structure of a qualitative dissertation

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Tips for a qualitative dissertation

Veronika Williams

17 October 2017

Tips for students

This blog is part of a series for Evidence-Based Health Care MSc students undertaking their dissertations.

Undertaking an MSc dissertation in Evidence-Based Health Care (EBHC) may be your first hands-on experience of doing qualitative research. I chatted to Dr. Veronika Williams, an experienced qualitative researcher, and tutor on the EBHC programme, to find out her top tips for producing a high-quality qualitative EBHC thesis.

1) Make the switch from a quantitative to a qualitative mindset

It’s not just about replacing numbers with words. Doing qualitative research requires you to adopt a different way of seeing and interpreting the world around you. Veronika asks her students to reflect on positivist and interpretivist approaches: If you come from a scientific or medical background, positivism is often the unacknowledged status quo. Be open to considering there are alternative ways to generate and understand knowledge.

2) Reflect on your role

Quantitative research strives to produce “clean” data unbiased by the context in which it was generated.  With qualitative methods, this is neither possible nor desirable.  Students should reflect on how their background and personal views shape the way they collect and analyse their data. This will not only add to the transparency of your work but will also help you interpret your findings.

3)  Don’t forget the theory

Qualitative researchers use theories as a lens through which they understand the world around them. Veronika suggests that students consider the theoretical underpinning to their own research at the earliest stages. You can read an article about why theories are useful in qualitative research  here.

4) Think about depth rather than breadth

Qualitative research is all about developing a deep and insightful understanding of the phenomenon/ concept you are studying. Be realistic about what you can achieve given the time constraints of an MSc.  Veronika suggests that collecting and analysing a smaller dataset well is preferable to producing a superficial, rushed analysis of a larger dataset.

5) Blur the boundaries between data collection, analysis and writing up

Veronika strongly recommends keeping a research diary or using memos to jot down your ideas as your research progresses. Not only do these add to your audit trail, these entries will help contribute to your first draft and the process of moving towards theoretical thinking. Qualitative researchers move back and forward between their dataset and manuscript as their ideas develop. This enriches their understanding and allows emerging theories to be explored.

6) Move beyond the descriptive

When analysing interviews, for example, it can be tempting to think that having coded your transcripts you are nearly there. This is not the case!  You need to move beyond the descriptive codes to conceptual themes and theoretical thinking in order to produce a high-quality thesis.  Veronika warns against falling into the pitfall of thinking writing up is, “Two interviews said this whilst three interviewees said that”.

7) It’s not just about the average experience

When analysing your data, consider the outliers or negative cases, for example, those that found the intervention unacceptable.  Although in the minority, these respondents will often provide more meaningful insight into the phenomenon or concept you are trying to study.

8) Bounce ideas

Veronika recommends sharing your emerging ideas and findings with someone else, maybe with a different background or perspective. This isn’t about getting to the “right answer” rather it offers you the chance to refine your thinking.  Be sure, though, to fully acknowledge their contribution in your thesis.

9) Be selective

In can be a challenge to meet the dissertation word limit.  It won’t be possible to present all the themes generated by your dataset so focus! Use quotes from across your dataset that best encapsulate the themes you are presenting.  Display additional data in the appendix.  For example, Veronika suggests illustrating how you moved from your coding framework to your themes.

10) Don’t panic!

There will be a stage during analysis and write up when it seems undoable.  Unlike quantitative researchers who begin analysis with a clear plan, qualitative research is more of a journey. Everything will fall into place by the end.  Be sure, though, to allow yourself enough time to make sense of the rich data qualitative research generates.

Related course:

Qualitative research methods.

Short Course

How To Write The Results/Findings Chapter

For qualitative studies (dissertations & theses).

By: Jenna Crossley (PhD). Expert Reviewed By: Dr. Eunice Rautenbach | August 2021

So, you’ve collected and analysed your qualitative data, and it’s time to write up your results chapter. But where do you start? In this post, we’ll guide you through the qualitative results chapter (also called the findings chapter), step by step. 

Overview: Qualitative Results Chapter

• What (exactly) the qualitative results chapter is
• What to include in your results chapter
• How to write up your results chapter
• A few tips and tricks to help you along the way
• Free results chapter template

What exactly is the results chapter?

The results chapter in a dissertation or thesis (or any formal academic research piece) is where you objectively and neutrally present the findings of your qualitative analysis (or analyses if you used multiple qualitative analysis methods ). This chapter can sometimes be combined with the discussion chapter (where you interpret the data and discuss its meaning), depending on your university’s preference.  We’ll treat the two chapters as separate, as that’s the most common approach.

In contrast to a quantitative results chapter that presents numbers and statistics, a qualitative results chapter presents data primarily in the form of words . But this doesn’t mean that a qualitative study can’t have quantitative elements – you could, for example, present the number of times a theme or topic pops up in your data, depending on the analysis method(s) you adopt.

Adding a quantitative element to your study can add some rigour, which strengthens your results by providing more evidence for your claims. This is particularly common when using qualitative content analysis. Keep in mind though that qualitative research aims to achieve depth, richness and identify nuances , so don’t get tunnel vision by focusing on the numbers. They’re just cream on top in a qualitative analysis.

