If you’re new to formal academic research, it’s quite likely that you’re feeling a little overwhelmed by all the technical lingo that gets thrown around. And who could blame you – “research methodology”, “research methods”, “sampling strategies”… it all seems never-ending!
In this post, we’ll demystify the landscape with plain-language explanations and loads of examples (including easy-to-follow videos), so that you can approach your dissertation, thesis or research project with confidence. Let’s get started.
What is research methodology?
Research methodology simply refers to the practical “how” of a research study. More specifically, it’s about how a researcher systematically designs a study to ensure valid and reliable results that address the research aims, objectives and research questions. Specifically, how the researcher went about deciding:
- What type of data to collect (e.g., qualitative or quantitative data)
- Who to collect it from (i.e., the sampling strategy)
- How to collect it (i.e., the data collection method)
- How to analyse it (i.e., the data analysis methods)
Within any formal piece of academic research (be it a dissertation, thesis or journal article), you’ll find a research methodology chapter or section which covers the aspects mentioned above. Importantly, a good methodology chapter explains not just what methodological choices were made, but also explains why they were made. In other words, the methodology chapter should justify the design choices, by showing that the chosen methods and techniques are the best fit for the research aims, objectives and research questions.
So, it’s the same as research design?
Not quite. As we mentioned, research methodology refers to the collection of practical decisions regarding what data you’ll collect, from who, how you’ll collect it and how you’ll analyse it. Research design, on the other hand, is more about the overall strategy you’ll adopt in your study. For example, whether you’ll use an experimental design in which you manipulate one variable while controlling others. You can learn more about research design and the various design types here.
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What are qualitative, quantitative
Qualitative, quantitative and mixed-methods are different types of methodological approaches, distinguished by their focus on words, numbers or both. This is a bit of an oversimplification, but its a good starting point for understanding.
Let’s take a closer look.
Qualitative research refers to research which focuses on collecting and analysing words (written or spoken) and textual or visual data, whereas quantitative research focuses on measurement and testing using numerical data. Qualitative analysis can also focus on other “softer” data points, such as body language or visual elements.
It’s quite common for a qualitative methodology to be used when the research aims and research questions are exploratory in nature. For example, a qualitative methodology might be used to understand peoples’ perceptions about an event that took place, or a political candidate running for president.
Contrasted to this, a quantitative methodology is typically used when the research aims and research questions are confirmatory in nature. For example, a quantitative methodology might be used to measure the relationship between two variables (e.g. personality type and likelihood to commit a crime) or to test a set of hypotheses.
As you’ve probably guessed, the mixed-method methodology attempts to combine the best of both qualitative and quantitative methodologies to integrate perspectives and create a rich picture. If you’d like to learn more about these three methodological approaches, be sure to watch our explainer video below.
What is sampling strategy?
Simply put, sampling is about deciding who (or where) you’re going to collect your data from. Why does this matter? Well, generally it’s not possible to collect data from every single person in your group of interest (this is called the “population”), so you’ll need to engage a smaller portion of that group that’s accessible and manageable (this is called the “sample”).
How you go about selecting the sample (i.e., your sampling strategy) will have a major impact on your study. There are many different sampling methods you can choose from, but the two overarching categories are probability sampling and non-probability sampling.
Probability sampling involves using a completely random sample from the group of people you’re interested in. This is comparable to throwing the names all potential participants into a hat, shaking it up, and picking out the “winners”. By using a completely random sample, you’ll minimise the risk of selection bias and the results of your study will be more generalisable to the entire population.
Non-probability sampling, on the other hand, doesn’t use a random sample. For example, it might involve using a convenience sample, which means you’d only interview or survey people that you have access to (perhaps your friends, family or work colleagues), rather than a truly random sample. With non-probability sampling, the results are typically not generalisable.
To learn more about sampling methods, be sure to check out the video below.
What are data collection methods?
As the name suggests, data collection methods simply refers to the way in which you go about collecting the data for your study. Some of the most common data collection methods include:
- Interviews (which can be unstructured, semi-structured or structured)
- Focus groups and group interviews
- Surveys (online or physical surveys)
- Observations (watching and recording activities)
- Biophysical measurements (e.g., blood pressure, heart rate, etc.)
- Documents and records (e.g., financial reports, court records, etc.)
The choice of which data collection method to use depends on your overall research aims and research questions, as well as practicalities and resource constraints. For example, if your research is exploratory in nature, qualitative methods such as interviews and focus groups would likely be a good fit. Conversely, if your research aims to measure specific variables or test hypotheses, large-scale surveys that produce large volumes of numerical data would likely be a better fit.
What are data analysis methods?
Data analysis methods refer to the methods and techniques that you’ll use to make sense of your data. These can be grouped according to whether the research is qualitative (words-based) or quantitative (numbers-based).
Popular data analysis methods in qualitative research include:
- Qualitative content analysis
- Thematic analysis
- Discourse analysis
- Narrative analysis
- Interpretative phenomenological analysis (IPA)
- Visual analysis (of photographs, videos, art, etc.)
Qualitative data analysis all begins with data coding, after which an analysis method is applied. In some cases, more than one analysis method is used, depending on the research aims and research questions. In the video below, we explore some common qualitative analysis methods, along with practical examples.
Moving on to the quantitative side of things, popular data analysis methods in this type of research include:
- Descriptive statistics (e.g. means, medians, modes)
- Inferential statistics (e.g. correlation, regression, structural equation modelling)
Again, the choice of which data collection method to use depends on your overall research aims and objectives, as well as practicalities and resource constraints. In the video below, we explain some core concepts central to quantitative analysis.
How do I choose a research methodology?
As you’ve probably picked up by now, your research aims and objectives have a major influence on the research methodology. So, the starting point for developing your research methodology is to take a step back and look at the big picture of your research, before you make methodology decisions. The first question you need to ask yourself is whether your research is exploratory or confirmatory in nature.
If your research aims and objectives are primarily exploratory in nature, your research will likely be qualitative and therefore you might consider qualitative data collection methods (e.g. interviews) and analysis methods (e.g. qualitative content analysis).
Conversely, if your research aims and objective are looking to measure or test something (i.e. they’re confirmatory), then your research will quite likely be quantitative in nature, and you might consider quantitative data collection methods (e.g. surveys) and analyses (e.g. statistical analysis).
Designing your research and working out your methodology is a large topic, which we cover extensively on the blog. For now, however, the key takeaway is that you should always start with your research aims, objectives and research questions (the golden thread). Every methodological choice you make needs align with those three components.
Example of a research methodology chapter
In the video below, we provide a detailed walkthrough of a research methodology from an actual dissertation, as well as an overview of our free methodology template.
Psst… there’s more (for free)
This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project.