Biology 9700/33 — May/June 2024

Background Concept

Sedimentation is the gravitational settling of particles suspended in a liquid. The yeast cells in a suspension are denser than the surrounding medium, so over time they sink to the bottom of the container, leaving clearer liquid above. A key point is that the total volume of liquid is conserved during sedimentation — only the distribution of the cells within it changes.

Understanding the Question

Test-tube R shows the starting condition: a uniform yeast cell suspension filling the lower part of the tube. The question asks you to predict and draw what test-tube S will look like after sedimentation has occurred, and to label the sediment. The two test-tubes are drawn side by side at the same scale, so any height comparison is direct.

Approach

The critical idea is volume conservation. Because the cells and the liquid they sit in occupy the same total volume whether the cells are suspended or settled, the top of the liquid in S must be at exactly the same height as the top of the liquid in R. The cells, however, will no longer be evenly distributed — they will have accumulated at the bottom, leaving clearer liquid above. So you need two lines: one at the top (matching R) and one part-way up marking where the sediment begins.

Step-by-Step Reasoning

1. Upper line: the level of liquid in S is the same as in R, so draw a horizontal line at exactly the height of the upper line shown in R.
2. Sediment line: the cells have settled to the bottom, forming a sediment layer. Draw a second horizontal line part-way up the tube, marking the top of this sediment.
3. Label: draw a label line from the bottom (denser) section to outside the test-tube, and write the word sediment at the end of the line.
4. The region between the two lines represents clearer liquid above the sediment; the region below the lower line represents the sediment itself.

Key Takeaways

• The total volume of liquid is conserved during sedimentation.
• A sedimented suspension shows two distinct regions: a sediment layer at the bottom and clearer liquid above.
• The height of the sediment is the dependent variable measured in this experiment.

Common Mistakes

• Drawing the upper line at a different height from R (forgetting that the liquid volume is unchanged).
• Drawing the sediment line too high (leaving little clear liquid) or too low (filling most of the tube with sediment).
• Failing to label the sediment, or labelling the clear liquid above instead.
• Drawing the sediment as a single line at the very bottom rather than as a layer with a defined top.

Things to Be Careful About

• The upper line on S must be at the same height as the top of the liquid in R — this is the key mark.
• The label line should point to the sediment, not to the clear liquid above.
• The label should be the word sediment — not 'yeast', 'cells' or 'pellet'.

Background Concept

Proportional dilution is the standard way of preparing a solution of a desired concentration from a more concentrated stock. The principle is:

For a 100 % stock of ethanol, this simplifies to $V_{\text{E}} = \dfrac{C}{100} \times V_{\text{final}}$, and the remainder of the final volume is made up with the diluent (here, distilled water W).

Understanding the Question

You must complete Table 1.2 to show how you will prepare the additional concentrations of ethanol you will use in the investigation. The two given rows (100 % and 60 %) demonstrate the proportional-dilution pattern; you must add three more rows in between, giving correct volumes of E and W that total 10 cm³ for each concentration.

Approach

Choose three intermediate concentrations that span the 60–100 % range in useful steps (e.g. 70, 80, 90 %). For each, calculate $V_{\text{E}} = \dfrac{C}{100} \times 10.0$ and $V_{\text{W}} = 10.0 - V_{\text{E}}$. Check that every row sums to 10.0 cm³.

Step-by-Step Reasoning

• 90 %: $V_{\text{E}} = \dfrac{90}{100} \times 10.0 = 9.0$ cm³, so $V_{\text{W}} = 10.0 - 9.0 = 1.0$ cm³.
• 80 %: $V_{\text{E}} = \dfrac{80}{100} \times 10.0 = 8.0$ cm³, so $V_{\text{W}} = 10.0 - 8.0 = 2.0$ cm³.
• 70 %: $V_{\text{E}} = \dfrac{70}{100} \times 10.0 = 7.0$ cm³, so $V_{\text{W}} = 10.0 - 7.0 = 3.0$ cm³.
• Each row sums to 10.0 cm³ ✓.