So, to recap, the results chapter is where you objectively present the findings of your analysis, without interpreting them (you’ll save that for the discussion chapter). With that out the way, let’s take a look at what you should include in your results chapter.

What should you include in the results chapter?

As we’ve mentioned, your qualitative results chapter should purely present and describe your results , not interpret them in relation to the existing literature or your research questions . Any speculations or discussion about the implications of your findings should be reserved for your discussion chapter.

In your results chapter, you’ll want to talk about your analysis findings and whether or not they support your hypotheses (if you have any). Naturally, the exact contents of your results chapter will depend on which qualitative analysis method (or methods) you use. For example, if you were to use thematic analysis, you’d detail the themes identified in your analysis, using extracts from the transcripts or text to support your claims.

While you do need to present your analysis findings in some detail, you should avoid dumping large amounts of raw data in this chapter. Instead, focus on presenting the key findings and using a handful of select quotes or text extracts to support each finding . The reams of data and analysis can be relegated to your appendices.

While it’s tempting to include every last detail you found in your qualitative analysis, it is important to make sure that you report only that which is relevant to your research aims, objectives and research questions .  Always keep these three components, as well as your hypotheses (if you have any) front of mind when writing the chapter and use them as a filter to decide what’s relevant and what’s not.

Need a helping hand?

How do I write the results chapter?

Now that we’ve covered the basics, it’s time to look at how to structure your chapter. Broadly speaking, the results chapter needs to contain three core components – the introduction, the body and the concluding summary. Let’s take a look at each of these.

Section 1: Introduction

The first step is to craft a brief introduction to the chapter. This intro is vital as it provides some context for your findings. In your introduction, you should begin by reiterating your problem statement and research questions and highlight the purpose of your research . Make sure that you spell this out for the reader so that the rest of your chapter is well contextualised.

The next step is to briefly outline the structure of your results chapter. In other words, explain what’s included in the chapter and what the reader can expect. In the results chapter, you want to tell a story that is coherent, flows logically, and is easy to follow , so make sure that you plan your structure out well and convey that structure (at a high level), so that your reader is well oriented.

The introduction section shouldn’t be lengthy. Two or three short paragraphs should be more than adequate. It is merely an introduction and overview, not a summary of the chapter.

Pro Tip – To help you structure your chapter, it can be useful to set up an initial draft with (sub)section headings so that you’re able to easily (re)arrange parts of your chapter. This will also help your reader to follow your results and give your chapter some coherence.  Be sure to use level-based heading styles (e.g. Heading 1, 2, 3 styles) to help the reader differentiate between levels visually. You can find these options in Word (example below).

Section 2: Body

Before we get started on what to include in the body of your chapter, it’s vital to remember that a results section should be completely objective and descriptive, not interpretive . So, be careful not to use words such as, “suggests” or “implies”, as these usually accompany some form of interpretation – that’s reserved for your discussion chapter.

The structure of your body section is very important , so make sure that you plan it out well. When planning out your qualitative results chapter, create sections and subsections so that you can maintain the flow of the story you’re trying to tell. Be sure to systematically and consistently describe each portion of results. Try to adopt a standardised structure for each portion so that you achieve a high level of consistency throughout the chapter.

For qualitative studies, results chapters tend to be structured according to themes , which makes it easier for readers to follow. However, keep in mind that not all results chapters have to be structured in this manner. For example, if you’re conducting a longitudinal study, you may want to structure your chapter chronologically. Similarly, you might structure this chapter based on your theoretical framework . The exact structure of your chapter will depend on the nature of your study , especially your research questions.

As you work through the body of your chapter, make sure that you use quotes to substantiate every one of your claims . You can present these quotes in italics to differentiate them from your own words. A general rule of thumb is to use at least two pieces of evidence per claim, and these should be linked directly to your data. Also, remember that you need to include all relevant results , not just the ones that support your assumptions or initial leanings.

In addition to including quotes, you can also link your claims to the data by using appendices , which you should reference throughout your text. When you reference, make sure that you include both the name/number of the appendix , as well as the line(s) from which you drew your data.

As referencing styles can vary greatly, be sure to look up the appendix referencing conventions of your university’s prescribed style (e.g. APA , Harvard, etc) and keep this consistent throughout your chapter.

Section 3: Concluding summary

The concluding summary is very important because it summarises your key findings and lays the foundation for the discussion chapter . Keep in mind that some readers may skip directly to this section (from the introduction section), so make sure that it can be read and understood well in isolation.

In this section, you need to remind the reader of the key findings. That is, the results that directly relate to your research questions and that you will build upon in your discussion chapter. Remember, your reader has digested a lot of information in this chapter, so you need to use this section to remind them of the most important takeaways.

Importantly, the concluding summary should not present any new information and should only describe what you’ve already presented in your chapter. Keep it concise – you’re not summarising the whole chapter, just the essentials.

