Grading

Summative Assessment

In-School Assessment

Practical Course Work

ASSESSMENT CRITERIA Doing brilliant IB ESS coursework.

The criteria for IA coursework are printed in your information booklet. As well as using this sheet as a checklist for the written sections, study the criteria and highlight any aspects which you do not succeed at the first time. Planning In rough before starting: □ List the possible input and output (dependent) variables relevant to the problem. □ Choose which of the input variables to change, and which to keep constant. □ Sketch a graph (with units on the axes) of what the results might be like. □ Think through any calculations that will be necessary (e.g. rates, percentages, changes). □ Jot down the likely sources of error in the experiment (not just lack of time!) In neat: □ State a specific ‘research question’ – which must make clear the input and output variables being investigated. E.g. “how does the concentration of caffeine in a drink affect the resting heart-rate of IB students?”. This can also be used as the title of your investigation. □ Write a hypothesis, if needed, briefly predicting the results you expect, and… □ … explain the prediction in relation to scientific ideas. [The hypothesis should be one sentence. The explanation will probably require a paragraph]. □ State the controlled variables, to be kept constant so they don’t influence the results. □ List the equipment needed. Think about… o Containers – give sizes o Measuring equipment – give details / units (e.g. 5cm3 pipette, light meter in Lux) o Biological materials – give species and other details where possible o Reagents – give estimated amounts and concentrations o Remember you’ll need equipment to measure the controlled variables, too! □ Write a method in numbered steps, o detailed enough for someone else to follow as instructions. o with enough values for the input variable, over a sensible range. o include precautions (e.g. zeroing balance, use of a colorimeter ‘blank’) o say how the input variable will be changed, o say how other variables will be controlled or taken into account. o State any environmental, safety or ethical aspects, giving precautions where needed (e.g. “all the woodlice will be carefully returned to their natural environment”). □ State what observations will be taken, what units will be used and shown how they will be recorded (it’s best to do this by giving a sample results table). □ State how the results will be analysed (eg: percentages, rates) and how this should be presented (eg: graph, giving details of the axes). □ Give details of how many results should be taken in order to gain reliable data. If you are measuring from different organisms, five recordings is a minimum. If you are doing repeat measurements on the same material, three repeats may be enough (check if they are all close together).

Data Collection and Processing □ Before you start experimenting, draw up a blank results table (with ruled lines); o give units in each column header, not in the body of the table. o Also give uncertainties (be realistic, and never less than ± 0.5 x smallest division). o Set out header as variable / unit (± uncertainty), e.g: “Temperature / °C (± 0.5)” o Use indices for units e.g. “cm3 g-1 s-1”, NOT “cm3 / g / s”. o allow space for extra observations / notes. o include measurements of your controlled variables. o if it seems sensible, allow space for calculations (averages, rates, etc) □ Record raw data directly into you results table. o Use decimal points e.g. 0•5 not 0,5 o Ensure your numerals are unambiguous (avoid flourishes & European 1’s) o Group but don’t punctuate thousands. E.g. 12 850 (not 12,850) or adjust units. □ Make any necessary repeats and/or checks to ensure the reliability of the data. □ Record any factors beyond your control that may influence the experiment.

□ Process the results into a form which matches the original hypothesis. You may need to: o Exclude obvious anomalies. If so, make it clear what you have done. o Take averages, to minimise random errors, and (if you have enough repeats)… o standard deviations to assess the spread of data around the average. o Do a test of statistical significance [see separate sheets on stats] o Calculate rates (amount / time) o Calculate percentages, or percentage change [ = (change/original) x 100 ] □ Plot these results on a suitable graph, again matching the hypothesis; o input variable along the x-axis, output up the y-axis. o ensure graph is fully labelled (title, units in proper format, key to data points, etc). o add error-bars to indicate uncertainties in measurement o if appropriate add a best-fit line (not a wobble-through-the-points line!): so that there is an equal spread of points above and below. □ Describe the trend(s) or pattern(s) in the data, taking account of its reliability. □ Report on any anomalous results.

Discussion, evaluation and conclusion □ Explain the results, as far as possible, in relation to appropriate scientific knowledge. □ If possible, compare your results to similar experiments reported by colleagues or books. □ Evaluate your experiment: o give the main limitations in the apparatus and techniques used. E.g. were the controlled variables actually controlled? What uncertainties are there in the measurements? o explain whether the limitations were serious enough to undermine the conclusion (e.g. refer to size of error bars compared with the trend in the data). □ State specific and realistic ways in which you could improve the investigation. o Concentrate on the actual method & apparatus, not just human errors and time. o If suggesting new apparatus (e.g. a datalogger to record results electronically), state how it would be used to help. □ Write a brief, clear conclusion: referring to the data, state whether it supports the hypothesis. NB: never use the word ‘prove’: data can support, or undermine a hypothesis. A hypothesis can be accepted, rejected, or modified.