Paper 3 Advanced Practical Skills | A Level Biology 9700

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🎯What you need to be able to do

Identify the independent and dependent variables and decide a suitable range, number of values and intervals.
Decide which variables to standardise, how to standardise them, and what control to use.
Assess the hazards of a procedure and judge the risk as low, medium or high.
Record raw and processed results in a table with descriptive headings and units, to an appropriate precision.
Display calculations clearly and use the correct number of significant figures.
Draw graphs, bar charts and histograms accurately, with correct axes, scales, plotting and lines.
Set up a light microscope, make plan diagrams and high-power drawings, and calculate actual sizes.
Interpret data, draw conclusions, identify systematic and random errors, and suggest improvements and extensions.

📚How the paper works

Paper 3 is a timetabled, laboratory-based practical test lasting 2 hours and worth 40 marks. It is 23% of the AS Level and 11.5% of the A Level, and it is assessed entirely on AO3 — experimental skills and investigations. Questions may be set in contexts outside the syllabus content: where the material or technique is unfamiliar, full instructions are given, because you are being marked on skill rather than recall.

The paper has two or three questions. One requires an investigation; another requires work with a light microscope. Centres provide microscopes for half the candidates at a time, so half the room starts on the investigation while the other half starts on the microscope, and you swap. Plan your time accordingly — you cannot go back to the microscope once you have handed it over. No dissection of animal material is required.

Marks are allocated across three skills:

Manipulation, measurement and observation — 15–17 marks. Decisions about measurements and observations, and the collection of data.
Presentation of data and observations — 11–13 marks. Recording, displaying calculations and reasoning, and the layout of tables and graphs.
Analysis, conclusions and evaluation — 11–13 marks. Interpreting, concluding, identifying sources of error and suggesting improvements.

Note where the weight lies. Nearly half the marks are for doing the practical properly, and about a quarter are for presenting what you did — before any biology is interpreted at all. Candidates who rush the table and the graph to reach the “real” questions are throwing away the most reliably earned marks on the paper.

🔬Making the decisions

Variables

Identify the independent variable (the one you change) and the dependent variable (the one you measure). Then decide:

a suitable range of values — wide enough to show the trend, and within what the material can tolerate;
the number of values — a minimum of five, which the syllabus states explicitly, and evenly spaced intervals across the range;
how you will change it, typically by serial or proportional dilution from a stock solution;
how you will measure the dependent variable, and how precisely;
the number of replicates at each value, so a mean can be calculated and anomalies identified;
the control — identical in every respect except that the factor under test is absent (distilled water instead of enzyme, boiled enzyme, glass beads instead of seeds);
which variables must be standardised, and how.

On that last point, the syllabus adds a useful qualification: variables expected to have a minimal effect — such as variation between test-tubes of the same type — do not need to be standardised. Listing them wastes time and dilutes an otherwise good answer.

Risk

You are expected to consider the hazards of the procedure — including any solutions and reagents — and to assess the risk as low, medium or high. A full answer names the hazard, the risk it presents, and the precaution: “hydrogen peroxide is an irritant; risk of eye damage if it splashes; wear eye protection and keep the tube pointed away from the face.” “Be careful” earns nothing.

📊Presenting the results

Tables

One table containing both raw and processed results, ruled with a border and lines between columns.
Descriptive headings with units in the heading and no units in the body of the table — write “time / s”, then bare numbers below.
The independent variable in the left-hand column (or the top row if the table runs in rows), with the dependent variable to its right.
Raw quantitative data recorded to the number of decimal places appropriate to the measuring instrument, and consistently — if a balance reads to 0.01 g, write 4.20 g, not 4.2 g.
Qualitative observations recorded as clear descriptions, not one-word colours: “blue-green with a fine orange precipitate” beats “green”.

Calculations and significant figures

Show every step and the reasoning, not just the answer. The rule for significant figures is stated in the syllabus and is worth learning verbatim: the correct number of significant figures for a calculated quantity is the same as, or one more than, the smallest number of significant figures in the data used in the calculation.

So a value calculated from data given to 3 s.f. and 2 s.f. should be quoted to 2 or 3 significant figures. Copying eight digits off a calculator is a lost mark; so is rounding to one.

Graphs

Choose the right form first: a line graph for continuous data, a bar chart for discontinuous or categoric data, a histogram for frequency data. Then:

independent variable on the x-axis, dependent on the y-axis;
axes labelled to match the table headings, including units;
a scale that uses most or all of the grid and can be read to within half a square — so use 1, 2, 5 or 10 units per square, never 3 or 7;
points plotted accurately with a sharp pencil as a small cross or a dot in a circle, with the intersection exactly on the point;
points joined by a clear, sharp, unbroken line — either a line of best fit, a smooth curve, or ruled straight lines between points, as the data warrant;
no extrapolation beyond the data unless it can be justified.

🔭Microscope work

Two kinds of drawing are marked differently, and confusing them is the fastest way to lose the marks:

Plan diagram — shows the distribution of tissues, with the layers in correct proportion and no individual cells drawn.
High-power drawing — a few cells showing correct shapes, correct relative sizes and proportions, cell walls drawn as two lines (three where two cells touch), and only observable contents. Do not add a nucleus you cannot see.