Key Takeaways

• Proportional dilution uses $V_{\text{E}} = \dfrac{C}{100} \times V_{\text{total}}$ and $V_{\text{W}} = V_{\text{total}} - V_{\text{E}}$.
• The chosen concentrations should give a useful spread across the 60–100 % range so that any trend is detectable.
• The control (C) is set up separately in step 5 and is not entered in this dilution table.

Common Mistakes

• Volumes that do not sum to 10.0 cm³ (e.g. writing 9 cm³ E + 0.5 cm³ W for 90 %).
• Choosing concentrations outside 60–100 % (e.g. 50 % or 0 %).
• Choosing concentrations that are too close together (e.g. 65, 66, 67 %) — too little range to reveal a trend.
• Forgetting the diluent entirely and recording only the volume of ethanol.

Things to Be Careful About

• The question requires three additional concentrations — not two, not four.
• Each row must sum to 10.0 cm³.
• The control tube C is set up in step 5 (water only) and is not part of the dilution table.

Background Concept

A results table in an experimental write-up must make it unambiguous what was measured, in what units, and at what intervals. Standard conventions include: a heading naming the independent variable (what was changed), a heading naming the dependent variable (what was measured) together with its unit, and a layout that lets the reader read off a value for any combination of conditions. The precision of the recorded values should match the resolution of the measuring instrument — here, a millimetre ruler, so whole millimetres.

Understanding the Question

You have carried out steps 1–15 of the method, measuring the height of the yeast sediment in each test-tube at 0, 4, 8, 12, 16 and 20 minutes. The question asks you to record these results in an appropriate table. The marks are awarded for the table's conventions (headings, units, completeness, precision) rather than for any particular numerical value, since the actual readings are student-dependent.

Approach

Design the table so that:

• the independent variable (concentration of ethanol) labels the rows, with the control C included as 0 %;
• the dependent variable (height of sediment in mm) is the column heading, with the time sub-headings (0, 4, 8, 12, 16, 20 min) underneath;
• every cell contains a height in whole millimetres (because the ruler has 1 mm divisions);
• the value at t = 0 is 0 mm in every tube (sedimentation has not yet started).

Step-by-Step Reasoning

1. The independent variable is the concentration of ethanol, so the rows are: 0 (C), 60, 70, 80, 90, 100 %.
2. The dependent variable is the height of the sediment; the unit is mm. The time points 0, 4, 8, 12, 16, 20 min are the sub-columns.
3. At 0 min the sediment has not yet formed, so the height is 0 mm in every tube.
4. At each subsequent time point, read the height of the sediment from the side of the test-tube against the mm ruler, and record the nearest whole millimetre.
5. The data in this representative set show a trend: moderate ethanol concentrations (around 70 %) give the greatest sedimentation, and very high concentrations (100 %) give almost none.

Key Takeaways

• Every results table needs headings that name both the quantity and the unit.
• The independent and dependent variables must each be clearly identified.
• All readings (here, one per tube per time point) should be included, and the precision used should be consistent (whole mm here, because of the ruler's resolution).
• A reading of 0 at t = 0 is correct and is expected.

Common Mistakes

• Omitting the control C from the table — the mark scheme requires its height to be recorded.
• Writing heights with decimals (e.g. 5.5 mm) when only whole mm can be read from the ruler.
• Putting the unit only at the top of a column instead of in the heading (the convention is to include the unit in the heading itself, e.g. height of sediment / mm).
• Forgetting to record the value at 0 min (the mark scheme explicitly requires this).
• Laying the table out with time as rows and concentration as columns, making it harder to compare concentrations at a glance.

Things to Be Careful About

• The 0 % row is the control C and must be included.
• Heights must be in whole millimetres; decimals are rejected.
• Headings must specify the quantity and the unit.
• The 0-minute reading is a baseline and should be 0 mm in every tube.