Tips for writing an A-grade results chapter

Now that you’ve got a clear picture of what the qualitative results chapter is all about, here are some quick tips and reminders to help you craft a high-quality chapter:

• Your results chapter should be written in the past tense . You’ve done the work already, so you want to tell the reader what you found , not what you are currently finding .
• Make sure that you review your work multiple times and check that every claim is adequately backed up by evidence . Aim for at least two examples per claim, and make use of an appendix to reference these.
• When writing up your results, make sure that you stick to only what is relevant . Don’t waste time on data that are not relevant to your research objectives and research questions.
• Use headings and subheadings to create an intuitive, easy to follow piece of writing. Make use of Microsoft Word’s “heading styles” and be sure to use them consistently.
• When referring to numerical data, tables and figures can provide a useful visual aid. When using these, make sure that they can be read and understood independent of your body text (i.e. that they can stand-alone). To this end, use clear, concise labels for each of your tables or figures and make use of colours to code indicate differences or hierarchy.
• Similarly, when you’re writing up your chapter, it can be useful to highlight topics and themes in different colours . This can help you to differentiate between your data if you get a bit overwhelmed and will also help you to ensure that your results flow logically and coherently.

If you have any questions, leave a comment below and we’ll do our best to help. If you’d like 1-on-1 help with your results chapter (or any chapter of your dissertation or thesis), check out our private dissertation coaching service here or book a free initial consultation to discuss how we can help you.

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21 Comments

This was extremely helpful. Thanks a lot guys

Hi, thanks for the great research support platform created by the gradcoach team!

I wanted to ask- While “suggests” or “implies” are interpretive terms, what terms could we use for the results chapter? Could you share some examples of descriptive terms?

I think that instead of saying, ‘The data suggested, or The data implied,’ you can say, ‘The Data showed or revealed, or illustrated or outlined’…If interview data, you may say Jane Doe illuminated or elaborated, or Jane Doe described… or Jane Doe expressed or stated.

I found this article very useful. Thank you very much for the outstanding work you are doing.

What if i have 3 different interviewees answering the same interview questions? Should i then present the results in form of the table with the division on the 3 perspectives or rather give a results in form of the text and highlight who said what?

I think this tabular representation of results is a great idea. I am doing it too along with the text. Thanks

That was helpful was struggling to separate the discussion from the findings

this was very useful, Thank you.

Very helpful, I am confident to write my results chapter now.

It is so helpful! It is a good job. Thank you very much!

Very useful, well explained. Many thanks.

Hello, I appreciate the way you provided a supportive comments about qualitative results presenting tips

I loved this! It explains everything needed, and it has helped me better organize my thoughts. What words should I not use while writing my results section, other than subjective ones.

Thanks a lot, it is really helpful

Thank you so much dear, i really appropriate your nice explanations about this.

Thank you so much for this! I was wondering if anyone could help with how to prproperly integrate quotations (Excerpts) from interviews in the finding chapter in a qualitative research. Please GradCoach, address this issue and provide examples.

what if I’m not doing any interviews myself and all the information is coming from case studies that have already done the research.

Very helpful thank you.

This was very helpful as I was wondering how to structure this part of my dissertation, to include the quotes… Thanks for this explanation

This is very helpful, thanks! I am required to write up my results chapters with the discussion in each of them – any tips and tricks for this strategy?

For qualitative studies, can the findings be structured according to the Research questions? Thank you.

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• Dissertation

How to Write a Dissertation | A Guide to Structure & Content

A dissertation or thesis is a long piece of academic writing based on original research, submitted as part of an undergraduate or postgraduate degree.

The structure of a dissertation depends on your field, but it is usually divided into at least four or five chapters (including an introduction and conclusion chapter).

The most common dissertation structure in the sciences and social sciences includes:

• An introduction to your topic
• A literature review that surveys relevant sources
• An explanation of your methodology
• An overview of the results of your research
• A discussion of the results and their implications
• A conclusion that shows what your research has contributed

Dissertations in the humanities are often structured more like a long essay , building an argument by analysing primary and secondary sources . Instead of the standard structure outlined here, you might organise your chapters around different themes or case studies.

Other important elements of the dissertation include the title page , abstract , and reference list . If in doubt about how your dissertation should be structured, always check your department’s guidelines and consult with your supervisor.

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Table of contents

Acknowledgements, table of contents, list of figures and tables, list of abbreviations, introduction, literature review / theoretical framework, methodology, reference list.

The very first page of your document contains your dissertation’s title, your name, department, institution, degree program, and submission date. Sometimes it also includes your student number, your supervisor’s name, and the university’s logo. Many programs have strict requirements for formatting the dissertation title page .

The title page is often used as cover when printing and binding your dissertation .

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The acknowledgements section is usually optional, and gives space for you to thank everyone who helped you in writing your dissertation. This might include your supervisors, participants in your research, and friends or family who supported you.

The abstract is a short summary of your dissertation, usually about 150-300 words long. You should write it at the very end, when you’ve completed the rest of the dissertation. In the abstract, make sure to:

• State the main topic and aims of your research
• Describe the methods you used
• Summarise the main results
• State your conclusions

Although the abstract is very short, it’s the first part (and sometimes the only part) of your dissertation that people will read, so it’s important that you get it right. If you’re struggling to write a strong abstract, read our guide on how to write an abstract .

In the table of contents, list all of your chapters and subheadings and their page numbers. The dissertation contents page gives the reader an overview of your structure and helps easily navigate the document.

All parts of your dissertation should be included in the table of contents, including the appendices. You can generate a table of contents automatically in Word.

