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IBdoingthistosurvive

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  • 2 weeks later...

Your first Bio IA - good luck!

I have gotten full marks in 2 of my Bio IAs, so here are some of my tips and tricks:

Design:

- Your research question is super important. Make sure you include your independent variable, your dependent variable, the variants (e.g. Volume of trypsin: 10g, 20g, 30g, 40g and 50g), how you will manipulate your IV and how you will use the results to calculate whatever you are trying to achieve. For example, if your measuring the rate of cellular respiration in yeast, you could be measuring the increase in CO2 ppm using a CO2 probe, over a certain period of time. This is your raw data. From here, make sure you include in your RQ how you will turn this information into a rate value. The average length of my research question was one third of an A4 page. It needs to be super extensive.

- Don't underestimate the importance of stating ALL your controlled variables. You will lose marks if you don't consider the important ones- say if you're measuring rate of photosynthesis and you don't control light! For each variable, say what it is, why it will affect your results if it's not controlled, and then, how you will control it. If it's a measurement control (e.g using the same quantity of spinach in each trial to measure photosynthesis, don't just say 'the same quantity of spinach will be used in each trial.' Rather, say '2.25g of spinach will be used in each trial, measured using an analytical balance.' Be precise and specific.

- Put in a nice introduction. This should be around 1-2 pages long with at least one academic source from either a textbook or scientific journal. This makes it look like you really know what you're talking about, and that you have thoroughly researched your topic. For example, if you're measuring the effect of increasing glucose concentration on cellular respiration of yeast, talk about the actual process of respiration, why glucose is important and detail into the optimum glucose conditions for yeast (if you can find it), or, of not, the results that you would expect to see.

- Finally, your Design should include the following: Intro, Aim, RQ, Hypothesis (not a criteria but still good to be able to refer to in the conclusion), Variables (IV, DV and CVs) and include with the IV the variants and how the effect of the IV on the DV will be measured,

Data Processing:

- Keep raw data separate to processed data. Make this clear, saying Raw Data and Processed Data

- You should have two graphs in the end. One with your processed data values (e.g. Change in CO2 ppm over 5 minutes for 5 variations of glucose) and one with your end data values (e.g. Rate of reaction at each of the variants). You have to include error bars. Seriously, you have to. You won't get a 6/6 if you don't.

- If you can accurately present qualitative data, raw data, process your data and include uncertainties, and then two graphs, and it's all correct, there is no reason why you shouldn't be able to get a 6/6 for data.

Conclusion and Evaluation:

- With your conclusion, don't just summarise your results. Try and explain them, even if the trend wasn't what you expected. Refer to why you would expect it to happen. If something went wrong, say that errors will be further evaluated in the evaluation.

- With the evaluation, you must suggest at least 5 reasonable improvements to your experiment. This isn't the time to a all the things that went wrong! Rather, talk about how if you a measuring transpiration it was very hard to blot water off the leaves, or if you are measuring photosynthesis that the lamp became hotter. How can you fix these? This is also the time to say why your experiment is limited, or where further research needs to be done to get more data. How can this research be used?

I hope that this helps. Having done 4 IAs for both Chem and Bio (8 in total) I'm well versed in just how overwhelming they can seem. Don't give up! The first one is always the hardest, and don't be shattered if it doesn't go well- my first IA was a total disaster! Good luck and feel free to ask any more questions :)

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  • 2 weeks later...

Your first Bio IA - good luck!

I have gotten full marks in 2 of my Bio IAs, so here are some of my tips and tricks:

Design:

- Your research question is super important. Make sure you include your independent variable, your dependent variable, the variants (e.g. Volume of trypsin: 10g, 20g, 30g, 40g and 50g), how you will manipulate your IV and how you will use the results to calculate whatever you are trying to achieve. For example, if your measuring the rate of cellular respiration in yeast, you could be measuring the increase in CO2 ppm using a CO2 probe, over a certain period of time. This is your raw data. From here, make sure you include in your RQ how you will turn this information into a rate value. The average length of my research question was one third of an A4 page. It needs to be super extensive.

- Don't underestimate the importance of stating ALL your controlled variables. You will lose marks if you don't consider the important ones- say if you're measuring rate of photosynthesis and you don't control light! For each variable, say what it is, why it will affect your results if it's not controlled, and then, how you will control it. If it's a measurement control (e.g using the same quantity of spinach in each trial to measure photosynthesis, don't just say 'the same quantity of spinach will be used in each trial.' Rather, say '2.25g of spinach will be used in each trial, measured using an analytical balance.' Be precise and specific.

- Put in a nice introduction. This should be around 1-2 pages long with at least one academic source from either a textbook or scientific journal. This makes it look like you really know what you're talking about, and that you have thoroughly researched your topic. For example, if you're measuring the effect of increasing glucose concentration on cellular respiration of yeast, talk about the actual process of respiration, why glucose is important and detail into the optimum glucose conditions for yeast (if you can find it), or, of not, the results that you would expect to see.

- Finally, your Design should include the following: Intro, Aim, RQ, Hypothesis (not a criteria but still good to be able to refer to in the conclusion), Variables (IV, DV and CVs) and include with the IV the variants and how the effect of the IV on the DV will be measured,

Data Processing:

- Keep raw data separate to processed data. Make this clear, saying Raw Data and Processed Data

- You should have two graphs in the end. One with your processed data values (e.g. Change in CO2 ppm over 5 minutes for 5 variations of glucose) and one with your end data values (e.g. Rate of reaction at each of the variants). You have to include error bars. Seriously, you have to. You won't get a 6/6 if you don't.

- If you can accurately present qualitative data, raw data, process your data and include uncertainties, and then two graphs, and it's all correct, there is no reason why you shouldn't be able to get a 6/6 for data.

Conclusion and Evaluation:

- With your conclusion, don't just summarise your results. Try and explain them, even if the trend wasn't what you expected. Refer to why you would expect it to happen. If something went wrong, say that errors will be further evaluated in the evaluation.

- With the evaluation, you must suggest at least 5 reasonable improvements to your experiment. This isn't the time to a all the things that went wrong! Rather, talk about how if you a measuring transpiration it was very hard to blot water off the leaves, or if you are measuring photosynthesis that the lamp became hotter. How can you fix these? This is also the time to say why your experiment is limited, or where further research needs to be done to get more data. How can this research be used?

I hope that this helps. Having done 4 IAs for both Chem and Bio (8 in total) I'm well versed in just how overwhelming they can seem. Don't give up! The first one is always the hardest, and don't be shattered if it doesn't go well- my first IA was a total disaster! Good luck and feel free to ask any more questions :)

Thank you so much for taking time to post this ^_^ really appreciate this!

I have one question though, for the variables do we need to explain their relevance to the experiment using citations from scientific journals/textbooks? Or is it ok if we explain without any references, simply our own words?

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That's fine! I'm happy to help. I know how hard I found it at first so I'm happy to share some of my wisdom (haha)

You don't have to have academic references, but it's good to try and find some kind of textbook reference or something if you can, as it looks like you have really got an understanding, of say, the effect of varying Potassium concentration on the growth rate of a certain type of seed, and why seeds need potassium etc.

Does that make sense?

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