Background Concept

A conclusion is a short statement describing the relationship between the independent and dependent variables, based on the candidate's own data. It is not a generic textbook statement — it must reflect the trend actually seen in the recorded results, and it must mention both the variable that was changed (concentration of ethanol) and the variable that was measured (height of the sediment).

Understanding the Question

Having recorded the height of the sediment at each concentration and time point, you must write one conclusion about how the concentration of ethanol affects sedimentation. The mark is for a statement that explicitly mentions both the concentration of ethanol and the height of sedimentation, and that follows the data.

Approach

Look at the column of values at 20 min and describe how the height changes as concentration increases. If the data show a peak at an intermediate concentration, say so; if they show a monotonic increase or decrease, describe the direction of change.

Step-by-Step Reasoning

1. Read the heights at 20 min: 0 % → 13 mm, 60 % → 19 mm, 70 % → 21 mm, 80 % → 16 mm, 90 % → 8 mm, 100 % → 3 mm.
2. As concentration rises from 0 % to 70 %, the height increases; above 70 %, the height falls.
3. The conclusion therefore links concentration to height and reports this non-monotonic trend.

Key Takeaways

• A conclusion must name the independent variable and the dependent variable explicitly.
• A conclusion should be supported by the data, not by textbook generalisations.
• The question asks for one conclusion only.

Common Mistakes

• Saying 'ethanol affects sedimentation' without specifying how (direction, magnitude or any peak).
• Giving a textbook generalisation (e.g. 'high concentrations of ethanol kill yeast cells') rather than a conclusion based on the recorded heights.
• Failing to mention the dependent variable (height of sediment).

Things to Be Careful About

• The statement must mention both the concentration of ethanol and the height of sedimentation (the mark scheme requires this).
• 'Amount of ethanol' is too vague; use 'concentration of ethanol'.

Background Concept

A hypothesis is a testable statement. To evaluate it, the experiment must include a control that differs from the experimental groups only in the variable named in the hypothesis. Here, the hypothesis claims that ethanol is needed for sedimentation — so the control must be a tube without ethanol. That is exactly what test-tube C is: it contains 7 cm³ of water (no ethanol) plus yeast and calcium chloride.

Understanding the Question

The hypothesis is: 'ethanol is needed for sedimentation of yeast cells to occur.' You must decide whether your data support or reject this statement, and explain how the results provide the evidence.

Approach

Look at what happens in the control tube C. If C shows sedimentation, then ethanol cannot be 'needed' (because sedimentation occurs without it). If C shows no sedimentation, then ethanol could indeed be 'needed'. Use the data to decide, then explain using a specific result.

Step-by-Step Reasoning

1. Test-tube C contains 0 % ethanol (only water, calcium chloride and yeast).
2. In the recorded data, C shows a sediment height of 13 mm at 20 min — that is, sedimentation has occurred in the absence of ethanol.
3. Therefore, ethanol is not a requirement for sedimentation. The hypothesis is rejected.
4. Explanation: because sedimentation occurs in C (which has no ethanol), ethanol is not needed for sedimentation to take place.

Key Takeaways

• A control without the variable named in the hypothesis is the decisive test of that hypothesis.
• 'Support' or 'reject' must be justified by a specific reference to the data — here, the height recorded for C.
• The word 'needed' is the key: 'needed' means 'without it, the process cannot occur'. If the process occurs without it, the claim is false.

Common Mistakes

• Writing 'support' because 'ethanol increases sedimentation' — that is a different hypothesis from the one stated.
• Failing to mention the control tube in the explanation (the mark scheme requires the evidence to come from the results).
• Saying 'yes' or 'no' without explicitly using the words 'support' or 'reject'.
• Confusing 'rejection' of a hypothesis with rejection of the experimental method — they are different things.

Things to Be Careful About

• The decision must be stated explicitly (support or reject), not implied.
• The explanation must refer to specific results — typically the height in tube C — not to a vague statement that 'sedimentation happened'.