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If you have used a lot of tables and figures in your dissertation, you should itemise them in a numbered list . You can automatically generate this list using the Insert Caption feature in Word.

If you have used a lot of abbreviations in your dissertation, you can include them in an alphabetised list of abbreviations so that the reader can easily look up their meanings.

If you have used a lot of highly specialised terms that will not be familiar to your reader, it might be a good idea to include a glossary . List the terms alphabetically and explain each term with a brief description or definition.

In the introduction, you set up your dissertation’s topic, purpose, and relevance, and tell the reader what to expect in the rest of the dissertation. The introduction should:

• Establish your research topic , giving necessary background information to contextualise your work
• Narrow down the focus and define the scope of the research
• Discuss the state of existing research on the topic, showing your work’s relevance to a broader problem or debate
• Clearly state your objectives and research questions , and indicate how you will answer them
• Give an overview of your dissertation’s structure

Everything in the introduction should be clear, engaging, and relevant to your research. By the end, the reader should understand the what , why and how of your research. Not sure how? Read our guide on how to write a dissertation introduction .

Before you start on your research, you should have conducted a literature review to gain a thorough understanding of the academic work that already exists on your topic. This means:

• Collecting sources (e.g. books and journal articles) and selecting the most relevant ones
• Critically evaluating and analysing each source
• Drawing connections between them (e.g. themes, patterns, conflicts, gaps) to make an overall point

In the dissertation literature review chapter or section, you shouldn’t just summarise existing studies, but develop a coherent structure and argument that leads to a clear basis or justification for your own research. For example, it might aim to show how your research:

• Addresses a gap in the literature
• Takes a new theoretical or methodological approach to the topic
• Proposes a solution to an unresolved problem
• Advances a theoretical debate
• Builds on and strengthens existing knowledge with new data

The literature review often becomes the basis for a theoretical framework , in which you define and analyse the key theories, concepts and models that frame your research. In this section you can answer descriptive research questions about the relationship between concepts or variables.

The methodology chapter or section describes how you conducted your research, allowing your reader to assess its validity. You should generally include:

• The overall approach and type of research (e.g. qualitative, quantitative, experimental, ethnographic)
• Your methods of collecting data (e.g. interviews, surveys, archives)
• Details of where, when, and with whom the research took place
• Your methods of analysing data (e.g. statistical analysis, discourse analysis)
• Tools and materials you used (e.g. computer programs, lab equipment)
• A discussion of any obstacles you faced in conducting the research and how you overcame them
• An evaluation or justification of your methods

Your aim in the methodology is to accurately report what you did, as well as convincing the reader that this was the best approach to answering your research questions or objectives.

Next, you report the results of your research . You can structure this section around sub-questions, hypotheses, or topics. Only report results that are relevant to your objectives and research questions. In some disciplines, the results section is strictly separated from the discussion, while in others the two are combined.

For example, for qualitative methods like in-depth interviews, the presentation of the data will often be woven together with discussion and analysis, while in quantitative and experimental research, the results should be presented separately before you discuss their meaning. If you’re unsure, consult with your supervisor and look at sample dissertations to find out the best structure for your research.

In the results section it can often be helpful to include tables, graphs and charts. Think carefully about how best to present your data, and don’t include tables or figures that just repeat what you have written  –  they should provide extra information or usefully visualise the results in a way that adds value to your text.

Full versions of your data (such as interview transcripts) can be included as an appendix .

The discussion  is where you explore the meaning and implications of your results in relation to your research questions. Here you should interpret the results in detail, discussing whether they met your expectations and how well they fit with the framework that you built in earlier chapters. If any of the results were unexpected, offer explanations for why this might be. It’s a good idea to consider alternative interpretations of your data and discuss any limitations that might have influenced the results.

The discussion should reference other scholarly work to show how your results fit with existing knowledge. You can also make recommendations for future research or practical action.

The dissertation conclusion should concisely answer the main research question, leaving the reader with a clear understanding of your central argument. Wrap up your dissertation with a final reflection on what you did and how you did it. The conclusion often also includes recommendations for research or practice.

In this section, it’s important to show how your findings contribute to knowledge in the field and why your research matters. What have you added to what was already known?

You must include full details of all sources that you have cited in a reference list (sometimes also called a works cited list or bibliography). It’s important to follow a consistent reference style . Each style has strict and specific requirements for how to format your sources in the reference list.

The most common styles used in UK universities are Harvard referencing and Vancouver referencing . Your department will often specify which referencing style you should use – for example, psychology students tend to use APA style , humanities students often use MHRA , and law students always use OSCOLA . M ake sure to check the requirements, and ask your supervisor if you’re unsure.

To save time creating the reference list and make sure your citations are correctly and consistently formatted, you can use our free APA Citation Generator .

Your dissertation itself should contain only essential information that directly contributes to answering your research question. Documents you have used that do not fit into the main body of your dissertation (such as interview transcripts, survey questions or tables with full figures) can be added as appendices .

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Home » Dissertation Methodology – Structure, Example and Writing Guide

Dissertation Methodology – Structure, Example and Writing Guide

• Table of Contents

Dissertation Methodology

In any research, the methodology chapter is one of the key components of your dissertation. It provides a detailed description of the methods you used to conduct your research and helps readers understand how you obtained your data and how you plan to analyze it. This section is crucial for replicating the study and validating its results.

