Both of us did EEs in Geography - specifically, human geography. KR's was a comparison of the effectiveness of the National Recycling Programme across Singapore's core and periphery. Chloe's was a comparison of different areas of sustainability (using the Egan Wheel) across Singapore's core and periphery. (This is by no means a complete EE guide, it's just a compilation of tips!)​

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Choosing a topic and formulating a research question/hypothesis

A few things to take note:

• Choose a topic you are interested in - you will spend tens of hours planning, writing and editing. This process is a hundred times more tortuous if your EE topic is something you despise

• Choose a topic/RQ that allows you to collect primary data fairly easily - my teachers said that Geo EEs with both primary and secondary data score better, so think about how you can collect primary data - surveys/questionnaires? Fieldwork experiments? Make sure that wherever you want to collect data and the equipment you require are easy to access

• Choose a topic that has easily accessible (and reliable!) secondary data  -  speaking from experience, primary data can sometimes be a bit wonky because of human error, small sample sizes etc., so it's really important that you have more reliable secondary data (perhaps from government/business/universities) to supplement your primary data. Make sure that there's enough of it available to you BEFORE you launch into your EE analysis/methodology etc. For example, KR was a third through her EE when she realised a specific set of secondary data she needed was kept confidential by the relevant businesses - so the last thing you want is to encounter such a roadblock along the way. Check that anything you might possibly need is publicly available first - if crucial info is unavailable, perhaps you need to change your topic 

• (VERY IMPORTANT) Choose a topic/RQ where the outcomes can be mapped spatially - this is absolutely crucial for a Geo EE, as the marking rubric states that you need to be able to compare data aon a spatial scale, and present your findings on maps. This is why both our EEs compared core and peripheral areas of Singapore. If there's no spatial element to your RQ/topic, it is imperative that you include it

• (OPTIONAL) Choose a topic which allows you to leverage on family and friend connections - if you know people whom you could interview, or business owners who might be able to provide secondary data, this comes in really handy and saves lots of time

• (OPTIONAL) Choose something related to what you want to study in uni so you can mention it in your uni application essays. This way, you can reflect on the skills you picked up in the EE process (eg. qualitative & quantitative data analysis, strengths and limitations of different methodologies) and show uni admissions officers that you've already been equipped with skills needed to thrive in uni (but this isn't crucial, if you haven't decided what you want to study at uni yet that's okay) 

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Introduction - what to include

• RQ and hypothesis 

• Map of your study area 

• Information on why your topic is worth examining/relevant 

• Any background information about schemes/policies you may be examining

• Key geographical concepts and models you are using (eg. Egan Wheel, Core-Periphery model)

• Justification of your hypothesis and study area

• Link to Geography syllabus - literally quote the syllabus point that inspired your EE topic

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Methodology

• Primary data - how did you collect this? Questionnaire? Fieldwork experiments? What was the size of your study area and when/under what conditions did you collect this data? What were your sampling methods and why - what were the strengths and limitations? Did you conduct pilot experiments/surveys to identify and correct flaws before doing it for real?

• Secondary data - where did you get it from and how do you know it's reliable? Any flaws? 

• Interviews (encouraged - good to have advice from people privy to larger-scale discussions on your EE topic) 

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Analysis - Spatial element - mapping your data

To achieve this, our biggest piece of advice is to superimpose your primary and secondary data onto maps (to compare data across different scales/regions). See below for an example (from one of our EEs which scored 30/34):

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There are lots of map softwares available online, or you can also use an iPad to draw things.

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Make sure that for all your maps you have a border, north arrow, an accurate scale and your legend(s) -- the Geo examiners are super super pedantic about these. One of my teachers said that we needed at least 5 of these maps... so naturally we included loads.

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Analysis - different approaches

You will need to answer your RQ from more than one angle. For example, KR's RQ measured the effectiveness of the recycling programme, so she used a variety of indicators - recycling participation, distribution of recycling bins, frequency of collection by recycling trucks etc. It's good to have multiple indicators - it shows the examiner that you are thorough in your research and analysis, and that you know how to synthesise the wealth of information you have.

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If certain data isn't available, see whether you can use proxy indicators. 

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Analysis - signposting

This entire section boils down to one key question - IS YOUR HYPOTHESIS SUPPORTED OR REJECTED? You need to consistently reference your hypothesis in this section. "XXXX data supports my hypothesis because..." or "YYYY data does not align with my hypothesis because...". You should use such phrasing/terminology to indicate to your examiner that you are consistently focused on your hypothesis. Remember that they read tons of EEs a day, so by signposting, you are drawing their attention to the most important parts. (KR even bolded all her references to the hypothesis...guess you could say that was a bold move) 

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Remember that reality isn't black and white so you won't have 100% of your data support the hypothesis, or 100% of your data reject it. For KR's data 80% of it supported the hypothesis and the remaining 20% rejected it. 

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It is also in this section where you can mention the flaws in your data, and how this has impacted your outcomes. For example, in KR's questionnaire, there was an uneven distribution of respondents across residential areas, and this made her results skewed. It's good to recognise these flaws as it demonstrates your ability to critically evaluate (a key component of the EE!). Remember that your results won't be perfect - expect flaws and explain why.

 

Conclusion

Is your hypothesis on the whole supported or rejected? Explain why - and reiterate the key findings/outcomes of your EE. Any major limitations of your findings - mention here to show evaluation. 

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Other random tips

• There was a lot of confusion (thanks IB!) over whether statistical tests are required - one of us didn't include one as it appeared very contrived, and scored 30/34, so if you don't need it don't add it 

• Before you begin your essay, create a secondary data/info spreadsheet with columns for 1) key points 2) URL -- makes your lifeso much easier when you have to do citations and bibliography 

• Speaking from experience - if you're circulating a questionnaire - try to send it to people from different backgrounds instead of limiting it to your immediate social circles, otherwise your results will be extremely skewed 

• Make sure your analysis is grounded in geographical theory/concepts/models -- shows that you are engaged with the subject 

• You can alter geographical models to fit your local context!! The flaw of many models is that they were designed to match limited contexts (usually only America/Eurocentric, which doesn't apply to the rest of the world), so you can introduce the original model, and then explain how you've tweaked it to make it more relevant to your local context

• If you reference model EEs from past years make sure they're from the most recent syllabus, as the rubric is consistently refreshed by IB

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