IB Diploma Biology – Internal Assessment Template



BEXLEY GRAMMAR SCHOOL

SCIENCE DEPARTMENT

IB Biology

Practical Handbook

A guide for your Internal Assessment.

Internal Assessment

Your final IB grade for your group 4 science course is based on three examination papers and an independent research project, called an ‘internal assessment’ or IA .Your Internal Assessment consists of one individual scientific study. It should reflect how a real scientific study is carried out in form and content.

Your teacher marks the IA investigation but the IB moderates a selection of student IA work externally. The IA is worth 20% of your total grade.

Although only one piece of work is completed as a full IA and submitted you will be doing practice pieces of work (60 hours for higher and 40 for standard ) and it is essential that you complete each of these to the best of your ability so that the feedback you get is meaningful. Pay attention to any practical skills or methods that you cover at any point in the course as these will help you to complete your IA correctly.

Key points:

Research question – You are to define a unique research question.

Time allocation – Ten hours of class time but you may be able to do additional work outside of class.

Context – You are to set your investigation in an appropriate scientific context.

Research – You are expected to do research on your topic.

Content – You does not have to demonstrate knowledge or skills that go beyond the level of their course, although you can do an investigation that is not syllabus-based.

Report length – 6 to 12 pages (excessive length will be penalised). The maximum length includes footnotes or references as well as data tables, graphs and charts, pictures and, of course, text.

Personal involvement – You are expected to ‘own’ your investigation, to demonstrate some insight, initiative or personal interest in your investigation.

Self-management – You are responsible for your work, including meeting deadlines.

Technology skills – You need ICT skills, including word-processing, spreadsheets, graphing software, and internet searches. You must also know how to reference resources.

Assessment criteria

You will be assessed on 5 criteria. They are not equally weighted. The criteria (to be awarded the highest marks) are outlined below. To help you meet these criteria use the structure and guidance information that follows on page 6

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Personal engagement

This criterion addresses your involvement in the investigation. It is important that you are interested in your topic such that you can demonstrate independent thinking, initiative or creativity. You must also demonstrate a justification for your research question; perhaps there is some personal significance, interest or curiosity here. Finally, you are to provide some personal input and initiative in the designing, implementation or presentation of the investigation. Although your teacher may guide the you into productive and safe areas of study, the student is expected to define their own research question You are to ‘own’ your project, not just repeat something found in a science book or journal. This does not mean you can’t keep things simple though! Just try and think of different variable or reason for the investigation for example. The expectations of personal engagement actually mean that you will enjoy doing the work.

Exploration (Question, background information and methodology)

You are expected to state a scientifically relevant and focused research question. You are to do research and set your research question in a scientific context. You should use appropriate terminology and appropriate scientific techniques to answer the research question. You must also be aware of factors that might influence the relevance, reliability and the quality of your data. If environmental and safety issues are relevant then you must demonstrate a full awareness of these issues.

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Analysis (results, processing, displaying and interpreting)

You are expected to make an appropriate and justified analysis of their data in a way that addresses the research question and can be used to support a valid conclusion. This analysis includes the selection, processing and interpretation of data. Errors and uncertainties, where relevant, are to be dealt with in a reasonable and consistent way.

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Evaluation (conclusion, evaluation and further study)

This criterion addresses your methodology and your results as set within a genuine and relevant scientific context. It focuses on how well your data supports the conclusion, including the method and appreciating the strengths and weakness of your work (ie does your evaluation reduce the confidence in your conclusion). You are expected to provide realistic and relevant suggestions for the improvement and extension of your investigation.

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Communication

You are expected to produce a written report that is clear and easy to follow. The report is to demonstrate effective communication and should be focused on the investigation’s process and outcome. No superfluous material should be included. The report is to be 6 to 12 pages in length; excessive length will be penalised under this criterion. Appropriate scientific terminology and conventions must be followed, and graphs, tables, images, charts must all be presented in a clear way.

Use the following structure and guidance for your report

Tick them off as you go.

Candidate name and number

Research question e.g. Investigation to find out the effect of dropping height on the height a ball bounces. (It should clearly include your independent and dependent variables and mention specific location/organism involved where relevant.)