Here are the basic elements that are typically included in a dissertation methodology:

• Introduction : This section should explain the importance and goals of your research .
• Research Design : Outline your research approach and why it’s appropriate for your study. You might be conducting an experimental research, a qualitative research, a quantitative research, or a mixed-methods research.
• Data Collection : This section should detail the methods you used to collect your data. Did you use surveys, interviews, observations, etc.? Why did you choose these methods? You should also include who your participants were, how you recruited them, and any ethical considerations.
• Data Analysis : Explain how you intend to analyze the data you collected. This could include statistical analysis, thematic analysis, content analysis, etc., depending on the nature of your study.
• Reliability and Validity : Discuss how you’ve ensured the reliability and validity of your study. For instance, you could discuss measures taken to reduce bias, how you ensured that your measures accurately capture what they were intended to, or how you will handle any limitations in your study.
• Ethical Considerations : This is where you state how you have considered ethical issues related to your research, how you have protected the participants’ rights, and how you have complied with the relevant ethical guidelines.
• Limitations : Acknowledge any limitations of your methodology, including any biases and constraints that might have affected your study.
• Summary : Recap the key points of your methodology chapter, highlighting the overall approach and rationalization of your research.

Types of Dissertation Methodology

The type of methodology you choose for your dissertation will depend on the nature of your research question and the field you’re working in. Here are some of the most common types of methodologies used in dissertations:

Experimental Research

This involves creating an experiment that will test your hypothesis. You’ll need to design an experiment, manipulate variables, collect data, and analyze that data to draw conclusions. This is commonly used in fields like psychology, biology, and physics.

Survey Research

This type of research involves gathering data from a large number of participants using tools like questionnaires or surveys. It can be used to collect a large amount of data and is often used in fields like sociology, marketing, and public health.

Qualitative Research

This type of research is used to explore complex phenomena that can’t be easily quantified. Methods include interviews, focus groups, and observations. This methodology is common in fields like anthropology, sociology, and education.

Quantitative Research

Quantitative research uses numerical data to answer research questions. This can include statistical, mathematical, or computational techniques. It’s common in fields like economics, psychology, and health sciences.

Case Study Research

This type of research involves in-depth investigation of a particular case, such as an individual, group, or event. This methodology is often used in psychology, social sciences, and business.

Mixed Methods Research

This combines qualitative and quantitative research methods in a single study. It’s used to answer more complex research questions and is becoming more popular in fields like social sciences, health sciences, and education.

Action Research

This type of research involves taking action and then reflecting upon the results. This cycle of action-reflection-action continues throughout the study. It’s often used in fields like education and organizational development.

Longitudinal Research

This type of research involves studying the same group of individuals over an extended period of time. This could involve surveys, observations, or experiments. It’s common in fields like psychology, sociology, and medicine.

Ethnographic Research

This type of research involves the in-depth study of people and cultures. Researchers immerse themselves in the culture they’re studying to collect data. This is often used in fields like anthropology and social sciences.

Structure of Dissertation Methodology

The structure of a dissertation methodology can vary depending on your field of study, the nature of your research, and the guidelines of your institution. However, a standard structure typically includes the following elements:

• Introduction : Briefly introduce your overall approach to the research. Explain what you plan to explore and why it’s important.
• Research Design/Approach : Describe your overall research design. This can be qualitative, quantitative, or mixed methods. Explain the rationale behind your chosen design and why it is suitable for your research questions or hypotheses.
• Data Collection Methods : Detail the methods you used to collect your data. You should include what type of data you collected, how you collected it, and why you chose this method. If relevant, you can also include information about your sample population, such as how many people participated, how they were chosen, and any relevant demographic information.
• Data Analysis Methods : Explain how you plan to analyze your collected data. This will depend on the nature of your data. For example, if you collected quantitative data, you might discuss statistical analysis techniques. If you collected qualitative data, you might discuss coding strategies, thematic analysis, or narrative analysis.
• Reliability and Validity : Discuss how you’ve ensured the reliability and validity of your research. This might include steps you took to reduce bias or increase the accuracy of your measurements.
• Ethical Considerations : If relevant, discuss any ethical issues associated with your research. This might include how you obtained informed consent from participants, how you ensured participants’ privacy and confidentiality, or any potential conflicts of interest.
• Limitations : Acknowledge any limitations in your research methodology. This could include potential sources of bias, difficulties with data collection, or limitations in your analysis methods.
• Summary/Conclusion : Briefly summarize the key points of your methodology, emphasizing how it helps answer your research questions or hypotheses.

How to Write Dissertation Methodology

Writing a dissertation methodology requires you to be clear and precise about the way you’ve carried out your research. It’s an opportunity to convince your readers of the appropriateness and reliability of your approach to your research question. Here is a basic guideline on how to write your methodology section:

1. Introduction

Start your methodology section by restating your research question(s) or objective(s). This ensures your methodology directly ties into the aim of your research.

2. Approach

Identify your overall approach: qualitative, quantitative, or mixed methods. Explain why you have chosen this approach.

