Preparing for Practical Assessment (OCR A-Level Biology A): Model Answers

Preparing for practical assessment

Introduction to experimental biology

Experimental science forms the foundation of modern biology. Throughout history, biologists have advanced our understanding through systematic research and investigation. Notable examples include researchers such as Hershey and Chase, who investigated DNA function using bacteriophages, Meselson and Stahl, who studied DNA replication mechanisms, and Beadle and Tatum, who explored the relationship between genes and proteins.

It is important to understand that proving a hypothesis conclusively is extremely challenging. Hypotheses can be tested and either disproved or modified, but definitive proof remains elusive. Often, a hypothesis persists until it is either replaced by a better explanation or refined based on new experimental evidence.

Practical studies represent an essential component of biology at all levels and must be integrated throughout any biology course. The practical skills developed at A-Level provide vital preparation for university-level biology and other advanced scientific courses.

Practical assessment requirements

Practical skills are assessed throughout the course in multiple ways. Students must complete and document a minimum of $12$ assessed practicals across the two years of an A-Level course in a logbook. These assessed practical activities enable learners to demonstrate competence across a broad range of skills while applying them in real experimental situations. The first year of study builds foundational skills that will be formally assessed during the second year.

Essential practical skills

Planning an experiment

Planning represents a crucial aspect of experimental biology. Begin with thorough research to identify previous studies addressing your problem. This research helps you select appropriate techniques and apparatus for your experimental design. Your selection must be grounded in sound scientific knowledge and a comprehensive understanding of the problem being investigated.

Preliminary research and studies

After choosing the most suitable technique and apparatus based on your preliminary research, conduct trial runs or preliminary studies. These trials help identify variables that could affect your experiment, determine how to control these variables, and establish optimal quantities and volumes for completing the experiment.

Identifying variables

To ensure your experimental outcomes are valid, you must control any variables that might influence results.

Independent variable: This is the single variable you deliberately change to determine its effect on the results. Only one independent variable should be altered in any experiment.

Controlled variables (also called confounding variables): These are all other variables that must be kept constant or at least monitored to account for their potential impact. You need detailed procedures for controlling these variables consistently and for changing the independent variable systematically. Your method should be sufficiently detailed that another scientist could replicate your experiment identically without requiring additional information.

Dependent variable: This is what you measure to determine the experimental outcome. The method for measuring this variable is crucial, as it reveals how the independent variable affects your results.

Control experiment: A control demonstrates that the independent variable—not some other aspect of the procedure—caused the observed changes. The control eliminates the possibility that changes would occur spontaneously.

Evaluation of experimental method

Your experimental design must be evaluated to ensure it properly tests the problem, uses appropriate methods, and will produce expected outcomes.

Limitations: These are fundamental design faults that must be identified and corrected where possible. For example, gas leakage in collection apparatus represents a limitation preventing accurate volume measurement. The required accuracy level must be assessed and improved where possible. This is particularly important when outcomes have significant consequences, such as delivering precise anaesthetic gas volumes to fruit flies for genetic breeding experiments. Incorrect volumes could prove fatal or allow flies to escape during procedures.

Procedures must be evaluated and improved where necessary. Sometimes evaluation is possible before beginning the main experiment, allowing immediate improvements; other times, evaluation can only occur after completing the experiment.

Record all procedural steps comprehensively to enable other researchers to replicate your work exactly without additional guidance.

Implementing an experiment

Using apparatus and techniques

Understanding how to employ various experimental techniques is essential; some techniques require practice before beginning the actual experiment. Following instructions correctly may seem straightforward, but misreading or misinterpreting instructions is surprisingly easy. Practice following instructions carefully to avoid errors.

Experiments fall into two categories:

• Qualitative experiments: Collecting and recording observations without numerical data
• Quantitative experiments: Collecting and recording numerical measurements

Units and measurements

Key measurement principles:

• Use millimetres ($\text{mm}$) as the standard length unit (not centimetres, which are not SI units)
• $1\text{ mm} = 10^{-3}\text{ m}$ (one-thousandth of a metre)
• $1\text{ μm} = 10^{-6}\text{ m}$ (one-millionth of a metre, or one-thousandth of a millimetre)
• Be careful with decimal point placement when converting between units

Common measurements include:

• Temperature
• pH
• Time
• Volume
• Length
• Mass
• Light intensity (measured in lux using a light meter)
• Optical density (measured using a colorimeter in arbitrary units, percentage transmission, or absorbance)

Measuring microscopic structures: When measuring lengths under a microscope, such as chloroplast dimensions, a graticule is needed to measure in micrometres ($\text{μm}$).