Background Concept

A common limitation of an investigation with widely spaced concentrations is that the optimum value can only be located to within the gap between two tested values. To find the optimum more accurately, you can (i) test values on both sides of the apparent optimum and (ii) reduce the spacing of the concentrations near it. Together these approaches 'zoom in' on the true peak.

Understanding the Question

The question has two parts. First, look at the 20-minute column of your table and state the concentration of ethanol that gave the greatest height of sediment. Second, suggest a modification of the procedure that would give a more accurate estimate of the concentration causing the most sedimentation.

Approach

• Part 1: read the 20-min column, find the largest value, and report the corresponding concentration.
• Part 2: think about how to refine the search. The marks are for (a) testing on either side of the stated concentration and (b) using narrower intervals close to it.

Step-by-Step Reasoning

1. At 20 min the heights are: 0 % → 13 mm, 60 % → 19 mm, 70 % → 21 mm, 80 % → 16 mm, 90 % → 8 mm, 100 % → 3 mm. The maximum is 21 mm at 70 %.
2. Modification 1 — test on either side of 70 %, e.g. additional concentrations at 65 % and 75 % (or any pair bracketing 70 %).
3. Modification 2 — use narrower intervals close to 70 % (e.g. 67, 68, 69, 70, 71, 72, 73 %) so the optimum is located more precisely.
4. The two modifications together 'home in' on the true optimum, giving a more accurate estimate.

Key Takeaways

• The optimum from a coarse investigation is only an estimate; refining the concentrations gives a more accurate value.
• Improvements should be specific to the limitation: here, the limitation is the gap between tested concentrations.
• Modifications to an investigation should be feasible in a school lab (i.e. achievable dilutions, sensible volumes).

Common Mistakes

• Stating a concentration that did not give the maximum in the student's own data — the mark requires the answer to come from the candidate's results.
• Suggesting only one of the two required modifications (either side, or narrower intervals).
• Suggesting vague improvements such as 'use more concentrations' without specifying that they should bracket the optimum and be closely spaced.
• Suggesting changes that do not address resolution, e.g. using a different type of yeast or a different temperature.

Things to Be Careful About

• The mark scheme requires both modifications: 'use concentrations of ethanol either side' and 'use narrower intervals close to' the optimum.
• The improvement should be a modification of the procedure, not a change of variable (e.g. do not change the yeast or the temperature).

Background Concept

A source of error in an experiment is anything that makes the recorded result differ from the 'true' value. Sources of error fall into two broad groups: systematic (every reading is shifted in the same direction by the same amount) and random (readings vary unpredictably). A flaw in the method itself — e.g. in timing, sampling or calibration — is also a source of error, and can usually be named and corrected.

Understanding the Question

You are asked to identify the main source of error in the procedure for measuring the height of yeast sediment at 4-minute intervals. The mark is for naming a specific flaw in the method, not a vague comment such as 'human error' or 'parallax'.

Approach

Re-read steps 13–15: the student measures the height of the sediment in each test-tube, one after another, then waits 4 min and repeats. Because the tubes are measured sequentially, they are not all at exactly 4 min, 8 min, etc. when measured — the first tube is measured close to 4 min, the last slightly later. This means the tubes are not being compared at exactly the same time after the start of sedimentation.

Step-by-Step Reasoning

1. Step 13 says: 'measure the height of the sediment in each test-tube. These are the results at the start (0 minutes).'
2. Step 14 says: 'After 4 minutes, measure the height of the sediment in each test-tube.'
3. But measuring each tube takes time, so the first tube is measured close to 4 min, while the last is measured later (perhaps at 4 min + several seconds or more).
4. The intervals between measurements are therefore not exactly 4 min in every tube.
5. This is the main procedural source of error: the tubes are not left for exactly the same length of time before being measured.

Key Takeaways

• Sources of error should be specific to the procedure and named, not described in general terms.
• Sequential measurement of multiple samples almost always introduces a small timing error.
• Improvements are usually obvious once the error is named: e.g. measure all tubes at exactly the same time using a multi-tube rack and a single ruler, or take a photograph at each time point.

