Design

IAs - Design - Data Collection and Processing - Conclusion and Evaluation

Internal Assessment - Design
This is probably the most challenging skill. Once you have mastered reflecting on the labs you've carried out you will be ready to then suggest further steps, which is in effect what designing a lab is all about.
 * Designing labs**


 * ** Levels/marks ** || ** Aspect 1 ** || ** Aspect 2 ** || ** Aspect 3 ** ||
 * ^  || ** Defining the problem and selecting variables ** || ** Controlling variables ** || ** Developing a method for collection of data ** ||
 * Complete/2 || Formulates a focused problem/research question and identifies the relevant variables. || Designs a method for the effective control of the variables. || Develops a method that allows for the collection of sufficient relevant data. ||
 * Partial/1 || Formulates a problem/research question that is incomplete or identifies only some relevant variables. || Designs a method that makes some attempt to control the variables. || Develops a method that allows for the collection of insufficient relevant data. ||
 * Not at all/0 || Does not identify a problem/research question and does not identify any relevant variables. || Designs a method that does not control the variables. || Develops a method that does not allow for any relevant data to be collected. ||

Though success in design needs a considered approach, it is really your creativity that is challenged. Read through the following steps before and during a design exercise.

A good introduction to design and the scientific method in general is this [|youtube video] thanks to Steve Taylor for posting it on his site you can also find a brief introduction to design on [|i-biology.net] too.


 * Preliminary investigations **

Play with the equipment, do mini tests. This will help you work out:
 * If your idea will work
 * If your equipment choice is the right one
 * Whether you are examining the right range of data
 * If the concentrations/volumes/masses you are using will produce measureable results
 * If you can collect enough data in the time given to you.


 * Specify the research (biological) question to be answered **

This should be a simple statement that refers to both the independent and dependent variables. Examples would be:


 * Investigate how pH affects the reaction rate of the enzyme amylase
 * Investigate how surface area to volume ratio affects the rate of osmosis


 * Background Information **

Outline the theory you are investigating. This is your first, and most important, chance to reference/refer to accepted theory. Textbooks, journals and reliable websites can all be used to help support the research question.

N.B. references must be properly cited


 * Put the question in the form of a hypothesis. Better still split it into a null hypothesis and alternate hypothesis. **

To write a good hypothesis your first step should be to sketch a graph (no numbers, just a rough drawing) of what you think is going to happen. You may include the graph if you feel it helps, but you must express what the graph shows in words. Give a scientific reason and refer back to your background information.

If you feel confident enough split up your hypothesis into null and alternate statements:

The null hypothesis is a statement that you want to test. In general, the null hypothesis is that things are the same as each other, or the same as a theoretical expectation. For example, if you measure the size of the feet of male and female chickens, the null hypothesis could be that the average foot size in male chickens is the same as the average foot size in female chickens. If you count the number of male and female chickens born to a set of hens, the null hypothesis could be that the ratio of males to females is equal to the theoretical expectation of a 1:1 ratio.

The alternative hypothesis is that things are different from each other, or different from a theoretical expectation. For example, one alternative hypothesis would be that male chickens have a different average foot size than female chickens; another would be that the sex ratio is different from 1:1.

[John McDonald - [|http://udel.edu/~mcdonald/stathyptesting.html]]

You are encouraged to explicitly list them out. It will make it clear in your mind what you have to focus on when designing the method. List out the independent and dependent variable. Identify as many relevant control variables as you can. The easiest way to lose a complete on aspect 1 is by not having an exhaustive list of control variables.
 * Determine which variables are relevant to the question **


 * Before writing the method consider the following questions: **
 * Looking back to your hypothesis decide what data do you need to produce the desired graph?
 * How will you process the raw data?
 * What raw data do you need to collect to support the processing?
 * You need to fulfill the 5 x 5 rule as a minimum – 5 different values of the independent variable and 5 repeats (so standard deviation can be calculated)
 * Beyond the 5 x 5 will your changes in the independent variable show a sufficient range and close enough increments to clearly produce the graph you desire? If not extend your range of measurements.
 * If you are taking samples (e.g. to estimate a population) is your sample size large enough to be reliable?

A scientific method is most simply explained as a way of addressing all the variables you have identified: controlling the controls, measuring the dependent and changing (in a controlled way) the independent variable. In terms of the IA criteria this is aspect 2.
 * Method **

Though it is not required you are strongly encouraged to start your method by listing out the apparatus used. Don’t forget quantify the equipment where you can, e.g. measuring cylinder 10cm3 (± 0.05cm3).

Bullet point or number each step. Keep each step short, concise and clear.

Your method should address the following points:
 * How __exactly__ does your method change the independent variable and what values are you choosing.
 * In detail say how you are measuring the dependent variable.
 * Give an example results table to show how you will record your findings.
 * Are you making up solutions/diluting solutions? If so detail this process, better show calculations and uncertainties in a table.
 * Assume all lab supplies given to you are prepared 100% accurately – your work is being assessed, not the lab technicians.
 * Address all control variables. Either by saying how you will keep them constant (the best option) or by randomising your samples so that variation should be roughly equal in all: //e.g. I cannot accurately determine how moisture varies throughout the field so I will randomly place the 10 plots where I will use herbicide and 10 plots where I will not use herbicide.//


 * Aspect 3 - Developing a method for collection of data **

This aspect should already be accounted for as long as you have collected enough data:
 * 5 x 5 rule is a minimum requirement when looking at how x affects y
 * For labs that will be analysed by t-tests 10 observations per independent variable change is a minimum

The method you suggest should be rigorous enough to collect the right data to allow you to investigate the research question. Get the first two aspects right and this last one should take care of itself.