In both: sharp pencil, fine clear unbroken lines, no shading, use most of the available space, and label with ruled lines that touch the structure named.

You may also be asked to calculate actual sizes from a photomicrograph using a magnification, a scale bar, or a representation of an eyepiece graticule and stage micrometer — the calibration method set out in Topic 1 — and to estimate numbers of cells or organelles in an area by sampling, using grids or fields of view.

🔎Errors and improvements

Distinguish the two kinds of error, because the syllabus does:

a systematic error affects every reading in the same direction — an uncalibrated balance, a meniscus read consistently from above — so it shifts all the results but may not affect the trend;
a random error varies unpredictably between readings — reaction time, judging a colour change — so it scatters the points and may affect the trend. It is reduced by repeating and taking a mean.

An improvement must be specific and must address a named source of error:

standardise a variable more effectively — a thermostatically controlled water bath rather than a beaker of warm water;
measure the dependent variable more accurately — a colorimeter rather than the eye, a gas syringe rather than counting bubbles;
use smaller intervals for the independent variable, especially around a peak or an intercept;
take replicate measurements and calculate a mean.

An extension is different from an improvement: it answers a new question, by investigating a different independent variable or applying the method in a new context.

“Repeat the experiment” and “be more accurate” are not improvements. Neither names a source of error or says what would change. Every improvement should read as: this measurement was imprecise because X, so I would do Y instead. If your suggestion could be written before seeing the experiment, it is not worth a mark.

✏️Worked example

A student investigated the effect of temperature on the activity of amylase by timing how long a starch–amylase mixture took to stop giving a blue-black colour with iodine. Results: 20 °C, 180 s; 30 °C, 96 s; 40 °C, 55 s; 50 °C, 61 s; 60 °C, 300 s (no change observed by 300 s). (a) Explain how to convert these into a measure of rate, and to how many significant figures the rate at 40 °C should be quoted. (b) Describe how you would present these data graphically. (c) Identify one systematic and one random error in this method, and give a specific improvement for each.

(a) The time taken is inversely related to the rate: a shorter time means a faster reaction. Calculate rate as 1/time, in s⁻¹. At 40 °C:

\[ \text{rate} = \frac{1}{55} = 0.0182\ \text{s}^{-1} \]

The time was recorded to 2 significant figures (55 s), so the calculated rate should be quoted to 2 or 3 significant figures — 0.018 or 0.0182 s⁻¹. Writing 0.01818181 is wrong, and so is 0.02.

The 60 °C reading needs care. “No change by 300 s” is not a measurement of 300 s; it is a statement that the reaction did not finish within the time allowed. Record it as such, and either omit it from the rate calculation or plot it as a rate of at most 0.0033 s⁻¹ with a note.

(b) Temperature is continuous, so a line graph is correct — not a bar chart. Plot temperature (the independent variable) on the x-axis, labelled “temperature / °C”, and rate on the y-axis, labelled “rate / s⁻¹” — the same headings as the table. Choose scales in 1, 2 or 5 units per square so that the plotted points fill most of the grid and the graph can be read to within half a square. Plot each point accurately with a sharp pencil as a small cross, and join them with a smooth curve, since enzyme activity varies continuously with temperature and shows a peak. Do not extrapolate beyond 20 °C or 60 °C.

(c)

Systematic error: the mixture was assumed to be at the stated temperature, but the enzyme and starch were probably added at room temperature and took time to reach it, so every reading is longer than it should be, in the same direction. Improvement: equilibrate the starch and the enzyme separately in the water bath for five minutes before mixing, and use a thermostatically controlled water bath rather than a beaker.
Random error: the end point is judged by eye, and the exact moment at which the iodine stops going blue-black varies with the observer, the lighting and the size of the drop sampled — so readings scatter unpredictably. Improvement: use a colorimeter to fix the end point at a defined absorbance, and take three replicates at each temperature and calculate a mean.

Note that the interval of 10 °C is too coarse to locate the optimum, which lies somewhere between 40 and 50 °C. A further improvement is to take readings at 42, 44, 46 and 48 °C — smaller intervals around the peak.

Check it. Sanity-check the shape of the processed data before drawing anything: rate should rise to a maximum and then fall steeply, which is what enzyme kinetics predicts. Converting the times to rates gives 0.0056, 0.0104, 0.0182, 0.0164 and (at most) 0.0033 s⁻¹ — a rise, a peak near 40–50 °C and a collapse at 60 °C as the enzyme denatures. If your processed figures do not show that shape, check whether you divided time by 1 rather than 1 by time.

Plotting time instead of rate, and treating ‘300 s’ as data. A graph of time against temperature is upside down relative to the biology — it shows a minimum where the activity is greatest — and although not strictly wrong, it makes the conclusion harder to state and often loses the interpretation marks. And a reading recorded because the experiment was stopped, rather than because something happened, is a limit, not a measurement; plotting it as though the reaction took exactly 300 s asserts something the data do not show.

📝Practise

Work through these, then reveal the answer. Each question targets a different objective from the list above.