Common Mistakes

• Vague answers such as 'human error', 'parallax error' (parallax when reading a ruler is real but is not the main error here) or 'not accurate' — these do not name a specific flaw in the method.
• Naming an irrelevant error, e.g. 'ethanol is flammable' (a safety issue, not a source of error in the data).
• Confusing 'source of error' with 'improvement': the question asks for the error, not the fix.

Things to Be Careful About

• The mark scheme gives 'the test-tubes were not left for the same length of time' as a model answer; a similarly specific procedural error is needed.
• The error should be the main one — i.e. the flaw that most affects the recorded data, not a minor cosmetic issue.

Background Concept

Systematic errors shift every reading in the same direction by the same amount (or by a consistent proportion). They arise from miscalibrated equipment, a consistent operator technique or a method bias. They do not change the shape of the trend, only the absolute values. Random errors vary unpredictably from reading to reading; they affect the spread (precision) of the data rather than the average. Whether an error affects the trend depends on whether it is consistent across all the readings being compared.

Understanding the Question

You are given a specific error: the 7 cm³ mark on the syringe actually delivers 7.1 cm³ (i.e. it is mis-marked by +0.1 cm³). You must (a) classify the error as systematic or random, and (b) state its effect on the trend in the results.

Approach

Ask two questions:

1. Is the error consistent (always +0.1 cm³) or does it vary randomly? If consistent, it is systematic.
2. Does the error affect every reading similarly? If yes, the trend — the pattern of how height changes with concentration — is preserved.

Step-by-Step Reasoning

1. The 7 cm³ mark on the syringe gives 7.1 cm³ every time it is used — the error is consistent, so it is systematic.
2. Every tube measured with this syringe receives 0.1 cm³ more ethanol than the volume stated in the method.
3. Because every tube is affected by the same small extra volume, the heights recorded are all shifted by a similar small amount. The differences between concentrations are essentially preserved.
4. Therefore, the error has no effect on the trend (the shape of the graph of height against concentration is unchanged); it only changes the absolute values slightly.

Key Takeaways

• A miscalibrated measuring instrument gives a systematic error.
• A systematic error that affects all readings equally does not change the trend — only the absolute values.
• A systematic error that affects some groups more than others would change the trend.
• A random error would increase the spread of readings and could obscure the trend if it were large.

Common Mistakes

• Classifying the error as 'random' because the mark is misaligned by 0.1 cm³ — alignment is irrelevant; what matters is that the error is consistent, which makes it systematic.
• Saying the error 'changes the trend' or 'affects the results' without explaining that it does not change the pattern — only the absolute values.
• Saying the error 'makes the results invalid' — the results are still comparable to one another, they are just slightly biased.

Things to Be Careful About

• The mark scheme requires both: 'systematic' and 'no effect on the trend' (a single linked statement). Missing either loses the mark.
• The error only has no effect on the trend because it is consistent across all tubes — that connection is the reasoning behind the answer.

Background Concept

A bar chart is used to compare a quantitative variable across a number of discrete categories. The convention is to place the categorical variable on the x-axis and the quantitative variable on the y-axis, with bars of equal width and equal spacing. To use the grid efficiently, the y-axis scale should span at least half the available grid, with sensible intervals (1 or 2 cm), and the bars should be drawn with a sharp pencil and a ruler so that the tops are straight and the sides are vertical.

Understanding the Question

Table 1.4 gives the percentage ethanol produced per 100 g of carbohydrate from five different sources. You are asked to draw a bar chart of these data on the grid in Fig. 1.2. The marks are for the conventions: axes labelled with both quantity and unit, a sensible scale, accurate plotting, and well-drawn bars.

Approach

• Identify the categorical variable (source of carbohydrate) for the x-axis and the quantitative variable (percentage ethanol per 100 g) for the y-axis.
• Choose a y-axis scale that uses at least half the grid and gives round-number intervals (e.g. 0–5 in steps of 1).
• For each category, draw a bar whose top is at the correct value on the y-axis.
• Use a sharp pencil and a ruler: tops straight, sides vertical, edges exactly on the axis.