• Qualitative methods are typically used for exploratory research and involve collecting non-numerical data. This might involve interviews, observations, or analysis of texts.
• Quantitative methods are used for research that relies on numerical data. This might involve surveys, experiments, or statistical analysis.
• Mixed methods use a combination of both qualitative and quantitative research methods.

3. Research Design

Describe the overall design of your research. This could involve explaining the type of study (e.g., case study, ethnography, experimental research, etc.), how you’ve defined and measured your variables, and any control measures you’ve implemented.

4. Data Collection

Explain in detail how you collected your data.

• If you’ve used qualitative methods, you might detail how you selected participants for interviews or focus groups, how you conducted observations, or how you analyzed existing texts.
• If you’ve used quantitative methods, you might detail how you designed your survey or experiment, how you collected responses, and how you ensured your data is reliable and valid.

5. Data Analysis

Describe how you analyzed your data.

• If you’re doing qualitative research, this might involve thematic analysis, discourse analysis, or grounded theory.
• If you’re doing quantitative research, you might be conducting statistical tests, regression analysis, or factor analysis.

Discuss any ethical issues related to your research. This might involve explaining how you obtained informed consent, how you’re protecting participants’ privacy, or how you’re managing any potential harms to participants.

7. Reliability and Validity

Discuss the steps you’ve taken to ensure the reliability and validity of your data.

• Reliability refers to the consistency of your measurements, and you might discuss how you’ve piloted your instruments or used standardized measures.
• Validity refers to the accuracy of your measurements, and you might discuss how you’ve ensured your measures reflect the concepts they’re supposed to measure.

8. Limitations

Every study has its limitations. Discuss the potential weaknesses of your chosen methods and explain any obstacles you faced in your research.

9. Conclusion

Summarize the key points of your methodology, emphasizing how it helps to address your research question or objective.

Example of Dissertation Methodology

An Example of Dissertation Methodology is as follows:

Chapter 3: Methodology

• Introduction

This chapter details the methodology adopted in this research. The study aimed to explore the relationship between stress and productivity in the workplace. A mixed-methods research design was used to collect and analyze data.

Research Design

This study adopted a mixed-methods approach, combining quantitative surveys with qualitative interviews to provide a comprehensive understanding of the research problem. The rationale for this approach is that while quantitative data can provide a broad overview of the relationships between variables, qualitative data can provide deeper insights into the nuances of these relationships.

Data Collection Methods

Quantitative Data Collection : An online self-report questionnaire was used to collect data from participants. The questionnaire consisted of two standardized scales: the Perceived Stress Scale (PSS) to measure stress levels and the Individual Work Productivity Questionnaire (IWPQ) to measure productivity. The sample consisted of 200 office workers randomly selected from various companies in the city.

Qualitative Data Collection : Semi-structured interviews were conducted with 20 participants chosen from the initial sample. The interview guide included questions about participants’ experiences with stress and how they perceived its impact on their productivity.

Data Analysis Methods

Quantitative Data Analysis : Descriptive and inferential statistics were used to analyze the survey data. Pearson’s correlation was used to examine the relationship between stress and productivity.

Qualitative Data Analysis : Interviews were transcribed and subjected to thematic analysis using NVivo software. This process allowed for identifying and analyzing patterns and themes regarding the impact of stress on productivity.

Reliability and Validity

To ensure reliability and validity, standardized measures with good psychometric properties were used. In qualitative data analysis, triangulation was employed by having two researchers independently analyze the data and then compare findings.

Ethical Considerations

All participants provided informed consent prior to their involvement in the study. They were informed about the purpose of the study, their rights as participants, and the confidentiality of their responses.

Limitations

The main limitation of this study is its reliance on self-report measures, which can be subject to biases such as social desirability bias. Moreover, the sample was drawn from a single city, which may limit the generalizability of the findings.

Where to Write Dissertation Methodology

In a dissertation or thesis, the Methodology section usually follows the Literature Review. This placement allows the Methodology to build upon the theoretical framework and existing research outlined in the Literature Review, and precedes the Results or Findings section. Here’s a basic outline of how most dissertations are structured:

• Acknowledgements
• Literature Review (or it may be interspersed throughout the dissertation)
• Methodology
• Results/Findings
• References/Bibliography

In the Methodology chapter, you will discuss the research design, data collection methods, data analysis methods, and any ethical considerations pertaining to your study. This allows your readers to understand how your research was conducted and how you arrived at your results.

Advantages of Dissertation Methodology

The dissertation methodology section plays an important role in a dissertation for several reasons. Here are some of the advantages of having a well-crafted methodology section in your dissertation:

• Clarifies Your Research Approach : The methodology section explains how you plan to tackle your research question, providing a clear plan for data collection and analysis.
• Enables Replication : A detailed methodology allows other researchers to replicate your study. Replication is an important aspect of scientific research because it provides validation of the study’s results.
• Demonstrates Rigor : A well-written methodology shows that you’ve thought critically about your research methods and have chosen the most appropriate ones for your research question. This adds credibility to your study.
• Enhances Transparency : Detailing your methods allows readers to understand the steps you took in your research. This increases the transparency of your study and allows readers to evaluate potential biases or limitations.
• Helps in Addressing Research Limitations : In your methodology section, you can acknowledge and explain the limitations of your research. This is important as it shows you understand that no research method is perfect and there are always potential weaknesses.
• Facilitates Peer Review : A detailed methodology helps peer reviewers assess the soundness of your research design. This is an important part of the publication process if you aim to publish your dissertation in a peer-reviewed journal.
• Establishes the Validity and Reliability : Your methodology section should also include a discussion of the steps you took to ensure the validity and reliability of your measurements, which is crucial for establishing the overall quality of your research.

