AS Science In Society 1.3
Teacher Notes
Introduction
This activity gives students direct practical experience of some of
the issues involved in collecting and analysing data on air
pollution. It is designed to be run over two sessions. In the first
session students will make their dust collectors and decide
where to place them, and in the second session they will collect
and analyse their data.
Resources
Session 1:
 Acetate sheet printed with 2mm graph paper grid - cut into
small squares (about 2x2cm)*
 Permanent marker pens for acetate
 Double sided sticky tape
 Small plastic bag to put dust collector in (optional)
 Map of local area (either printed out or displayed on
whiteboard/OHP)
Session 2
 Data analysis worksheet
 Microscopes (or hand lenses if not available)
OR

Worksheet Ulgham data
The activity
Activity 1
Ask students to discuss, in pairs or small groups, how they would
measure the air pollution in their local area. Use prompt
questions such as:
 Will different areas give different readings? What sort of
places might they take measurements at?
 Will measurements vary with the weather? With time of
day?
 How could they minimise random errors?
Activity 2
Explain to students that they are going to be measuring dust in
the air at different places. You could choose to measure around
the school site, or ask students to measure in different places
around the local area.
How Science Works
Aa We can never be sure that an
observation is accurate or that a
measurement tells us the ‘true’ value of the
quantity we are measuring. We may be
influenced by what we expect. Random
and/or systematic errors can arise from
limitations of the measuring equipment
used, or our skill in using it. A single
measurement of anything is therefore
inherently risky.
Ab If we make repeat measurements of the
same quantity, the values are likely to vary.
This might be because the quantity we are
measuring is changing, or because of
measurement error. If errors are random,
the average of several measurements is the
best estimate of the value of the quantity.
The smaller the spread of the measured
values and the larger the number of repeat
measurements, the more confident we can
be that the mean is close to the ‘true’ value.
Ad A set of repeat measurements can be
summarised by stating an average value
and an indication of the spread of values.
Useful visual representations are error bars
on graph points, and box-and-whisker plots.
Ae To judge if there has really been a
change in the value of a quantity, we need
to take account of both the difference in the
mean values and the spread of repeat
measurements. It is hard to detect a small
change in the mean value of a quantity
when the range of values in the data set is
greater than the change being detected.
Ag Data can be presented and analysed in
a variety of formats including graphs with
linear scales.
Ah If a measurement is much smaller or
larger than the others in a set of repeats, or
lies well off a graph line that the others are
close to, this may indicate that it is incorrect
and should be repeated (if this is possible)
or discarded (if it is not).
* Graph paper is a pdf file of graph paper that you can use to print onto printer appropriate acetate.
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AS Science In Society 1.3
Teacher Notes
Students should assemble their dust collector. On the acetate they will mark a 5 x 5 square, and stick a
piece of double sided sticky tape over this area – taking care not to remove both sides of the tape. Place
in plastic bag to avoid contamination.
As a group decide where the collectors are going to be placed. You could choose different areas of the
school site, or around the local area near students’ homes.
Discuss
 where to put them,
 should they all be the same distance above the ground
 should they be sheltered
 how to deal with rain/ adverse weather.
 how long to leave them exposed to the air.
This activity works best if there is no rain! Students may need to use sticky tac to keep the detectors
from blowing away.
Ask students to predict where they think will be the most and least dusty places – mark on the map,
along with the collection points they have chosen.
Students should then take the collectors home, site them as agreed in class and collect dust for the
appropriate amount of time. They should then cover the collector with a piece of normal sticky tape and
bring back to the next class.
Activity 3
Students now need to obtain data from their dust collector. Using the data analysis worksheet they will
use the microscope to count dust particles on each square of their dust collector. They will collate
results from the group to produce a graph which shows the number of dust particles at different
locations.
You should use this as an opportunity to discuss the nature of data with the students
 Why did they have to cover the dust collector with normal sticky tape?
 Were there any outliers?
 Why is it helpful to know both the mean and the range of the data?
 Have they measured the ‘true’ value of dust in the area?
 Would their results change if the weather had been different?
 Is the range of values in the data set greater than the difference in dust levels? What does that
mean for any conclusions they can draw?
Ask them to look at the prediction made as a class earlier – does their data support the prediction? Can
they explain what they have found?
Alternative activity
If it is difficult for students to produce and collect the data, then you can use the alternative worksheet
“Ulgham data” which gives dust collection samples for a fictional village to allow students practice in
analysing the dust data.
January 2008
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AS Science In Society 1.3
Student Sheets
Introduction
In order to investigate links between health and air quality we need to be able to obtain accurate
measurements of different air pollutants in different places. This activity will allow you to collect your
own data on dust levels in your local area. You will then analyse the data you and other members of the
class have collected.
Making your dust collector.
1. You will be given a small square of acetate which has a grid on it.
2. Using marker pens draw round a 5x5 square as shown. This is your
collecting area.
3. Place a small square of double sided sticky tape over the square.
4. DO NOT remove both sides of the covering.
5. Put your collector in a small plastic bag (if you have been given one).
As a class you will discuss where to place the collectors, how to ensure that you carry out a ‘fair test’,
and how long to collect dust for.
6. Place your collector in your agreed position. You may need to use sticky tac to stop it blowing
away. Remove the covering from the double sided sticky tape
7. When your collector has been exposed for the appropriate amount of time, cover the collecting
area with a normal piece of sticky tape.
Prediction
One important part of carrying out science is making predictions about experiments. As a class you are
collect particulate pollution around your local area.
 Which area do you think will have the most dust?
 Which area do you think will have the least dust?
 Why?
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AS Science In Society 1.3
Student Sheets
Particle collection practical
Data Analysis Worksheet
1. Using a microscope (on low power) or a hand lens look closely at your dust collector. You should
see something similar to the diagram below.
We record this data on a grid like this:
2. Record the dust distribution on your dust collector in the grid below.
3. Calculate the mean number of dust particles in a small square.
Mean = total number of dust particles on collector
number of squares on collector
=
=
4. Work out the range of your data
Range = maximum value – minimum value =
5. In order to see whether your prediction from last session was correct you need to compare the
results from all of the class.
Make a table with the following columns, and collate the results.
Location of dust collector
Page 2
Mean number of dust
particles per small square
Range
©The Nuffield Foundation 2008
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AS Science In Society 1.3
Student Sheets
6. Plot the results on a graph showing the mean and the range of the data set.