Introduction

Why are you interested in this topic/what prompted you to want to investigate/what issue does it address?

Describe the context – location, species, organ system, biological concept if relevant. Use diagrams, maps, photographs etc.

Give a hypothesis.

You must include good quality biological theory which helps to explain what you are researching and your hypothesis. This should be IB standard and link the 2 variables together.

You could include a reference to a secondary source – if possible, one which you can later compare your results/conclusions with. Give the reference as a footnote if a secondary source is used.

Variables (these could be in a table)

Independent – state clearly what your independent variable is and the range of values you will test.

Dependent – state clearly what your dependent variable is. (Exactly what you will be measuring)

Controlled – state each of the variables that you can and will control; state how you will control each one and why it needs to be controlled (ie – would would happen to the expected result If this factor was higher/lower and why?).

Uncontrolled – state any variables that are important but cannot be controlled. Think – can they at least be monitored to see if they vary?

Apparatus

List each piece of apparatus and where possible state sizes. A labelled diagram showing how apparatus is set up may be helpful

List all materials/chemicals with the total volume needed, units and concentrations.

Use SI units of measurement and be precise i.e. state uncertainties of measurements e.g. +/- 0.5 cm3

Risk Assessment

State any important risks/hazards and how you will minimise them. You may need to consult the Hazcards in the lab for specific chemicals/concentrations.#

Ethical considerations

Are there any ethical implications to your investigation? How will you minimise harm/impacts on the environment.

Method

Write your method as a logical sequence of numbered steps/bullet points.

Be specific about how to use apparatus and about quantities of substances. It must be repeatable. How are you going to increase your chance of getting accurate and reliable results?

Don’t forget to explain how your controlled variables were controlled and how they were monitored

If appropriate, include a ‘control’ with which to compare experimental results – NB this may not always be necessary.

Avoid writing things like “I will measure out 5cm3 water into a test tube” – instead, say “Measure out 5cm3 water into a test tube”

State the different values of the IV that you will test and how many times you will repeat the experiment so that it is clear that your method allows for the collection of sufficient relevant data. The minimum should usually be 5 values of IV and 5 repeats, but the quantity of data will depend on the complexity of the experiment. Statistical tests often require a particular amount of data to be valid (eg standard deviation should have 25 values!).

Mention how you plan to analyse your results – it’s no good planning to collect a tiny quantity of data if your chosen method of analysis requires a lot more! If possible, say what data processing you are going to do and why.

Was there any preliminary results, or research that helped you to formulate your method. (IE is certain apparatus recommended over an alternative elsewhere? Did a preliminary study help you to select the range of your independent variable?). For ecology practicals ensure that you describe your sampling technique very specifically and justify it.

Results

Record any qualitative observations made during the investigation. (eg a colour change, change in appearance of vegetation across an area, how vigorously a reaction is bubbling.)

Record all raw data in a table, as you collect it. The table must have a title/heading.

The independent variable should be in the left-hand column, with the dependent results to the right.

Each column must have a descriptive heading with SI units and uncertainties (This depends on the apparatus being used. See the ‘uncertainties sheet). Units must only go in the heading

Your data must be recorded to an appropriate number of decimal places based on the measuring apparatus used, and within each column the use of decimal places must be consistent. They must also be consistent with the uncertainty (so you may have to add .0 to your results)

Never split a table across 2 pages.

Identify anomalous results e.g. by highlighting them and including a key.

Table 1: A table to show how water temperature affects the time taken for a sugar cube to dissolve.

|Temperature of water (oC) |Time taken for a sugar cube to dissolve. (s ± 1s) |

|±0.5 oC | |

| |Repeat 1 |Repeat 2 |Repeat 3 |

|20.0 |300 |310 |305 |

|30.0 |290 |300 |275 |

If appropriate, calculate the mean and standard deviation. Would a rate be useful – check your calculations as errors will drop marks.

Processed data to should do the same number of decimal places as the raw data.