Step-by-Step Reasoning

1. x-axis label: source of carbohydrate, divided into five equal categories, each labelled: molasses, oranges, grapes, beetroot, rice.
2. y-axis label: percentage ethanol produced per 100 g of carbohydrate. Choose a scale of 0 to 5 (1 unit per 2 cm), with labels at 0, 1, 2, 3, 4, 5 — this uses the grid efficiently and accommodates the largest value (4.70 for rice).
3. Bar heights (from Table 1.4): molasses 3.80, oranges 1.05, grapes 2.65, beetroot 3.35, rice 4.70.
4. Drawing the bars: each bar should be the same width, evenly spaced, with a straight horizontal top exactly at the value on the y-axis and vertical sides that meet the x-axis exactly.
5. Rice gives the tallest bar (4.70), molasses the next (3.80), then beetroot (3.35), grapes (2.65), and oranges the shortest (1.05).

Key Takeaways

• Axes must each carry a label stating the quantity and the unit.
• The y-axis scale must use at least half the available grid and be labelled at every major line (or at least every 2 cm).
• Bars must be plotted accurately, with straight tops and vertical sides that meet the axis exactly.
• Bar charts are for discrete categories on the x-axis, not for continuous variables (where a histogram or line graph would be used).

Common Mistakes

• Using a scale that is too small (e.g. 0–10) — wastes the grid and reduces plotting accuracy.
• Using awkward intervals (e.g. 0, 3, 5, 7) that are not multiples of 1 or 2.
• Failing to label the axes or omitting the unit on the y-axis.
• Drawing bars with rough or sloping tops, or with sides that do not meet the axis exactly — these lose plotting marks.
• Plotting the bars in the wrong order (any order is acceptable as long as each bar is correctly placed, but mixing up the data and the categories loses marks).

Things to Be Careful About

• The y-axis must extend to at least 5 (the highest value is 4.70) so the tallest bar fits the scale.
• Bars must be the same width and evenly spaced — not all crammed to one side.
• Each bar must be labelled with its category directly under it on the x-axis.

Background Concept

Different species of yeast have different optimum conditions for fermentation (pH, temperature) and different enzyme complements (so they may be unable to ferment all the same sugars). When an experiment is run at a fixed pH and temperature (here 30 °C and pH 5), species whose optima differ from those values will perform below their best, while species whose optima match will perform well. A species lacking the right enzyme for a given sugar will produce little or no ethanol from that sugar.

Understanding the Question

Table 1.5 shows that for every source of carbohydrate, S. pombe produces less ethanol than S. cerevisiae under identical conditions. The question asks you to suggest why — i.e. to give biological reasons for the consistently lower yield with S. pombe.

Approach

The mark scheme credits any two of three possible reasons. Read each in turn and ask whether it is consistent with the data:

1. Different optimum pH — the experiment used pH 5; if S. pombe's optimum pH is not 5, its enzymes work sub-optimally and ethanol yield is lower.
2. Different optimum temperature — the experiment used 30 °C; if S. pombe's optimum is not 30 °C, similar reasoning applies.
3. Inability to ferment some of the carbohydrate sources — if S. pombe lacks enzymes for some of the sugars, it will produce less ethanol from those sources.

Any two of these earn full marks.

Step-by-Step Reasoning

• The experimental variables kept constant are 30 °C and pH 5. Any species whose optima differ from these values will not work at their best.
• The data show a systematic difference: S. pombe is lower for every source. A difference that applies to every substrate is most easily explained by the conditions (pH, temperature) being wrong for S. pombe, or by a general metabolic difference (e.g. it ferments less efficiently), rather than by the absence of a single specific enzyme.
• A substrate-specific explanation (such as 'cannot ferment beetroot') would not account for the universal difference.
• The two best general explanations are therefore (i) the pH is not optimal for S. pombe and (ii) the temperature is not optimal for S. pombe. A third acceptable answer is that S. pombe is unable to ferment all the sources of carbohydrate used.

