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What is a theoretical framework?

Developing a theoretical framework for your dissertation is one of the key elements of a qualitative research project. Through writing your literature review, you are likely to have identified either a problem that need ‘fixing’ or a gap that your research may begin to fill.

The theoretical framework is your toolbox . In the toolbox are your handy tools: a set of theories, concepts, ideas and hypotheses that you will use to build a solution to the research problem or gap you have identified.

The methodology is the instruction manual: the procedure and steps you have taken, using your chosen tools, to tackle the research problem.

Why do I need a theoretical framework?

Developing a theoretical framework shows that you have thought critically about the different ways to approach your topic, and that you have made a well-reasoned and evidenced decision about which approach will work best. theoretical frameworks are also necessary for solving complex problems or issues from the literature, showing that you have the skills to think creatively and improvise to answer your research questions. they also allow researchers to establish new theories and approaches, that future research may go on to develop., how do i create a theoretical framework for my dissertation.

First, select your tools. You are likely to need a variety of tools in qualitative research – different theories, models or concepts – to help you tackle different parts of your research question.  

When deciding what tools would be best for the job of answering your research questions or problem, explore what existing research in your area has used. You may find that there is a ‘standard toolbox’ for qualitative research in your field that you can borrow from or apply to your own research.

You will need to justify why your chosen tools are best for the job of answering your research questions, at what stage they are most relevant, and how they relate to each other. Some theories or models will neatly fit together and appear in the toolboxes of other researchers. However, you may wish to incorporate a model or idea that is not typical for your research area – the ‘odd one out’ in your toolbox. If this is the case, make sure you justify and account for why it is useful to you, and look for ways that it can be used in partnership with the other tools you are using.

You should also be honest about limitations, or where you need to improvise (for example, if the ‘right’ tool or approach doesn’t exist in your area).

This video from the Skills Centre includes an overview and example of how you might create a theoretical framework for your dissertation:

How do I choose the 'right' approach?

When designing your framework and choosing what to include, it can often be difficult to know if you’ve chosen the ‘right’ approach for your research questions. One way to check this is to look for consistency between your objectives, the literature in your framework, and your overall ethos for the research. This means ensuring that the literature you have used not only contributes to answering your research objectives, but that you also use theories and models that are true to your beliefs as a researcher.

Reflecting on your values and your overall ambition for the project can be a helpful step in making these decisions, as it can help you to fully connect your methodology and methods to your research aims.

Should I reflect on my position as a researcher?

If you feel your position as a researcher has influenced your choice of methods or procedure in any way, the methodology is a good place to reflect on this.  Positionality  acknowledges that no researcher is entirely objective: we are all, to some extent, influenced by prior learning, experiences, knowledge, and personal biases. This is particularly true in qualitative research or practice-based research, where the student is acting as a researcher in their own workplace, where they are otherwise considered a practitioner/professional. It's also important to reflect on your positionality if you belong to the same community as your participants where this is the grounds for their involvement in the research (ie. you are a mature student interviewing other mature learners about their experences in higher education). 

The following questions can help you to reflect on your positionality and gauge whether this is an important section to include in your dissertation (for some people, this section isn’t necessary or relevant):

• How might my personal history influence how I approach the topic?
• How am I positioned in relation to this knowledge? Am I being influenced by prior learning or knowledge from outside of this course?
• How does my gender/social class/ ethnicity/ culture influence my positioning in relation to this topic?
• Do I share any attributes with my participants? Are we part of a s hared community? How might this have influenced our relationship and my role in interviews/observations?
• Am I invested in the outcomes on a personal level? Who is this research for and who will feel the benefits?

One option for qualitative projects is to write an extended literature review. This type of project does not require you to collect any new data. Instead, you should focus on synthesising a broad range of literature to offer a new perspective on a research problem or question.  

The main difference between an extended literature review and a dissertation where primary data is collected, is in the presentation of the methodology, results and discussion sections. This is because extended literature reviews do not actively involve participants or primary data collection, so there is no need to outline a procedure for data collection (the methodology) or to present and interpret ‘data’ (in the form of interview transcripts, numerical data, observations etc.) You will have much more freedom to decide which sections of the dissertation should be combined, and whether new chapters or sections should be added.