When measuring time, you are limited by reaction time. Therefore, record time typically to the nearest $0.5\text{ s}$ or at most to $0.1\text{ s}$. Round values from digital stopclocks accordingly.

Presenting data

Different data types require different presentation formats. Qualitative data, quantitative data, ecological study results, and microscope drawings each need appropriate presentation methods.

Identify during planning and implementation stages how you will process and present collected data.

Recording data

Quantitative data must be recorded to the correct number of significant figures. When calculating a mean, the number of significant figures in the total determines how many significant figures should express the mean.

Decimal places: All data must be recorded to the same number of decimal places. Processed data may be recorded either to the same number of decimal places or to one more decimal place than raw data. This rule relates to measuring instrument resolution: if measuring apparatus records to the nearest whole number, precision cannot exceed one decimal place when calculating means.

Analysis

Once an experimental procedure is complete, collected results must be processed and interpreted to reach valid conclusions.

Mathematical processing

At the simplest level, mathematical skills involve calculating rates or means. More advanced skills may include:

• Calculating standard deviation and standard error
• Applying statistical tests (chi-squared, Student's t-test, Spearman's rank correlation coefficient)

When using these tests, follow formulae steps in logical sequence, then understand the meaning of results and their impact on experimental conclusions.

Graphical presentation

Present outcomes using graphs, bar charts, or histograms as appropriate. Select the correct graphical format for your data type.

Line graphs may be drawn using:

• Smooth line or curve of best fit: When confident in intermediate values, approximately $50\%$ of plots should fall on each side of the line
• Plot-to-plot line: Ruled lines connecting individual plots, used when no confidence exists in intermediate values

Graph size: Make good use of available paper. Plotted points should occupy at least half the graph grid in both $x$ and $y$ directions.

Using graphs: How graphs are used depends on experiment type. Enzyme experiments might require reading the gradient to determine rate, while other experiments might need reading the intercept to determine values such as water potential.

Evaluation of results

Evaluating results differs from evaluating procedures. This essential skill enables drawing valid conclusions from results, sometimes relying on mathematical processing and statistical tests.

During planning, you identified procedural limitations. Now evaluate these limitations regarding their impact on collected data. Experimental errors (operator errors or "one-off" errors) affect results and may produce anomalies. Identify anomalies by looking for results inconsistent with trends or other replicates—typically differences exceeding $10\%$ from the mean value.

Large percentage errors may lead to rejected conclusions or require retesting with improved apparatus or procedures to reduce error.

Practising practical techniques

Using laboratory glassware

Laboratory glassware serves numerous experimental techniques, so practice with various types is important. Using measuring cylinders accurately for volume measurement represents a basic practical skill. Select appropriate measuring cylinder size based on required volume—smaller cylinders often provide better resolution but may not hold sufficient volume.

Using a microscope

Light microscope use represents an important biological skill because many organisms and structures are extremely small and only visible when magnified. This applies to tissues, cells, and cell organelles.

A light microscope operates by directing light through a thin biological specimen on a glass slide. Light passes through multiple lenses, allowing image observation through the eyepiece lens. Several objective lenses on a rotating disc can be selected, enabling viewing under both low and high power.

Microscope technique: Always start viewing specimens by focusing on low power and carefully positioning the specimen centrally in the field of view. This prevents losing the specimen when switching to higher magnification. Once focused on low power, rotating to higher power should maintain the specimen in view and roughly focused, though fine focusing improves clarity under high power.

Microscope drawings

Drawing specimens observed under microscopy provides a vital method to document and record observations. Biological drawings should be scientific rather than artistic, representing accurate records of what you observe.

