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Dissertation methodology: how to write a methodology chapter (chapter 3)
The methodology chapter explains how you did your research and why you did it that way. An examiner reads it to judge one thing: can the findings that follow be trusted? A clear methodology makes the rest of the dissertation or thesis easier to defend.
This guide shows how to write a dissertation methodology step by step. It covers what a methodology should include, how long it should be, and how to describe your design, sample, data collection, analysis, quality checks, ethics and limitations. The same advice works for a methodology section in a research paper.
What is a dissertation methodology?
The methodology is the chapter or section that describes and justifies your research process. It answers four questions:
- What type of study did you do?
- Who or what did you study, and how did you choose them?
- How did you collect and analyse the data?
- Why were these the right choices for your research questions?
Methodology or method? The two words are often mixed up. Methods are the tools and steps: a questionnaire, an interview, a t-test. Methodology is the reasoning behind them: why those methods suit your question. A good chapter does both. It describes the methods and explains the methodology.
Chapter 3 research methodology: a note on names
In many Nigerian universities, and in other places that use a five-chapter structure, the methodology is Chapter Three, often titled "Research Methodology" or "Methodology". Chapter One is usually the introduction, Chapter Two the literature review, Chapter Four the results or data analysis, and Chapter Five the discussion, summary and conclusion.
In the UK, Ireland and many other places, the chapter may simply be called "Methodology" or "Methods", and its number depends on your structure. The content is much the same. Always use the headings and order your department gives you.
What should a methodology include?
Most methodology chapters cover these parts, in roughly this order:
- A short introduction that restates the research questions.
- Research design and approach.
- Population, sample and sampling technique.
- Research instruments and data collection.
- Data analysis.
- Validity and reliability (or trustworthiness for qualitative work).
- Ethical considerations.
- Limitations.
- A short summary.
Some departments also ask for the study area, a pilot study or the philosophical position (for example, positivism or interpretivism). Include them if your guidelines do.
How to write a methodology chapter, section by section
1. Restate your research questions
Open with one short paragraph that reminds the reader of your aim and research questions. Everything in the chapter should link back to them. If a choice does not help answer a question, ask why it is there.
2. Research design and approach
Your research design is the overall plan. Your approach is the type of data you work with:
- Quantitative. Numbers and measurement. Common designs are surveys, experiments and correlational studies. Use it when you want to measure how much, how many or how strongly things are related.
- Qualitative. Words, meanings and experiences. Common designs are case studies, interviews, focus groups and ethnography. Use it when you want to understand how or why people think and act as they do.
- Mixed methods. Both, combined in a planned way. Use it when one kind of data alone cannot answer your questions. Say how and when the two parts connect.
Do not just name your design. Justify it. Say why it fits your questions better than the alternatives.
3. Population, sample and sampling technique
Define the population: the full group your study is about. Then describe your sample: the people, cases or documents you actually studied, and how many.
Name your sampling technique and explain why you used it.
- Probability sampling (for example simple random, stratified or cluster sampling) gives each member a known chance of selection. It suits quantitative studies that aim to generalise.
- Non-probability sampling (for example purposive, convenience or snowball sampling) selects people for a reason or for access. It is common in qualitative studies, where depth matters more than numbers.
Explain how you decided the sample size. For a survey, that may be a formula or a published table. For interviews, it may be the point at which new interviews stopped adding new ideas. Be honest about who took part and who did not.
4. Research instruments and data collection
Describe the tools you used: a questionnaire, interview guide, observation checklist, test or existing dataset. Say where each came from. Did you design it, adapt it from an earlier study, or use it as published? If you adapted a tool, cite the original.
Then explain how you collected the data: when, where, by whom, and in what form (paper, online, phone, face to face). Mention any pilot test and what you changed after it.
5. Data analysis
Explain how you turned raw data into findings. Be specific enough that another researcher could repeat it.
- Quantitative data. Say how you cleaned and coded the data, then name the analysis: descriptive statistics such as frequencies, means and percentages, and any tests such as chi-square, t-tests, ANOVA, correlation or regression. Name the software, for example SPSS, Stata or Excel, and state the significance level you used. Our guide on how to choose the right statistical test shows how to match each test to your objectives and data.
- Qualitative data. Say how you prepared the data (for example, transcribing interviews), then name the analysis, such as thematic analysis or content analysis. Explain how you coded the data and built themes. If you used software such as NVivo, say what you used it for. The software organises the data; you still do the thinking. Our guide on how to analyse qualitative data walks through thematic analysis step by step.
Link each analysis to the research question it answers. Our guide to data analysis in research explains the main methods and steps in more detail.
6. Validity and reliability, or trustworthiness
Show the reader why they can trust your results.