Here is an overview of a common structure for an extended literature review:

Introduction

• Provide background information and context to set the ‘backdrop’ for your project.
• Explain the value and relevance of your research in this context. Outline what do you hope to contribute with your dissertation.
• Clarify a specific area of focus.
• Introduce your research aims (or problem) and objectives.

Literature review

You will need to write a short, overview literature review to introduce the main theories, concepts and key research areas that you will explore in your dissertation. This set of texts – which may be theoretical, research-based, practice-based or policies – form your theoretical framework. In other words, by bringing these texts together in the literature review, you are creating a lens that you can then apply to more focused examples or scenarios in your discussion chapters.

Methodology

As you will not be collecting primary data, your methodology will be quite different from a typical dissertation. You will need to set out the process and procedure you used to find and narrow down your literature. This is also known as a search strategy.

Including your search strategy

A search strategy explains how you have narrowed down your literature to identify key studies and areas of focus. This often takes the form of a search strategy table, included as an appendix at the end of the dissertation. If included, this section takes the place of the traditional 'methodology' section.

If you choose to include a search strategy table, you should also give an overview of your reading process in the main body of the dissertation.  Think of this as a chronology of the practical steps you took and your justification for doing so at each stage, such as:

• Your key terms, alternatives and synonyms, and any terms that you chose to exclude.
• Your choice and combination of databases;
• Your inclusion/exclusion criteria, when they were applied and why. This includes filters such as language of publication, date, and country of origin;
• You should also explain which terms you combined to form search phrases and your use of Boolean searching (AND, OR, NOT);
• Your use of citation searching (selecting articles from the bibliography of a chosen journal article to further your search).
• Your use of any search models, such as PICO and SPIDER to help shape your approach.
• Search strategy template A simple template for recording your literature searching. This can be included as an appendix to show your search strategy.

The discussion section of an extended literature review is the most flexible in terms of structure. Think of this section as a series of short case studies or ‘windows’ on your research. In this section you will apply the theoretical framework you formed in the literature review – a combination of theories, models and ideas that explain your approach to the topic – to a series of different examples and scenarios. These are usually presented as separate discussion ‘chapters’ in the dissertation, in an order that you feel best fits your argument.

Think about an order for these discussion sections or chapters that helps to tell the story of your research. One common approach is to structure these sections by common themes or concepts that help to draw your sources together. You might also opt for a chronological structure if your dissertation aims to show change or development over time. Another option is to deliberately show where there is a lack of chronology or narrative across your case studies, by ordering them in a fragmentary order! You will be able to reflect upon the structure of these chapters elsewhere in the dissertation, explaining and defending your decision in the methodology and conclusion.

A summary of your key findings – what you have concluded from your research, and how far you have been able to successfully answer your research questions.

• Recommendations – for improvements to your own study, for future research in the area, and for your field more widely.
• Emphasise your contributions to knowledge and what you have achieved.

Alternative structure

Depending on your research aims, and whether you are working with a case-study type approach (where each section of the dissertation considers a different example or concept through the lens established in your literature review), you might opt for one of the following structures:

Splitting the literature review across different chapters:

This structure allows you to pull apart the traditional literature review, introducing it little by little with each of your themed chapters. This approach works well for dissertations that attempt to show change or difference over time, as the relevant literature for that section or period can be introduced gradually to the reader.

Whichever structure you opt for, remember to explain and justify your approach. A marker will be interested in why you decided on your chosen structure, what it allows you to achieve/brings to the project and what alternatives you considered and rejected in the planning process. Here are some example sentence starters:

In qualitative studies, your results are often presented alongside the discussion, as it is difficult to include this data in a meaningful way without explanation and interpretation. In the dsicussion section, aim to structure your work thematically, moving through the key concepts or ideas that have emerged from your qualitative data. Use extracts from your data collection - interviews, focus groups, observations - to illustrate where these themes are most prominent, and refer back to the sources from your literature review to help draw conclusions. 

Here's an example of how your data could be presented in paragraph format in this section:

Example from  'Reporting and discussing your findings ', Monash University .

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Home   >>   Blog   >>   Tips on writing a qualitative dissertation or thesis, from Braun & Clarke – Part 1

Tips on writing a qualitative dissertation or thesis, from Braun & Clarke – Part 1

Our advice here relates to many forms of qualitative research, and particularly to research involving the use of thematic analysis (TA). 

