Research question:
This should be a clear focused question that says exactly what you are investigating. It shouldn't be too long and it must include the dependent and independent variables.
Eg. What is the effect of pH on the activity rate of salivary amylase?
Dependent variable: activity rate
Independent variable: pH
Hypothesis:
This is a paragraph or two where you explain your research question. You are going to say something like:
"Salivary Amylase is a an enzyme that digests starch into di- and monosaccharides. Since it's a salivary amylase, the enzyme works best at an alkaline pH of 7, in other words, the optimum pH is 7. At this pH, the rate of amylase activity will be at it's highest. A pH that is much lower (very acidic) or much higher (very alkaline) will denature the enzyme permanently (specifically the active site), and the enzyme can't function anymore. The activity of the enzyme will decrease as we increase or decrease pH."
You may also want to include a graph to show this if this possible.
Variables:
A list or a table that include:
-Independent variable: this is the variable you're changing. In the example above, the pH.
-Dependent variable: this is what changes when you change the independent variable. Eg. Activity rate.
-Controlled variables: these are all the other variables that must be kept the same in order to get an accurate results. For example, Temperature, pressure..etc.
Apparatus:
This is the list where you include everything you are going to use. Make sure you don't forget anything. My teacher always told me to include a diagram of the apparatus, so you may want to add that too.
When listing the apparatus, be specific:
1)'A beaker' wont work, you have to specify the type and the volume. Same for any other apparatus of this sort.
2)When listing chemical substances like enzymes or starch solutions. Include the volume and the concentration.
3)For Solid substances used, include the mass in 'g'
4)When mentioning the thermometer, you may want to say it goes from -2C to 100C just to be specific.
Method:
I always prefer the method being in a list format rather than a paragraph. It makes it much easier to read and understand. I would advise you to not use the first person. For example if you want to say "I will measure 50ml of starch solution into a beaker" you should say "Measure 50ml of starch solution into a beaker"
Please make sure you include every single step, don't miss one because it seems like an 'obvious' step!
Also make sure that your method controls the controlled variables and allows the collection of raw data.
After finishing your design, take a look at the table below (from the syllabus) to make sure you didn't miss anything:
Data Collection and Processing (DCP)
Collected data:
This is normally given in one or more tables. Make sure your table is clear and easy to read and follow. Trust me, it makes a difference. Do not forget to include the units at the top of each column in brackets and the error!
Here's an example:
Data processing:
Data processing is where they want you to do something with the data. Find an average, do one of the hypothesis test, calculate the standard deviation...etc. It normally depends on the experiment.
Errors/uncertainties:
This is the calculation of the % error in your experiment which you're going to discuss in CE.
The uncertainty of each apparatus should be printed on it. If it's not, then the uncertainty is the half the smallest division. For example, a ruler that with 0.1cm division will have an error of +/- 0.05cm.
Data presentation:
This presentation should be of the raw data and the processed data if possible.
Bar graphs and line graphs are one of the best way to present a data in most cases. A pie chart or a scatter graph may also be used. When adding the graph, make sure it has a title, labelled axis and legends. If you are for example investigating something at two different environments or situations, you should have a graph for each and then a third graph with the both, to show better comparison. In most cases, you are going to have to do at least 3 or 4 trials, include the graphs for each, then a final one of the average results. When appropriate include the uncertainties in the graph.
Please make sure the graph/chart is suitable for your type of data before using it.
Here are examples:
Bar Graph:
Pie Chart:
Once again, take a look at the criteria for a last check:
Conclusion and Evaluation (CE)
Conclusion:
The first point about the conclusion is that it should directly relate to the hypothesis. In other words, your conclusion must restate and discuss the hypothesis. You are not going to say why the results weren't accurate in this section. You're going to do discuss your results. Does it support the hypothesis? Were you predictions correct? Make sure you mention them again. I read this in one of the documents it got, and many people make this mistake: when talking about a hypothesis you're talking about whether the results support or refute the hypothesis, not prove the hypothesis.
In your conclusion, make sure you discuss the graphs, the charts..the data processing..etc.
Evaluation and improvement methods
I would organize this part in this way:
1st paragraph: the weaknesses and limitations.
In other words, all the possible reasons you could think of as to why your % error is too big (if that applies), why you results didn't perfectly support the hypothesis, why you results weren't accurate...etc. So basically, you're going to talk about all the weaknesses in your design and the effects these weaknesses had on the results. When mentioning the possible errors, I suggest doing it in bullet points because like I said they're much easier to read and understand.
2nd paragraph: improvements:
This is basically the "The errors above could be avoided next time by.....". Then just start suggesting all the things you would do differently next time to get better results, for example:
1)Repeat the experiments more than x times.
2)Control temperature and pressure more carefully.
3)Try to reduce human errors.
4)Use more accurate apparatus for volume measurements. and so on.
Criteria table:
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