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Qualitative research

In this section on Qualitative Research  you can find out about:

You might also want to consult our other sections on  Planning your research ,  Quantitative research  and  Writing up research , and check out the Additional resources .

• << Previous: Approaches to quantitative research
• Next: Developing a theoretical framework >>

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• What Is Qualitative Research? | Methods & Examples

What Is Qualitative Research? | Methods & Examples

Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.

Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.

Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.

Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.

• How does social media shape body image in teenagers?
• How do children and adults interpret healthy eating in the UK?
• What factors influence employee retention in a large organization?
• How is anxiety experienced around the world?
• How can teachers integrate social issues into science curriculums?

Table of contents

Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.

Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.

Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.

Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.

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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:

• Observations: recording what you have seen, heard, or encountered in detailed field notes.
• Interviews:  personally asking people questions in one-on-one conversations.
• Focus groups: asking questions and generating discussion among a group of people.
• Surveys : distributing questionnaires with open-ended questions.
• Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
• You take field notes with observations and reflect on your own experiences of the company culture.
• You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
• You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.

Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.

For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.

Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.

Most types of qualitative data analysis share the same five steps:

• Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
• Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
• Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
• Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
• Identify recurring themes. Link codes together into cohesive, overarching themes.

There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.

Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:

• Flexibility

The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.

• Natural settings

Data collection occurs in real-world contexts or in naturalistic ways.

• Meaningful insights

Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.

• Generation of new ideas

Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.

Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:

• Unreliability

The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.

• Subjectivity

Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.

• Limited generalizability

Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .

• Labor-intensive

Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Chi square goodness of fit test
• Degrees of freedom
• Null hypothesis
• Discourse analysis
• Control groups
• Mixed methods research
• Non-probability sampling
• Quantitative research
• Inclusion and exclusion criteria

Research bias

• Rosenthal effect
• Implicit bias
• Cognitive bias
• Selection bias
• Negativity bias
• Status quo bias

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organization to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organize your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

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How to write the analysis and discussion chapters in qualitative (SSAH) research

By charlesworth author services.

• Charlesworth Author Services
• 11 November, 2021

While it is more common for Science, Technology, Engineering and Mathematics (STEM) researchers to write separate, distinct chapters for their data/ results and analysis/ discussion , the same sections can feel less clearly defined for a researcher in Social Sciences, Arts and Humanities (SSAH). This article will look specifically at some useful approaches to writing the analysis and discussion chapters in qualitative/SSAH research.

Note : Most of the differences in approaches to research, writing, analysis and discussion come down, ultimately, to differences in epistemology – how we approach, create and work with knowledge in our respective fields. However, this is a vast topic that deserves a separate discussion.

Look for emerging themes and patterns

The ‘results’ of qualitative research can sometimes be harder to pinpoint than in quantitative research. You’re not dealing with definitive numbers and results in the same way as, say, a scientist conducting experiments that produce measurable data. Instead, most qualitative researchers explore prominent, interesting themes and patterns emerging from their data – that could comprise interviews, textual material or participant observation, for example. 

You may find that your data presents a huge number of themes, issues and topics, all of which you might find equally significant and interesting. In fact, you might find yourself overwhelmed by the many directions that your research could take, depending on which themes you choose to study in further depth. You may even discover issues and patterns that you had not expected , that may necessitate having to change or expand the research focus you initially started off with.

It is crucial at this point not to panic. Instead, try to enjoy the many possibilities that your data is offering you. It can be useful to remind yourself at each stage of exactly what you are trying to find out through this research.

What exactly do you want to know? What knowledge do you want to generate and share within your field?

Then, spend some time reflecting upon each of the themes that seem most interesting and significant, and consider whether they are immediately relevant to your main, overarching research objectives and goals.

Suggestion: Don’t worry too much about structure and flow at the early stages of writing your discussion . It would be a more valuable use of your time to fully explore the themes and issues arising from your data first, while also reading widely alongside your writing (more on this below). As you work more intimately with the data and develop your ideas, the overarching narrative and connections between those ideas will begin to emerge. Trust that you’ll be able to draw those links and craft the structure organically as you write.

Let your data guide you

A key characteristic of qualitative research is that the researchers allow their data to ‘speak’ and guide their research and their writing. Instead of insisting too strongly upon the prominence of specific themes and issues and imposing their opinions and beliefs upon the data, a good qualitative researcher ‘listens’ to what the data has to tell them.

Again, you might find yourself having to address unexpected issues or your data may reveal things that seem completely contradictory to the ideas and theories you have worked with so far. Although this might seem worrying, discovering these unexpected new elements can actually make your research much richer and more interesting. 

Suggestion: Allow yourself to follow those leads and ask new questions as you work through your data. These new directions could help you to answer your research questions in more depth and with greater complexity; or they could even open up other avenues for further study, either in this or future research.

