Time for one oscillation
= 2pi.SQRT (M/k)
- Where:
- M is the mass
- K is a constant
that depends on the 'springiness' of the spring.
Capturing the data
- How will you accurately
measure the time of one oscillation?
- How will you measure
the mass?
- What assumptions
are you making in taking these measurements?
- What shape do
you expect the displacement/time curve to have?
Modelling the data
- What variable
will you use for your model?
- What variable(s)
will you empirically adjust?
- Why might the
model not fit your data?
Extensions
- What might you
(or children) expect to affect the time for an oscillation that does
not appear in the model?
- How could you
test whether this/these variables really do have no effect?
- Use the model
to make a prediction - then test this empirically.
- Return
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Reaction
of Acid and Marble
What science says
- The scientific
model says that the time rate at which the acid and marble react depends
only on the concentration of the acid, the temperature, and the surface
area of the marble (how 'broken up' it is).
- The greater the
concentration, the temperature and the surface area the faster the reaction.
The rate is linearly dependent on the concentration and surface area
and exponentially dependent on the temperature. At a fixed temperature
- Rate of reaction
= k.(Surface area).[Acid]^x.
- Where:
- k is the rate
constant that depends on the reaction and the temperature
- [Acid]
is the concentration of the acid
- x is a constant
- usually a small (1,2) whole number
Capturing the data
- How will you accurately
measure the rate of reaction?
- How will you measure
the concentration?
- What assumptions
are you making in taking these measurements?
- What shape do
you expect the mass/time and/or volume of gas/time curves to have?
Modelling the data
- What variable
will you use for your model?
- What variable(s)
will you empirically adjust?
- Why might the
model not fit your data?
Extensions
- What might you
(or children) expect to affect the rate of reaction that does not appear
in the model?
- How could you
test whether this/these variables really do have no effect?
- Use the model
to make a prediction - then test this empirically.
- Return
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Reaction
of Acid and Alkali
What science says
- The scientific
model says that the pH of the mixture is logarithmically related to
the concentration of hydrogen ions in the solution
- pH = -log[H+]
- and that for strong
(not concentrated) acids and alkalis the only reaction that matters
is that between the acid and the alkali
- Acid + Alkali
= Salt + Water
- However, for weak
acids and alkalis the picture is much more complicated and one gets
a quartic equation for [H+] which is best solved iteratively
(See the section ''Exploratory Examples' here
for details).
Capturing the data
- How will you measure
the pH?
- How will you measure
the volume of acid/alkali added?
- What assumptions
are you making in taking these measurements?
- What shape do
you expect curves of pH against volume of acid added and [H+]
against volume of acid added to have for combinations of strong and
weak acids and bases?
Modelling the data
For the strong
acid/strong base reaction
- What variable
will you use for your model?
- What variable(s)
will you empirically adjust?
- Why might the
model not fit your data?
For the weak
acid/weak base reaction
- Explore the given
simulation and think why it might not fit the data
Extensions
- What might you
(or children) expect to affect the reaction that does not appear in
the model? (Or not to affect the reaction which does appear
in the model)
- How could you
test whether this/these variables really do have no effect?
- Use the model
to make a prediction - then test this empirically.
- Return
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Motion
Sensor/Timer
What science says
- If 's' is used
to stand for distance and 't' for time then:
- velocity (v) =
ds/dt
- acceleration (a)
= d2s/dt2 = dv/dt
- Hence - when starting
from zero velocity - the distance and acceleration are related by:
- s = 1/2(a.t2)
- (Check that you
understand why this equation follows from the ones above.)
Capturing the data
Timing
- What data can
you actually measure using the equipment?
- How can/does the
machine transform this to the variables you may wish to use?
Motion sensor
- What data can
you actually measure using the equipment?
- How can/does the
machine transform this to the variables you may wish to use?
Modelling the data
Motion sensor
- It is often hard
for children to appreciate what constant velocity and/or acceleration
feel like. This experiment is designed to help you try to recreate the
model by physical action. Move your hand/yourself to make graphs of
constant velocity and acceleration (both positive - speeding up - and
negative - slowing down) appear on the screen.
Timing
- Does the data
fit the model? What aspects of the equipment are designed to help this
fit be as close as possible?
Extensions
Motion sensor
- Are the graphs
what you expect? Try recreating more complex motion curves.
Timing
- Try dropping a
ball through the two sensors arranged vertically. how can you use this
to measure the acceleration due to gravity?
- Devise a way of
using the sensors to measure reaction rates of individuals.
- Use the model
to make a prediction - then test this empirically.
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Sound
map - extension to other tasks
What to do
- Construct a 'sound
map' of the outside of the Institute and provide an explanation of the
data you get.
- It would be best
to draw a map of the Institute before you start and use it to predict
the relative (and possibly absolute?) Levels of sound you will find.
Capturing the data
- Where should you
take measurements?
- Over what time
period?
- Which of the values
will you use?
- What other data
do you need?
Modelling the data
- As this is an
extension activity, it is your task to devise and then use a method
of modelling these data.
Extensions
- Again - here it
is for you to devise and then try out an extension activity to this
task.
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Books
and Links
Two books of ideas
on data logging in science are:
- The IT in
Science Book of Data Logging and Control
- Data Logging in
Practice
Both are by Roger
Frost and both are published by the ASE. He also has a website
with more tips.
A brief survey of
the research in this area can be found in Roy Barton's paper
'Does data
logging change the nature of children's thinking in experimental work
in science?'
This is chapter 5
(pp 66-72) of Bridget Somekh's book
'Using information
technology effectively in teaching and learning'
published by Routledge
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This page is
maintained by Tim Brosnan. Please send any comments to:
t.brosnan@ioe.ac.uk.
- Last updated
on 18th July 2000
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