Data analysis *sigh*. The reason that many students believe that the Biology HSC exams do not reflect the syllabus and have weird sets of stimulus and graphs. However, for many others data analysis is an opportunity to gain easy marks through referring to information on the page (rather than having to memorise mountains of content for the exam)!
I believe that data analysis is a welcome change from the old Biology syllabus, and I hope that by the end of this article, you will have all the tips to help you to secure a band 6!
When my year 12 Biology class was reflecting upon our data analysis exam performance, someone in my class gave this piece of advice, which I believe is pretty genius.
Try and interpret the material in front of you before reading the question. Now, this tip mainly applies to graphs and data as my eyes tended to gloss over large chunks of text if I had no idea what I was looking for.
However, if you are given a graph, map or stimulus dealing with data, try to pick out the trends and purpose of the data before reading the question. This way you can think of all of the important parts before being distracted by the question. For example, the axes, the trends in the data (increasing, decreasing, plateauing, varied between the variables) and think about how the data may relate to a part of the syllabus.
2020 HSC, Question 20
Without reading the multiple-choice options we can deduct that the basic trend is that siblings will have the most similar traits in this order: identical twins, biological siblings and adoptive siblings. Just as we would expect from our Biology knowledge!
So, you have had a look at the data and hopefully have a general idea of why NESA added it to your Biology exam and what the most important points are.
I would next recommend that you read the question and go through your normal routine of pulling out key terms, analysing the verb and noting the mark allocation.
A common mistake that students make is that they will ignore the data component of the question and jump straight to answering all of the content points. Even if they had the most incredible answer in the world, the absence of data means that there is no way that they will receive a band 6.
The other mistake students make is including the data but not considering how this data relates to their Biology content. Although data analysis may seem really unfamiliar, NESA tries to make it easier by making the data related to your syllabus sections so that the analysis is merely about applying your understanding of Biology to different concepts.
The trick to data analysis is to provide sufficient data to allow it to drive your answer, therefore making the analysis easy.
My rule was to always include one piece of complete data (more on that in a second) for every two marks. For odd number mark allocations, round up.
E.g. 4 marks = 2 pieces of complete data minimum
5 marks = 3 pieces of complete data minimum
Therefore, when I was planning my answer, I would always draw a number of checkboxes corresponding to every piece of data I would have to use. That way, I could check them off throughout my answer once I had included data and analysed it, allowing me to figure out once my answer was complete.
The most important step. When writing data analysis responses, it is important to consider how you would write band 6 answers without data too. That way you can tackle these notoriously more challenging questions with ease, and not forget essential information such as definitions, examples and links to the syllabus.
When adding data to your responses, you want to make sure that you include complete sets of data. This means adding all of the available information and not just highlighting some points in the data set. For example, you want to consider all axes on a graph, and not just consider how independent variables vary in one respect.
Here is an example to explain this concept further.
Biology Additional Practice Questions, Module 6 Question 11 b.
Sample answer: Strain B would be better as it leads to the production of a higher concentration of ethanol in a shorter amount of time than Strain A. For example, 10g/L of ethanol is created in 30 hours in comparison to 20g/L of ethanol in 30 hours by Strain B. This is suitable for commercial use as a higher concentration being created would allow for an increase in sales and a need for less of the modified yeast, which also proves to be of economic benefit.
In this response, the student has used complete data sets, through referring to g/L of ethanol produced, the strain and the amount of time it took.
My main piece of advice is to put everything on the page and leave nothing in your head. If in doubt, remember that they positively mark in Biology, so as long as you are not saying anything factually incorrect or contradictory, you should include it!
When checking, ensure that you have:
* Responded to the verb adequately
* Provided introductory sentences talking about the relevant concepts and defined key terms.
* Included complete sets of data and in the case of comparisons, as is seen in the example above, included at least one piece of data for each independent variable.
* Analysed the data and linked it to concepts you have learned about in class.
* Identified trends and pulled out key features within the stimulus.
* Linked back to the question.
At the end of the day, data analysis should be a welcome break from the longer response questions and an opportunity for you to gain easy marks from referring to stimulus on your exam paper. If you pull out the key features, do not rush your responses and ensure that you have sufficient information, you will absolutely smash it!