Based on our experience of supervising students over two decades, as well as our writing on qualitative methodologies, we discuss what we think constitutes good practice – and note some common problems to avoid. 

Our first tip is  always to check local requirements ! Check what is required in your university context with regard to the format and presentation of your dissertation/thesis; if our advice clashes with this, discuss it with your supervisor. Sometimes requirements are “rules”, and sometimes they’re more norms and conventions, and there’s room to do things differently.

Qualitative centric research writing

Why might our advice here clash with what your local context expects or requires? The simple answer is that there isn’t a widely agreed on  single  standard for reporting qualitative research. Broadly speaking, there are two styles of qualitative research reporting – let’s call these “add qualitative research and stir” and “qualitative centric”. The “add qualitative and stir” style reflects the default conventions for reporting  quantitative  research slightly tweaked for qualitative research. Some characteristics of this style of reporting include: 

• third-person/passive voice
• searching out and identifying a “gap” in the literature in the introduction
• methodological critique of existing research; 
• and, when it comes to reporting the analysis, separate “results” and “discussion” sections. 

This style of reporting is far more widely understood and accepted than the other. 

What we advocate for is a “qualitative centric” style of reporting – one that is more in line with the ethos and values of qualitative research. This style departs from quantitative norms of empirical research reporting, and is consequently less widely recognised and understood. 

This is why you might experience a clash between what we recommend as good practice and what is required in your local context. We experience this clash of reporting values all the time – we have been required by reviewers and editors on numerous occasions to turn our qualitative centric research papers into something more conventional, and our students have sometimes been required by examiners to turn their qualitative centric theses into something more conventional (e.g., by separating out an integrated “results and discussion” and including methodological critique in the introduction). 

We want to be open about the fact that there  can be  risks in a qualitative centric style of reporting! One of the aims of this blog post, and the  Twitter thread  on which it is based, is to increase understanding of qualitative centric reporting styles so that fewer qualitative researchers are required to rework their research report into something less reflective of the ethos of qualitative research. 

So, what are some of the features of a qualitative centric reporting style? Let’s work through a report section by section.

Introduction

Think of the opening section of your report not as a literature  review  but as an  introduction  – the introduction is highly likely to include discussion of relevant literature, but the goal of the introduction is not to review the literature and find a “gap”. Instead, your goal in this section is to provide a context and rationale for your research.

If you do discuss bodies of literature, try to avoid summarising study after study after study… instead overview and synthesise a body of literature (What questions have been asked? What, if any, assumptions have been made? What are some of the common themes across the literature?). Have the confidence to tell the reader something about the state of the literature from your perspective.

Theoretical consistency in your introduction 

If you embrace fully the ethos and values of qualitative research, you don’t just understand qualitative research as providing you with tools and techniques to generate and analyse data; you’re unlikely to be a committed positivist or (simple/pure) realist. So if you’re not a positivist or realist when conducting and reporting  your  own research, how should you handle reporting research in your introduction that  is  positivist/realist? We think it’s important to be theoretically consistent across  your  report! 

That means not being a positivist/realist in your introduction when discussing quantitative research, then shifting to being something else when reporting your research. It means you need to think carefully about how you present and frame the findings of quantitative research. As an example, don’t present results from other projects as statements of fact (e.g. by stating “gay men are more likely than straight men to experience poor body image”), but rather as what other research has reported e.g. by saying “several quantitative studies suggest that gay men are more likely than straight men to experience poor body image”. It’s a subtle but important difference. It shows the reader that you understand your theoretical approach, and that it doesn’t (necessarily) align with the philosophical assumptions underpinning the quantitative research. 

We would also advise against engaging in methodological critique based on the values and assumptions of quantitative research in an introduction (methodological critique consistent with the philosophical assumptions of your research may be appropriate).

Framing your research: inverted triangles or stacked boxes?

Ideally, your introduction will make an  argument for your research  and  frame it within relevant wider contexts . It will flow beautifully – the reader will always know why they are being told something and where they are being taken next. There will be no jumping around from one to another seemingly unrelated topic. 

