This section provides a holistic view to the topic you are addressing. You should answer the following: Why are you interesting in the topic? Why is it important? What are questions you could post, that may or may not be answer in the subsequent sections.
Personal engagement is something that is shown throughout the IA, and is quite difficult to nail down. It involves showing that you have considered the experiment both from a top-down and a bottom-up perspective. Top-down shows that you have considered the broad implications of the variables on the results. The bottom-up perspective is when you look at the nitty-gritty details of the experiment – which is what they’re looking for! They’re looking for students who can show that they are passionate about the topic that they’ve chosen (or at least fake it!). So an example might be, if your experiment is about measuring how variable X influences variable Y, and you build a device in the process to measure variable Y, discussing the nitty-gritty details of the device and how you built it.
While strictly no longer a requirement of the IB, the hypothesis adds meat to your IA and shows that you have considered different outcomes to your experiment prior to conducting it. In real life, you will have completed the experiment prior to writing your hypothesis. However, still write in the future tense, e.g. “I expect the pendulum period to be proportional to X variable”. Another key point is that older examiners (prior to 2013) are used to seeing the hypothesis section, adding wholeness to the IA from their point of view.
The independent variable is what you change in the experiment. So if you’re changing the length of string of your pendulum, that’s your independent variable! Make sure to state how many iterations you will have in the experiment. So say you are changing the pendulum string length from 5cm to 40cm in steps of 5cm. Since all measurements have an uncertainty inherent to their measure, quote the values with an uncertainty. So, e.g. “Changing the length of the pendulum strength length from 5cm to 40cm in steps of 5cm±0.1cm”. The ±0.1cm is done by taking half the smallest measure – for measurements with a ruler (which are always imprecise), you can the smallest measure on your ruler.
The dependent variable is what you are measuring. So if it’s the time taken for the pendulum to complete one oscillation, then that’s the dependent variable. Similar to the independent variable, you need to comment on the precision of the equipment you measure, so ± half the smallest unit of measurement.
The controlled variables are all assumptions that remain consistent in your experiment. So this will almost certainty include the room temperature remaining constant. In the pendulum example, it will also include the length of string and the mass of the pendulum bob, as both of these would change the results in the dependent variable.
The apparatus includes all the equipment you used, described precisely in such a way that others can conduct the experiment.
To do well in the method section you need to checkbox a couple of things. The first thing you need to do is outline all the steps in the experiment in detail. So, this would include information on how to setup the experiment, on how to proceed with it, and mention how variables would remain controlled during the experiment. An example is included below:
The data processing section includes all the calculations, that are used through out the IA. These will almost always include the mean calculation, standard deviation calculations (which gives you the uncertainty for your experiment, along with other calculations relevant. If your independent variable is the frequency of a pendulum, you will need to calculate the time taken, for one swing of the pendulum and then use this to calculate the frequency.
The conclusion and analysis section include firstly a general statement of what is taking place. If the relationship between the independent and dependent variable is a straight line, state this! If it’s a curve, analyse what kind of curve if it. It may either be a log graph, a partially exponential graph or a square root of x graph. To check this, you can plot a log-log graph, a y vs. x squared graph or a y vs. square root x graph. The resulting line should be a straight line.
The evaluation section should outline the areas where errors occurred or may have occurred. Examples include things that were perhaps not fully controlled during the experiment, such as the mass of the input material or the temperature of the experiment.