Are there any outliers in the data set? If so, do you think that they are due to natural variation in
dust levels, or an error in the measurements?
Look back at your prediction from last lesson.

Does your graph back up your prediction?

Is there a real difference in the measurement of dust particles between the locations in your
study? How can you tell?
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AS Science In Society 1.3
Student Sheets
Particle collection practical
Alternative data analysis worksheet
Ulgham Data
A student places three dust collectors around a small village called Ulgham.
Position 1
On a bus stop by the main road into the village.
Position 2
In the play area in the local park.
Position 3
Placed on wall outside the student’s house in a quiet street in the village.

Which area do you think will show the most particulate pollution? Why?
The following diagrams show the samples that were obtained when the student examined the dust
collectors under a microscope.
Position 1
Position 2
Position 3
Record the number of dust particles on each dust collector in the grids below.
Position 1
Page 4
Position 2
Position 3
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Copies may be made for UK in schools and colleges
AS Science In Society 1.3
Student Sheets
7. Calculate the mean number of dust particles in a small square.
Mean = total number of dust particles on collector
number of squares on collector
8. Work out the range of your data
Range = maximum value – minimum value
9. In order to see whether your prediction from last session was correct you need to compare the
results from all of the class.
Make a table with the following columns, and collate the results.
Location of dust collector
Mean number of dust
particles per small square
Range
Position 1 – main road
Position 2 – play park
Position 3 – quiet road
10. Plot the results on a graph showing the mean and the range of the data set.

Are there any outliers in the data set? If so, do you think that they are due to natural variation in
dust levels, or an error in the measurements?

Does your graph back up your prediction?

Is there a real difference in the measurement of dust particles between the locations in your
study? How can you tell?
Page 5
©The Nuffield Foundation 2008
Copies may be made for UK in schools and colleges