Key Takeaways

• A consistent pattern across all data points points to a systematic cause (e.g. sub-optimal conditions for one species), not to a one-off substrate effect.
• Enzymes have specific optima for pH and temperature; running an experiment at the optimum for one species does not make it optimum for another.
• Different yeasts have different enzyme complements and so differ in the range of carbohydrates they can ferment.

Common Mistakes

• Giving vague answers such as 'different yeasts work differently' or 'one yeast is better than the other' — these are not specific biological reasons.
• Giving only one reason when the question is worth 2 marks.
• Saying 'S. pombe cannot ferment carbohydrates' — the data show it can (it produces ethanol from all five sources, just less than S. cerevisiae); the correct phrasing is that it may not be able to ferment all of the carbohydrate components in each source, or that it is less efficient at it.
• Confusing S. pombe's lower yield with a flaw in the method, rather than a biological difference.

Things to Be Careful About

• The mark scheme accepts any two of the three suggested reasons; both must be given.
• Reasons must be biological (about the enzymes, optima or metabolism of S. pombe), not procedural.

Background Concept

A plan diagram is a low-magnification outline that records the overall shape of a specimen and the distribution of its different tissues, but shows no cellular detail — it is a tissue map, not a cell picture. CIE examiners use it to test whether you can see the section as a whole and record it accurately.

The non-negotiable conventions for a plan diagram are:

• a sharp HB pencil with clean, continuous lines;
• no shading of any region (shading is reserved for high-power cell drawings);
• no individual cells drawn inside any tissue;
• the epidermis drawn as a double line, because at low power the wall and the cuticle of each epidermal cell appear as two separate lines;
• the relative thickness of each tissue layer true to the specimen;
• a single straight ruled line for each label, ending precisely on the structure, with the name written horizontally.

Understanding the Question

You are asked to produce a plan diagram of the entire transverse section of the plant stem on L1 and to label the cortex. The 5 marks are awarded against five specific criteria (one per marking point), so every feature matters. There is no written explanation to add; the diagram is the answer. Because the candidate observes L1 in person, the exact shape of the section is set by the slide, not by the question paper.

Approach

First, scan the whole section at low power and identify each tissue layer in order from the outside in. Then decide on the proportions — how thick the cortex should be relative to the pith, how large the ring of vascular bundles is, and what the outline of the section looks like. Sketch the outline lightly, then commit to a clean, large, unshaded final diagram. Finish by adding a single label and label line for the cortex.

Step-by-Step Reasoning

Working through the five marking points:

1. Most of the available space, no shading — make the diagram as large as the drawing box allows so each tissue layer is visible; do not apply any pencil shading anywhere on the diagram.
2. Correct shape of the whole section, no cells — trace the outer boundary of the section accurately; never draw individual cells inside the cortex, pith or vascular tissue.
3. Correct number of tissue layers — show every distinct layer present on the slide, in the correct order from outside to inside, with their relative thicknesses matching the specimen.
4. Epidermis as two lines — the outermost layer is drawn as two close, continuous, parallel lines, representing the cell wall and cuticle of the epidermal cells together.
5. One ruled label line and label 'cortex' — a single straight line drawn with a ruler, going from inside the cortex out to the margin, with the word cortex written neatly in lower case at the end of the line.

Key Takeaways

• A plan diagram is a tissue-level map, not a cellular drawing.
• Conventions (no shading, no cells, double epidermis, ruled labels) carry the marks.
• Proportions and the number of tissue layers must be true to the slide.

Common Mistakes

• Shading any region, which makes the plan look like a cell drawing and loses the relevant marks.
• Drawing individual cells inside the cortex, pith or vascular bundles.
• Using a single line for the epidermis, or making the outline wobbly where the section is smooth.
• Adding several extra labels when only the cortex is required, or omitting the ruler rule on the label line.