NB for a standard deviation to be valid it should really be based on a large number of repeats (at least 20if this is not possible calculate the SD but include a comment that it is not valid if your data does not show a normal distribution or you have too few repeats – it is still worth doing it as it gives you an idea of the reliability of your results.

Do you need to do any other calculations e.g. t-test and does your data processing need a null hypothesis? Give the formula used for any calculation that is not on a standard calculator menu. Lay out any processing clearly.

Do you reject or accept your null hypothesis based on your results/analysis? If using a statistical test give the full summary statement about critical values etc.

Plot graphs of processed data. Is your graph the correct sort? Line graph v bar chart.

Add a title to your graph.

Ensure the scale of the graph is correct and allows the data points to be plotted accurately.

Always include error/uncertainty bars either to show the range or +/- standard deviation. Include a key to say what type of error bars they are

Adjacent data points should be joined by a straight line and the line should start with the first data point and end with the last one, as there should be no extrapolation beyond these points

Add a line of best fit where relevant and label it as such. Make it different to the previous line.

The IV should be on the X axis and the DV on the Y axis.

Add descriptive labels to access and include units and uncertainties. If you’re plotting a mean – say so on the axis (otherwise it won’t be clear it’s processed).

Conclusion

Make a clear, precise statement based on your data. Describe any trends and quote data.

Justify your conclusion using your data.

Explain your conclusion with detailed science. Does this match the known theory (refer back to your background information) – reference to a secondary source is essential here. Refer to cited published data if available. You can reference using footnotes. If your results don’t match your expectations or published data refer back to what you would have expected and why. Do not worry about repeating what you have written earlier in the report.

Evaluation

Consider your data:

Evaluate your results.

Where your results accurate? This can be judged by considering if they matched what your research said should happen. Also- how close were your points to the line of best fit. Closer= more accurate.

Where your results reliable? Reliable results mean that your repeats were similar and so your range bars were small. Don’t just be general- refer to specific range bars. Point out the most/least precise. Remember- more reliability means less uncertainty in your data and more confidence in your results.

What is the impact of these uncertainties in your data. Does it reduce the confidence in your conclusion?

Consider your method (you could use a table like the one below to set this bit out):

Identify at least 5 weaknesses/limitations/sources of error in your method and indicate the magnitude of impact on data (small, medium, large or rank order the limitations – which is the most important?). See the ‘common limitations’ sheet for some ideas. Eg Was your method repeatable? What did you control well? What made it difficult to do the method in exactly the same way each time? What were the things you couldn’t control?

Evaluate the impact of the limitations. Does it cause you to overestimate a value? Or does it reduce accuracy or reliability? Why?

Suggest realistic improvements which would address each of the limitations you have identified. These must be achievable in a school environment.

|Limitation |How/why it affects data |Ranking |Suggested improvement |

|Difficult to maintain a stable temperature|The temperature fluctuated by +/- 8( C. If it got higher |1 |Use a thermostatically controlled |

|in a water bath made using a beaker of |than it should be, the rate of the reaction would | |water bath, and monitor it |

|water and a Bunsen burner |increase. | |constantly with a thermometer |

|Only three repeats were collected due to |The raw data collected was unreliable as it had a large |2 |Collect at least 5 repeat readings |

|time constraints |range. Therefore I cannot be confident that my mean is | |at each temperature. |

| |accurate. More repeats would have helped me to identify | | |

| |anomalies and omit them if necessary. | | |

| | | | |

Now that you have evaluated do your results really allow you to answer your research question. How confidant are you.

|Your evidence is strong if you answer yes to these questions: |Your evidence is weak if you answer yes to these questions: |

|Are your results consistent enough to give you reliable evidence to use to answer|Are your results variable or are there many anomalous results that |

|the research question? |can’t easily be explained? |

|Was the design of your experiment successful so that it gave precise and accurate|Were there faults in the experimental design which limited the |

|results? |precision or the accuracy? |

|Were all the variables controlled satisfactorily so that only the independent |Were there uncontrolled variables, which |

|variable was varied? |Introduced uncertainties into your interpretation of the results? |

|Is there only one explanation that fits all the evidence and answers the research|Are there alternative explanations that would also fit the evidence |

|question? |and which you cannot refute? |

|Can you support each part of your answer to your research question with |Are there parts of your answer to the research question which are |

|experimental evidence or by reference to other published data? |unsubstantiated or uncertain and which need further investigation? |

How could your investigation be extended? Have your results raised any other questions that could be investigated?

