Speaker 1: There are three things that are so important to put inside your research methodology, but it all starts with this, your research questions. So when you're coming up with your methodology, you have to think about your research question and ultimately the methodology in one word is the design that you're using to answer that research question. That is the most important thing. So once you've got a research question, you have to be so clear on what you are answering and then you'll be able to go on and say, well, I'm going to use these techniques, this analysis, this data to answer this research question. So the research question is the first important thing and then you can look at the methodology. Let's put that in a different color. So that's methodology, yeah. Now, method and methodology are very, very different from each other. Well, not very different, but they're different from each other. So methodology is the framework or the design of your experiment. It's the big umbrella that sits over everything that's saying I'm going to use this sort of approach and underneath that are three things, one of them being the method. The method is essentially the tools that you are going to use to answer that research question. So do not get confused. Methodology and method, they're two very different things. So methodology is the design. All right, what am I going to do? Is the, let's put this in a different color. Okay, is the design of your experiment or it's the kind of framework that you're going to use to answer any questions and then underneath methodology, you've got three things. The first one, let's choose a different color, let's go crazy, let's go blue. So we've got the method, okay. So this is, that is meant to be a one, the method comes in two primary flavors. The first flavor is qualitative. The second flavor is quantitative or you can have a mix of both flavors, lovely. So the first one is qualitative. Qualitative, what is the quality that you're looking for? So now this means that quite often, you don't need to have like a determined outcome. You're looking at how people feel or how something exists. You want to look at why something is a certain way. You also want to sort of explore a little bit more. This qualitative thing answers the who, the what, the how, the why and maybe even the where. So this is the sort of experiment where you're going to go out and you're going to sort of use techniques like focus groups. You're going to question people. You're going to have a look at people's responses. You may inject yourself into a certain environment and just absorb what's going on. You don't necessarily need a hardcore hypothesis because this is more exploratory, okay. The second one versus method is quantitative. That's way better. Okay, quantitative means that you're looking for the amount of something. Now in my field in the sciences, we are all about the quantitative. How much can I improve something by? How much is something changing? How much is there in the world? How much can I make this thing happen? That is what we're measuring and this is really good if you have a hypothesis that you need to test. Therefore, you're creating a controlled experiment and you're testing various things to see how much something, the quantity of that change. So this is something that we did all the time in the STEM field and qualitative quite often is in the social sciences, the humanities, but you can have a blended approach. So you can blend these together in a mixer like that. So you can blend these together and essentially just sort of like create your own thing where you are taking, for example, a questionnaire someone's filled out, quite a qualitative way of doing experiments, but you're using statistical analysis to extract terms or you're asking people a questionnaire where it's like one to five and then you're using that one to five scale to create numbers, to create a quantity of a certain aspect of your study. So those are the two massive flavors. You've got quantitative and qualitative or you could blend them together like some people do. Now the second thing people need to get from your research methodology section is the data collection. The data collection is so very important because what people need to get from reading your research methodology, so are you going out and asking people questions? Is it a survey? Are you doing one-on-one interviews? Are you doing a controlled experiment where you're only changing one variable and measuring something else? That was my experience from the science and chemistry background that I'm in. So are you collecting data yourself or are you going out and using data that's already out there to formulate your own research methodology? Now that is very, very important. This is about reproducibility. This is the kind of little bits of detail that people need if they want to reproduce your experiment. So what are you doing? How are you doing it? Where are you going to get this information? Are you creating it yourself? That is the data collection information that needs to be in your research methodology so someone can then just do the same thing that you've just done so that they can reproduce your results which arguably in science, reproducibility isn't one of our strong points. I'll be absolutely honest with you there. And then the last thing people need, let's choose a different color. Ooh, purple, nice. And the last thing people need when you're writing a research methodology is your analysis. Analysis. Okay, analysis is where you just have to describe what you're doing with the data. How did you decide whether or not something was to be included? Did you get rid of outliers, for example? Or how are you using statistical software or particular statistical analysis to get your results? Those are very important. Once again, this is about making sure someone can do exactly what you've just done by using the techniques you've used. So if you're doing any sort of statistical analysis, you need to make sure you include the details. In qualitative experiments, you may just be looking at the themes that have come out. You may be looking at pictures or images. You may also just be looking at how you can group responses from essays and come up with themes that can get together. So we're either looking here at, say, statistics or we're looking at things like, what did I say? Oh, themes. And so really, you're just sort of saying to someone, yeah, look, I collected this data. This is how I kind of sorted it out in my mind, either using numbers with statistics or looking at themes and collecting them together. And then we take our conclusions from the analysis that we've created. So this is all about making sure someone can just follow through all of your work and do exactly what you've just done. So you also need to include here any software. So if you've used any software, you need to also say in here. So what sort of packages have you used? Have you used R? Have you used other sort of AI to generate groups and themes together? Because that's a very popular thing these days. And that's essentially the three things that need to be in your methodology. You've got your method, whether or not you're using qualitative or quantitative. You've got your data collection, how you've actually got the data. In my thesis, which looks like this, all of my sort of methodology was based around the different techniques that I would be using for data collection. So I've got dynamic light scattering. What else have I got? No, come on now. You can do better than this. I've got differential scanning calorimetry. I've got thermogravimetric analysis. I've got transmission electron microscopy. I've got atomic force microscopy. You get the idea. But that was my data analysis. And under each one of those techniques, I made sure that I had the statistical software that I used and any sort of like image processing stuff I used for getting information out of my collected data. So that's very important. Those are the three things that need to be in a methodology section when you're writing it. And the last thing is limitations. Limitations are so very important because what you're saying is I use these techniques, but it doesn't answer certain aspects of this question as well as I would hoped. But you do have to argue in there that the techniques that you are using are better than other ones out there and you can cite other bits of literature. So that's the methodology section. Now you're armed with everything you need to know to go away and write it up. And if you like this video, go check out this one where I talk about how to write a masterpiece systematic literature review with AI. Go check it out.