To help with flow and structure, work out if your introduction is the classic “inverted triangle” (starts broad and gets increasingly more specific) or what we call the “stacking boxes” structure. With the latter, you have several different topics to discuss but they aren’t easily classifiable as broader or more specific, they are all roughly at the same level. Your task is to decide how to order or stack the boxes! This is a judgement call and you will often need to figure out what works best  as you write . We regularly advise our students to reorder their stack of boxes; we do the same with our own work. You can’t always know ahead of writing how things will flow. 

With a “stacking boxes” introduction, we strongly recommend having some signposting or an overview at the start of the introduction to help the reader understand what you will cover and where things are going. Try to have linking sentences between different topics or sections to signal transitions to the reader (we’ve been here, now we are going there…). 

Research questions/aims

Typically, we’d advise you to end the introduction with your research questions/aims*. Any question (or questions) and aims should make sense to the reader – they definitely should not come as a surprise! – in light of the context you have presented. You want the reader to almost expect and anticipate your research question; you want your research question to  make sense . 

*Though, in some instances, this  might  work best at the start, ahead of your box stack! In such cases, you should come back to it at the end or before the start of the methodology. This works within a qualitative-centric introduction because you are not building towards a great “reveal” of the “gap” you have identified. 

Make sure you formulate your research question in a way that is consistent with the ethos and values of qualitative research. Don’t frame your research question(s) as hypotheses or, indeed, discuss what you expect to find. A common error is to formulate a research question in terms of the impact or effect of X on Y – which is essentially a poorly-disguised quantitative hypothesis! Our book  Successful Qualitative Research  provides a detailed discussion of formulating research questions for qualitative research. If you’re using TA, we have recently published a paper  Conceptual and Design Thinking for Thematic Analysis  t hat includes guidance on appropriate research questions for reflective TA – the approach to TA that we developed and first wrote about in  2006 .

Circling back to the title 

Let us circle around to thesis/dissertation  titles  here too – qualitative research is nothing if not recursive! Double check your title to make sure it isn’t implicitly quantitatively framed either. You really don’t want the reader to read your title and the introduction and be expecting a quantitative study when they get to your research questions! Ideally a good title tells the reader something about the topic, the methodological approach and perhaps also a key message from the analysis. Short, evocative quotations from participants can make great titles. Here’s an example from a project on  gay fathers .

Read Part 2 of this blog.

Victoria Clarke and Virginia Braun’s forthcoming book is  Thematic Analysis: A Practical Guide . They have websites on  thematic analysis  and the  story completion method . You can find them both on  Twitter  –  @drvicclarke  and  @ginnybraun  – where they tweet regularly about qualitative research.

More from edpsy:

Job: Educational Psychologist x 2 posts - Derby

About Victoria Clarke

Victoria is an Associate Professor in Qualitative and Critical Psychology at the University of the West of England, Bristol, UK. You can find her on Twitter - @drvicclarke - regularly tweeting about qualitative research.

View all posts by Victoria Clarke

About Virginia Braun

Virginia is a Professor in Psychology at The University of Auckland, Aotearoa New Zealand. You can find her on Twitter - @ginnybraun – (re)tweeting about qualitative research and other issues.

View all posts by Virginia Braun

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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.

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Qualitative research methods.

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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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Top 4 Steps of Qualitative Data Analysis for Dissertation

Welcome to our blog on qualitative data analysis for dissertation. We’re here to guide you through the essential steps, demystifying the methods of qualitative data analysis in dissertation. In simple terms, we’ll break down the importance of qualitative data analysis in a dissertation. Think of it as a roadmap to help you navigate and understand each step easily. 

Qualitative data analysis is the process of examining non-numerical information, such as text, images, or audio, to uncover patterns, themes, and insights. In the world of dissertation research, qualitative analysis plays a crucial role in exploring the depth and nuances of human experiences, opinions, and behaviors. 

Unlike quantitative methods that deal with measurable data, qualitative analysis offers a rich and contextual understanding, making it particularly valuable in social sciences, humanities, and other fields where the focus is on the quality rather than quantity of information. It allows researchers to delve into the intricacies of their subjects, providing a holistic view that goes beyond statistical figures. 

We’ll also provide an example of qualitative data analysis to make things clearer. By the end, you’ll see how these steps are like puzzle pieces that come together to tell the story of your dissertation. Let’s dive in and make qualitative data analysis less daunting and more understandable for your academic journey.

Methods of Qualitative Data Analysis in Dissertation

1. thematic analysis:.