- Validity asks whether you measured what you meant to measure. You might show this by basing questions on earlier tools, asking experts to review the instrument, or piloting it.
- Reliability asks whether the measure is consistent. For a scale in a questionnaire, researchers often report an internal-consistency statistic such as Cronbach’s alpha.
- Trustworthiness is the usual term in qualitative research. It is often discussed as credibility, transferability, dependability and confirmability. You might show it with detailed descriptions, an audit trail of decisions, checking interpretations with participants, or reflecting on your own role.
7. Ethical considerations
Explain how you protected participants. Cover informed consent, voluntary participation, confidentiality or anonymity, safe storage of data and any approval you obtained from an ethics committee. If your study involved children, patients or other vulnerable groups, say what extra care you took.
8. Limitations
Every study has limits. Name the main ones honestly: a small or non-random sample, self-reported data, a short time frame, or access problems. Then say what you did to reduce their effect and what they mean for your conclusions. Examiners trust a researcher who sees the limits of their own work.
An illustrative example
The example below is made up to show the style. It is not from a real study.
This study used a quantitative cross-sectional survey design to examine the relationship between digital skills training and job-search activity among recent graduates in Kaduna State. A survey suited the aim because it allowed the same questions to be asked of a large group and the answers to be compared. The population was graduates who completed their first degree in the previous two years. A stratified random sample was drawn by field of study, so that each field was represented. Data were collected with an online questionnaire adapted from earlier studies and piloted with a small group of graduates outside the sample. The data were cleaned in Excel and analysed in SPSS using frequencies, percentages and chi-square tests, with significance set at 0.05. Participants gave informed consent and no names were recorded.
Notice what it does. Each sentence states a choice and, where it matters, the reason for it.
How long should a methodology be?
There is no fixed rule. It depends on your field, your design and your total word count. Your department handbook or supervisor is the best guide, so check there first. What matters more than length is that every choice is described and justified. A shorter, specific chapter is better than a long one full of textbook definitions.
Methodology in a proposal vs a final dissertation
You write about your methodology twice: once in the proposal, and again in the final dissertation. The two are not the same.
- In the proposal, you describe what you will do, mostly in the future tense. You show the plan is sound and realistic. Our guide on how to write a research proposal shows where this fits.
- In the final dissertation, you describe what you did, in the past tense. You report what actually happened, including changes to the plan, the final sample, response rates and any problems in the field, and you explain why.
Do not just copy the proposal into the final chapter. Update it so it matches what really happened.
Common mistakes to avoid
- Too much textbook theory. Long definitions of every design waste words. Explain your own choices.
- Description without justification. Say why, not only what.
- Methods that do not match the questions. Each question needs a clear way to be answered.
- Vague analysis. "Data were analysed statistically" is not enough. Name the tests and the software.
- Ignoring quality and ethics. Validity, reliability or trustworthiness, and ethics, all need their own space.
- Hiding limitations. Examiners notice. Name them and explain their effect.
- Mixed tenses. Use the past tense for what you did in the final dissertation.
Methodology checklist
- Research questions restated
- Design and approach named and justified
- Population, sample and sampling technique explained
- Instruments described, sourced and piloted
- Analysis named, with software, for each question
- Validity and reliability or trustworthiness shown
- Ethics, consent and data storage explained
- Limitations stated honestly
- Headings follow your department’s guidelines
Want an expert review of your methodology?
Erudite Digital Team is a research consultancy led by Eliakim Anzizi, PhD. We review methodology chapters for clarity and fit between questions, design and analysis. We also analyse quantitative and qualitative data in SPSS, NVivo, Excel and Stata, and explain the results in plain English. See our data analysis and proofreading and editing services, or start with our free services.
Frequently asked questions
What should a dissertation methodology include?
Usually the research design and approach, population and sampling, instruments and data collection, data analysis, validity and reliability or trustworthiness, ethics and limitations. Follow the headings your department gives you.
What is the difference between methodology and methods?
Methods are the tools and steps you used, such as a survey or interviews. Methodology is the reasoning that explains why those methods suit your research question.
How long should a methodology be?
There is no fixed length. It depends on your field, design and total word count. Check your department handbook or ask your supervisor.
What are the parts of chapter 3 research methodology?
In a five-chapter structure, Chapter Three usually covers the research design, study area or population, sample and sampling technique, instruments, validity and reliability, data collection, data analysis and ethical considerations.
What tense is a methodology written in?
In a proposal, mostly the future tense, for what you will do. In the final dissertation, the past tense, for what you did.
Want your methodology checked before you submit? Send your chapter and research questions on WhatsApp or by email. We reply with a clear plan. See our data analysis service.
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