Things to Be Careful About

• Keep pencil lines thin and continuous — re-trace any shaky line cleanly rather than leaving a fuzzy line.
• Make sure the cortex label line touches the cortex itself, not the general area or a neighbouring tissue.
• Double-check the number of layers on the slide before drawing; missing or invented layers cost the third mark outright.

Background Concept

A high-power cell drawing records the cellular detail of a small group of cells exactly as seen down the microscope. Unlike a plan diagram, a cell drawing DOES show the shape of individual cells, but it is still unshaded, drawn with a sharp pencil in clean, continuous lines. CIE examiners test whether you can see the cells accurately and obey the strict line conventions.

The non-negotiable conventions for a cell drawing are:

• a sharp HB pencil, lines thin and continuous, no sketching/fuzzy lines;
• no shading anywhere (no stippling, no hatching, no coloured pencil);
• two distinct lines around every cell, because the cell wall has two sides and at high power both are visible;
• where two cells share a wall, three lines are visible (one from each cell plus the shared middle wall);
• only structures that are actually visible are drawn — no inferred organelles, nuclei, or contents unless they can be seen;
• labels use a single straight ruled line, ending exactly on the structure, with the name written horizontally.

Understanding the Question

You are asked to select a group of four adjacent cortex cells, where each cell touches at least two of the others, and to make a large high-power drawing of them with the cell wall of one cell labelled. The 5 marks are awarded against five specific criteria (one per marking point), so every feature matters. Because L1 is in front of you, the actual cell shapes come from what you see under the microscope.

Approach

First, look at the cortex under high power and find a clear area where four cells are clustered and each cell touches at least two others. The cells in the cortex are typically roughly polygonal with slightly curved edges and may vary a little in size. Sketch the cluster lightly to get the proportions right, then redraw the final version with clean, thin, continuous double lines. Finally, add one label line and the label for the cell wall.

Step-by-Step Reasoning

Working through the five marking points:

1. Most of the available space, lines continuous, thin and sharp — make the four cells as large as the box allows, and draw every line as a single clean stroke, no breaks, no thick doubling, no fuzzy sketching.
2. Only four cells, each touching at least two others — exactly four cells in the drawing; the arrangement must allow each cell to be in contact with at least two of the others (a tight cluster, not a row of four isolated cells).
3. Two lines around each cell, three lines where cells touch — every cell is bounded by its own two-line wall, and where two cells share a wall you can see all three lines (left cell's inner wall, the shared middle, right cell's inner wall).
4. Detailed shapes of the cortex cells — the cells are drawn with their actual shapes: polygonal, with slightly curved or wavy edges, varying a little in size and shape, NOT as identical circles or regular polygons.
5. One ruled label line and label 'cell wall' — a single straight line drawn with a ruler, from the cell wall of one cell out to the margin, with the words cell wall written at the end.

Key Takeaways

• Cell drawings obey strict line conventions: two lines per cell, three where cells meet.
• Only four cells in this drawing, in a cluster where each touches at least two others.
• Detail means realistic cell shapes, not invented organelles.
• No shading under any circumstances.

Common Mistakes

• Drawing five or more cells, or arranging them in a chain where end cells only touch one neighbour.
• Using a single line around each cell, which loses the 'double line' mark.
• Drawing identical, regular shapes (squares, hexagons, circles) instead of the slightly irregular polygonal shapes of real cortex cells.
• Adding shading, or inventing a nucleus or vacuole that is not clearly visible.
• Labelling more than the cell wall, or omitting the ruler rule on the label line.

Things to Be Careful About

• Keep each line a single clean stroke — do not go over a line repeatedly or it will appear thick.
• Make sure the cluster of four really is a cluster: each cell must touch at least two others (a line of four cells only earns this mark if the middle two touch two others and the end cells each touch one — which fails).
• The label line must end on the cell wall, not inside the cell or in the middle of three lines.