• High-power drawings should show detailed cellular structure, typically drawing no more than $15$ connected cells representative of all visible cell types

• Include magnification or scale indication (such as a scale bar)
• Draw label lines straight using a ruler, writing labels at line ends (not along lines)
• Use annotations to provide additional information about features (functions, properties, or observations)
• Make good use of available paper

Labelling: High-power drawings must be labelled with cell names (not tissue names). Low-power plans should be labelled only with tissue names (not cell names). For example, in a plant stem, the low-power plan should label "xylem" (the tissue name), while high-power drawings should label "xylem vessels" (the cell name).

Other biological drawings

Qualitative tests

Qualitative tests using reagents identify biological molecules through simple chemical tests producing colour changes. Examples include the starch test using iodine solution and the reducing sugar test using Benedict's solution.

Other qualitative tests use indicators changing colour when specific reactions occur. For instance, in the Hill reaction, the electron acceptor changes from coloured to clear when accepting electrons from chloroplast electron transport chains. Enzyme reactions may change cloudy milk solution to clear when casein protein is hydrolysed.

Quantitative tests

Quantitative tests involve numerical data values and comprise many biological experiments.

To generate numerical data, quantitative tests must use apparatus measuring or collecting this data type. The simplest tests time colour changes or appearance changes, making time the numerical data. However, timing has uncertainty about exact endpoints, which is subjective—determining precise endpoints is difficult even using comparators as reference points.

Plotting graphs from standard sets provides another opportunity to gather numerical data, though this may also rely on endpoint judgement.

Using a colorimeter: A colorimeter represents another suitable method for collecting numerical data. It measures light passing through coloured solutions to determine colour amount present. Various samples can be tested, such as betalain pigment solutions from beetroot cylinders left in water at different temperatures. A colour filter in the light path ensures correct wavelength measurement for specific pigments. For betalain (purple pigment), the correct wavelength is green light.

You need to understand colorimeter use and be aware of limitations and possible errors, including methods to reduce their impact.

Separating techniques

Chromatography: This technique separates unknown mixtures using a solvent that dissolves molecules and a medium such as paper. The solvent moves through the medium, carrying molecules with it. Molecules spread out and separate because they move at different rates.

Identifying molecules: Calculate the Rf value of each solute and compare against known values:

$\text{R}_f = \frac{\text{distance moved by solute}}{\text{distance moved by solvent}}$

Because Rf values are ratios, they are always less than $1$ and have no units.

Electrophoresis: This separation technique uses the principle that molecules in solution separate by size due to movement rate variation. Molecules move through fluid-covered gel using electric current. The smallest molecules travel furthest, separating solutes along the current line.

Safe and ethical use of organisms

Using aseptic techniques to investigate microorganisms

Sterile techniques prevent contamination of microbe cultures by other microbes, particularly important for preventing accidental human pathogen culture.

Dissection

Dissection involves opening organisms (plants or animals) to observe internal structures. Use sharp scissors and scalpels safely but confidently to avoid damaging internal tissues when laying them open for clear viewing. Draw these structures as a dissection record.

Using sampling techniques

Field investigations on populations require measuring population samples, as measuring entire populations is impossible. Samples must be representative of whole populations; therefore, samples must be random, avoiding bias such as selecting individuals for specific characteristics or ease of sampling.

Random sampling steps:

• Use a quadrat (square of known dimensions) to select and collect samples
• Select correct quadrat size and number using specific quadrat selection techniques
• Use random numbers to generate coordinates for quadrat placement in the chosen area
• Lay down a grid or double metre tapes to create a grid across the sampling area

When sampling seashores, factor in requirements such as sampling from different beach zones.

Sampling plant leaves or insects to measure size variation may require accounting for factors like age. Size variation determined by organism age rather than environmental conditions under study would invalidate the study, so only specimens of certain ages may be selected. For example, studying dog whelk shell height-to-width ratios might select only adults, ignoring juveniles.

Using technology such as data loggers or computer modelling

Computer-based modelling exercises supplement learning in laboratories or at home. These include ecological sampling studies, succession and zonation studies enabling comparison of ecological situations, and studies on disease impacts, predation, or predator-prey relationships examining theoretical population effects.