Does the answer to your question have any relevance to the real world?

Reference list

There are different ways of referencing secondary sources in the text of your work. The IB does not have a particular preference but it must be consistent in your work. Whichever way you choose to reference in the text it must be accompanied by a full reference list at the end of your work. In the reference list. These must be written alphabetically in the format below.

If it’s a book:

Barber, J. Tribes of Kenya. Frankin Watts. 1998

Douglas, A. Symbiotic Interactions. Oxford University Press. 1994

If it’s a journal:

Knight J. Gene therapy. Biological Sciences Review. Vol 6, No.1, pp22-24.

If it’s a website:

Emma Brenard. Tardigrades: Water bears in space. Viewed online on 20/08/14 at (There’s not always an author- if not replace it with the name of the general website. You must still include the full URL.)

Throughout the text, the easiest option is to use numbered footnotes. So if the first reference was the Tardigrade one, next to the relevant info in your paragraph do a superscript 1. Then put the 1 and the full reference at the bottom of the page. It will then be repeated again in this reference list. Your numbers should continue throughout the whole piece of work- not stop and start again for different sections.

Help sheet- Uncertainties

When you take measurements you cannot be sure that the data is completely accurate. The measurement apparatus you use will have uncertainties. You need to refer to these when writing up investigations

(Consider this- I could measure out 10 mls of liquid but ‘the real value’ could actually be 10.05 mls but I wouldn’t notice this if my measuring cylinder only had whole mls on the scale. The uncertainty tells you how much your measurement could be ‘out’ by.)

Quote these uncertainties:

• On your apparatus list (This allows people to copy your method using apparatus of the same precision)

• In the headings of results tables

• On the axis of graphs.

They can also be discussed in your evaluation. If the uncertainties are large your conclusions could be in doubt.

The uncertainties depend on what you are using to collect the data….

Rulers that measure mm :

Rulers are a special case. The uncertainty is always ±1mm

The bar is 1.4cm or 14mm

The uncertainty in the table heading would be ±0.1cm or ±1mm

Measuring apparatus (eg measuring cylinders, thermometers) but not rulers.

The uncertainty is ± half of the place value (ie half of that decimal place) of the last measured value.

Eg if a syringe has markings that go up in 0.1mls its uncertainty would be ±0.05mls

Eg. A measuring cylinder has markings that go up in 10mls. Its uncertainty would be ± 5mls.

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Electronic instruments (eg a balance)

The minimum uncertainty is ± 1 unit of the last decimal place. (Note that this is different to the non-electronic things above.)

Eg. A balance gives measurements in grams to 2 decimal places. Its uncertainty would be ± 0.01g

Estimated uncertainties

When you are counting something (particularly observations on living things) you will have an uncertainty. You need to make a sensible estimate of uncertainty.

Eg abdominal breathing movements of a locust. ±1 or 2

Eg. Heart beats of Daphnia ±10 (The uncertainty is higher because the movement is faster so you’re likely to be out by more)

Eg % cover of moss in a quadrat. ± 4%

Uncertainties and your raw data.

Uncertainty and raw data should have the same number of decimal places. This may mean adding a zero onto your raw data.

Here are some examples showing just 1 column from data tables. Refer back to the previous information to justify to yourself why these uncertainty values have been given ( ie what type of apparatus is being used). Note how many decimal places the raw data has been recorded to.

A) A gas syringe has a scale which goes up in 10ml increments

|Volume of gas (ml ±5ml) |

|30 |

|20 |

|25 |

|10 |

B) A thermometer has a scale which goes up in 1oC increments.

|Temperature of water. (oC ±0.5oC) |

|4.0 |

|54.0 |

|78.0 |

|11.0 |

C) A student was measuring his own pulse rate.

|Pulse rate (beats min-1 ±2) |

|55 |

|56 |

|61 |

|55 |

D) A balance measures to a precision of 0.1g

|Mass of glucose (g ± 0.1g) |

|10.0 |

|15.5 |

|20.2 |

|21.0 |

Help Sheet- Common limitations to investigations.