Work closely with the literature

As you analyse and discuss the prominent themes, arguments and findings arising from your data, it is very helpful to maintain a regular and consistent reading practice alongside your writing. Return to the literature that you’ve already been reading so far or begin to check out new texts, studies and theories that might be more appropriate for working with any new ideas and themes arising from your data.

Reading and incorporating relevant literature into your writing as you work through your analysis and discussion will help you to consistently contextualise your research within the larger body of knowledge. It will be easier to stay focused on what you are trying to say through your research if you can simultaneously show what has already been said on the subject and how your research and data supports, challenges or extends those debates. By drawing from existing literature , you are setting up a dialogue between your research and prior work, and highlighting what this research has to add to the conversation.

Suggestion : Although it might sometimes feel tedious to have to blend others’ writing in with yours, this is ultimately the best way to showcase the specialness of your own data, findings and research . Remember that it is more difficult to highlight the significance and relevance of your original work without first showing how that work fits into or responds to existing studies. 

In conclusion

The discussion chapters form the heart of your thesis and this is where your unique contribution comes to the forefront. This is where your data takes centre-stage and where you get to showcase your original arguments, perspectives and knowledge. To do this effectively needs you to explore the original themes and issues arising from and within the data, while simultaneously contextualising these findings within the larger, existing body of knowledge of your specialising field. By striking this balance, you prove the two most important qualities of excellent qualitative research : keen awareness of your field and a firm understanding of your place in it.

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How To Write the Findings Chapter for Qualitative Studies

Writing the findings chapter for qualitative studies is a critical step in the research process. This chapter allows researchers to present their findings, analyze the data collected, and draw conclusions based on the study’s objectives. In this blog post, I’lll explore the purpose, key elements, preparation, writing, and presentation of the findings chapter in qualitative studies.

Introduction: Contextualizing Your Findings

The introductory section serves as the gateway to your qualitative findings chapter. Begin by reiterating your problem statement and research questions, setting the stage for the data that will be presented. Highlighting the purpose of your research is crucial at this point to give context to the reader.

Example: The primary aim of this case study is to explore how educators perceive the integration of artificial intelligence (AI) tools in K-12 education settings. This research seeks to understand the perceptions and experiences of educators who have implemented AI technologies in their classrooms, framed within the context of Technological Pedagogical Content Knowledge (TPACK). In this chapter, data are systematically organized into three overarching themes, each comprising sub-themes that provide a nuanced understanding of the participants’ perspectives. The research questions guiding this investigation were: (1) What are educators’ perceptions of the role of AI tools in K-12 classrooms? (2) How do educators navigate the challenges of integrating AI tools into their teaching practices? The answers to these questions are integral to understanding the complex dynamics of AI implementation in educational contexts.  

Overview of Findings

Following this, offer a brief overview of your main findings. While you should not delve into the details here, giving the reader an idea of what to expect can be helpful. Explain the overall structure of your results chapter and how you’ve organized it to maintain coherence and logical flow.

The Heart of the Matter: The Body of Your Chapter

Presentation.

The body of the chapter is where you lay out your data for the reader. In qualitative research, this usually means dividing your data into themes or categories, which should be clearly described and substantiated with quotes and examples from your dataset. These themes provide the skeletal framework upon which your narrative is built.

Structure and Flow

When planning your qualitative findings chapter, carefully outline the sections and subsections to maintain the flow of the writing and improve readability. You can structure your chapter based on themes, which is often the case in qualitative research, but other formats like chronological or framework-based structures may be more appropriate depending on your specific research design.

✅ Consistency is Key: Make sure each portion of findings adheres to a standardized structure. This enhances consistency and enables the reader to follow your line of reasoning.

Objective and Descriptive Language

While your narrative might touch upon individual experiences and perspectives, remember to maintain an objective tone. Your task is to describe, not interpret—that comes later, in the Discussion chapter. Thus, avoid phrases that suggest interpretation, such as “suggests” or “implies.”

Visual Aids

Tables, figures, and other visual aids can add another layer of comprehension and break up the text, but make sure they can be understood independently of your body text. Label them clearly and use color coding judiciously to indicate differences or hierarchy.

Data Analysis and Interpretation

As you delve into the data, aim to narrate a coherent story. Interpret your findings in light of the literature in the field and your theoretical framework, but remember to clearly differentiate between your descriptions and your interpretations.

✅ References and Appendices: When using quotes or data excerpts, reference them appropriately. Use appendices to present additional data and ensure that you cite them according to the referencing style prescribed by your institution (e.g., APA, Harvard).

Bringing It All Together: The Concluding Summary

This is the section where you summarize your key findings in a concise manner, reiterating points that directly relate to your research questions. It serves as a stepping stone to the Discussion chapter, providing the reader with the essential takeaways. As a rule of thumb, this section should contain no new information.

Additional Tips and Tricks

– Write in the past tense, as you present findings that have already been gathered.

– Review your work multiple times, ensuring each theme or finding is backed by sufficient data.

– Use Microsoft Word’s “heading styles” for consistency.

Final Thoughts

With the right approach, writing the Findings chapter can be an enriching experience that showcases your research and prepares you for discussions and conclusions that follow. The tips and guidelines presented here are meant to make this crucial chapter as clear and impactful as possible, helping you make a valuable contribution to your field of study.

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