1. A student is asked to investigate the effect of sucrose concentration on the mass of potato tissue. State the independent and dependent variables, and describe how to produce five concentrations from a 1.0 mol dm⁻³ stock.

Independent variable: the concentration of the sucrose solution. Dependent variable: the change in mass of the potato tissue, expressed as a percentage of the initial mass so that cylinders of different starting masses can be compared. Proportional dilution to make 20 cm³ of each: for 1.0 mol dm⁻³ use 20 cm³ stock and 0 water; for 0.8, use 16 cm³ stock + 4 cm³ distilled water; for 0.6, 12 + 8; for 0.4, 8 + 12; for 0.2, 4 + 16. Add distilled water alone (0.0 mol dm⁻³) as the control. Measure volumes with a syringe or pipette rather than a measuring cylinder, and mix thoroughly. This gives five values plus a control at even intervals across the range, satisfying the minimum of five values the syllabus requires.

2. State the rule for significant figures in calculated quantities and apply it: a rate is calculated from a volume of 12.5 cm³ and a time of 40 s.

The rule: the number of significant figures in a calculated quantity should be the same as, or one more than, the smallest number of significant figures in the data used. Here the volume is given to 3 significant figures (12.5) and the time to 2 (40). The smallest is 2, so the answer should be quoted to 2 or 3 significant figures. Rate = 12.5 ÷ 40 = 0.3125 cm³ s⁻¹, so quote 0.31 or 0.313 cm³ s⁻¹. Writing 0.3125 claims a precision the data do not support; writing 0.3 discards precision that was earned. Remember to include the unit, derived correctly from cm³ divided by s.

3. Explain the difference between a plan diagram and a high-power drawing, and give two rules that apply to both.

A plan diagram shows the distribution of tissues in a specimen — the outline and correct relative proportions of each layer — with no individual cells drawn. Drawing cells into a plan diagram loses the mark. A high-power drawing shows a few individual cells in detail: correct shapes, correct relative sizes and proportions, cell walls drawn with two lines (three where two cells are in contact), and only the contents that can actually be observed. Rules applying to both: use a sharp pencil giving fine, clear, unbroken single lines with no shading; use most of the available space; and label with ruled lines that touch the structure being named, with labels written horizontally outside the drawing.

4. A student obtains these repeat readings at one concentration: 42, 44, 43, 68, 43 s. Identify the anomaly, explain how to deal with it, and calculate the mean you would use.

The reading of 68 s is anomalous: it lies far outside the cluster of the other four, which fall within a range of 2 s of each other, and there is no reason to expect such variation from a controlled procedure. It should be identified, ringed on the table and excluded from the mean, with a brief statement of why. It should not be silently deleted — anomalies are recorded and then discounted with a reason, because concealing them is dishonest and because a pattern of anomalies is itself informative. Mean of the remaining four: (42 + 44 + 43 + 43) ÷ 4 = 43 s. If time allowed, the correct response is to repeat that reading to see whether the anomaly recurs. Possible causes worth suggesting: a timing error, a tube not properly equilibrated, or contamination of that tube.

5. A colorimeter is suggested as an improvement to an experiment in which a colour change is judged by eye. Explain precisely why it improves the results.

Judging a colour change by eye is a subjective measurement: different observers, and the same observer under different lighting or at different points in the experiment, place the end point at slightly different moments. This is a random error, so it scatters the readings unpredictably and can obscure the trend. A colorimeter measures the absorbance of light of a chosen wavelength passing through the sample, giving a numerical value. The end point can then be defined objectively as a fixed absorbance, identical for every tube and every repeat, so the same criterion is applied every time. It is also more sensitive than the eye, detecting changes too small to see, and it produces continuous quantitative data that can be plotted against time to give a rate rather than a single end-point time. The improvement is therefore in both reliability (less scatter) and precision.

6. Distinguish between an improvement and an extension, giving one example of each for an investigation into the effect of light intensity on the rate of photosynthesis in pondweed.

An improvement increases the accuracy or reliability of the existing investigation, by addressing a source of error in what was already done. Example: replace counting bubbles, which is imprecise because bubbles vary in size and may be missed, with collecting the gas in a syringe and measuring its volume over a fixed time; or insert a heat shield of water between the lamp and the plant so that moving the lamp does not also change the temperature, which would otherwise be an uncontrolled variable. An extension answers a new question, by investigating a different independent variable or applying the method in a different context. Example: investigate the effect of light wavelength by using coloured filters at constant intensity, to see whether the action spectrum matches the absorption spectrum of the pigments; or investigate the effect of hydrogencarbonate concentration to test whether carbon dioxide is limiting. Both are credited, but a question asking for an improvement is not answered by an extension.

🔗Go deeper — other people’s work

These are external resources, not mine. If one stops working, tell me and everything above it on this page still stands.

Cambridge International specimen Paper 3 and its mark scheme — the fastest way to see how the three skill areas are actually awarded
Cambridge International, “How to manage your science practical exams” — written for centres, but it explains the confidential instructions, the supervisor’s report and why your paper may differ from another school’s
Nuffield Foundation practical biology — standard protocols for most of the techniques the paper draws on, with the controls and precautions spelt out