Limitations

A limitation is any factor that has not been controlled or taken into account in the design of an experiment can be referred to as a limitation. A limitation can be described as a design fault. Limitations will reduce the confidence you can have in the conclusions you draw from your investigation.

(Errors are different- if you make a mistake this doesn’t count as a limitation.)

The limitations will obviously depend on the investigation you carried out but here are some common ones. Ensure that you discuss them in the context of your investigation.

• Were a limited number of values for the independent variable investigated?

Imagine you wanted to investigate the effect of pH on something. You investigate pH 4,5,6,7 and 8. This is a limited range and so you could not conclude what the impact of lower or higher pHs would be. Also intermediate values should be investigated to more accurately determine where the optimum pH is. Intermediate values are good for confirming any trend, giving a more complete picture of how one thing affects another, and if a change occurs (eg an increase, decrease, plateau) you can more accurately say when this occurs.

• In investigations that involve gas collection – could gas be escaping from the apparatus at any point? This would cause the volume data to be lower than it should be.

• In investigations that involve gas collection – could there be more than one gas being collected which would cause you to overestimate the volume?

• Were any important factors not controlled? Consider all the factors that affect enzyme action/ diffusion/ respiration / photosynthesis/ transpiration etc from theory lessons. They should all be controlled unless used as the independent variable.

• Were investigations carried out at optimal conditions? You may control temperature but if it is too low you may get very little activity in a particular reaction. This will make it harder for you to make judgements about whether the independent variable is having an effect.

• Does any part of the investigation involve making judgments about colour, clarity, % cover? These are subjective judgements (based on opinion) and so could vary each time you make an observation. Could a comparison chart or electronic devise be used instead? This would increase the accuracy of measurements.

• Did the precision of your apparatus lead to uncertainties you consider to be unacceptable? If uncertainties are large it is more likely that data for each of the independent variable values could overlap. If they do then you can’t confidently say that there was a real difference between them. An improvement could be to use more precise apparatus.

• A small number of repeats (or none at all) is problematic as it reduces your ability to judge reliability. More repeats help you identify anomalies and omit them if necessary. More reliable data means that you can have more confidence that mean data is accurate.

• If sampling- was your sample size large enough to be representative of the population or area? A small sample could mean that you are not getting a true impression of a characteristic or area.

• If sampling- were there temporal, special, or safety constraints that stopped you from sampling in the ideal place or time?

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For specification starting in September 2014. Updated 2015.

Keep me safe

and bring to lessons!

In here this is information on:

• How does the internal assessment fit in with the rest of your course?

• Criteria for assessment of your IA

• Structure of your IA and specific instructions for what to include- essential to follow when completing practice tasks and the real thing!

• How to decide what the uncertainty of apparatus is.

• Some examples of common limitations to investigations.

See also:

• Also see p710-712 of your textbook.

• There is a specific IA book ‘A Students Guide to Internal Assessment’ which is very useful for writing up any investigation but does refer to the old coursework.

• There are example pieces of work on the KS5 Biology Fronter page

When writing about variables- the word ‘amount’ is banned! Refer to volumes of, mass of, number of sample sites etc.

Remember:

Accuracy- closeness to the ‘true’ value

Reliability- the consistency of repeats

Precision- The ability to be exact (degree of precision). Eg using a balance that measures to 2 decimal places is more precise than using one that only measures to whole numbers.

NB – It would be sensible for you to measure the amount of liquid here as 25mls. This doesn’t affect your uncertainty value as they only relate to measured values (as opposed to estimated ones).

Only estimate halves of measurements.

40

30

20

10

NB. You uncertainty is also linked to how you use the apparatus. If a timer measures to 0.01 of a second but you ignore the decimal places and just record whole seconds the uncertainty is ±1s and not ±0.01s.

This gas syringe was half way between 20 and 30. This was an estimate (but it doesn’t affect the uncertainty).

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