– Identify and analyze recurring themes or patterns within the data.

– Organize these themes to capture the essence of your findings.

2. Content Analysis:

– Examine the content of your data for specific words, phrases, or themes.

– Categorize and quantify these elements to draw meaningful insights.

3. Grounded Theory:

– Develop theories from the data rather than applying pre-existing ones.

– Constantly compare data, allowing emerging theories to guide the analysis.

4. Narrative Analysis:

– Focus on the stories within the data.

– Explore the structure and content of these narratives to extract meaningful information.

5. Case Study Analysis:

– In-depth examination of a specific case or cases.

– Explore the details and context to understand the broader implications.

Step 1: Pre-Analysis Meditation

Importance of this step: .

Understanding the Significance: Pre-analysis meditation serves as a mental reset, helping researchers clear preconceived notions and biases. By fostering a reflective mindset, researchers approach the data with openness, encouraging unbiased exploration.

How PhD Researchers Can Implement Pre-Analysis Meditation:

Schedule Mindful Moments: Dedicate a few minutes before each analysis session for mindfulness. Incorporate deep-breathing exercises to ease into a focused state.

Step 2: Metaphorical Mapping

Unlocking creative insights:.

– Visual Representation: Metaphorical mapping allows for a visual interpretation of complex data, aiding in comprehension.

– Stimulates Creativity: Translating findings into metaphors encourages creative thinking, unveiling nuanced insights not immediately apparent in the raw data.

Enhancing Communication:

– Facilitates Explanation: Metaphors serve as powerful tools for conveying complex ideas, making it easier to communicate findings to a broader audience.

– Captures Essence: Mapping metaphors captures the essence of data, providing a holistic perspective that goes beyond literal interpretation.

How PhD Researchers Can Implement Metaphorical Mapping:

– Pinpoint central themes or concepts within the data.

– Select metaphors that resonate with the essence of these concepts.

– Create a visual map connecting metaphors to corresponding data points.

– Explore the relationships and interplay between different metaphors.

– Refine metaphors iteratively as analysis progresses.

– Allow the metaphorical map to evolve, reflecting deeper insights gained during analysis.

Step 3: Parallel Universe Probing

Importance of this step:, encouraging diverse perspectives:.

Promotes Critical Thinking: Parallel universe probing encourages researchers to explore diverse analytical angles, fostering critical thinking.

Challenges Assumptions: By envisioning alternative interpretations, researchers challenge preconceived notions, ensuring a more robust analysis.

Enhancing Analytical Rigor:

Strengthens Validity: Considering multiple perspectives strengthens the validity of findings, ensuring a comprehensive and well-rounded analysis.

Minimizes Bias: Actively engaging in parallel universe probing minimizes confirmation bias, promoting a more objective evaluation of the data.

How PhD Researchers Can Implement Parallel Universe Probing:

1. imagine alternative scenarios:.

Envision different ways the data could be interpreted.

Challenge assumptions by exploring contrasting analytical pathways.

2. Seek Diverse Opinions:

Collaborate with peers or mentors to gain diverse perspectives.

Discuss alternative interpretations to broaden the analytical scope.

3. Document Comparative Analysis:

Record and compare the outcomes of parallel universe probing.

Consider the advantages and disadvantages of every viewpoint.

Step 4: Multisensory Synthesis

– Expands Interpretation Horizons: Multisensory synthesis encourages researchers to go beyond reading, engaging various senses for a more holistic understanding of the data.

– Taps into Intuition: Incorporating multiple senses, including visual, auditory, and tactile, taps into intuitive insights, enriching the analytical experience.

– Enhances Data Connection: Multisensory exploration strengthens the connection with data, allowing for a more immersive and empathetic analysis.

– Facilitates Creative Expression: Engaging different senses facilitates creative expression, providing alternative avenues for expressing complex findings.

How PhD Researchers Can Implement Multisensory Synthesis:

Explore visual representations, auditory descriptions, or tactile expressions of data. Experiment with alternative formats to capture the essence of the findings. Discuss multisensory interpretations with peers or mentors. Gain insights from diverse perspectives on how different senses can contribute to a richer analysis. Recognize individual sensory strengths and preferences. Tailor the multisensory approach to align with personal modes of perception.

Final Thoughts

In summing up our journey through the top 4 steps of analyzing qualitative data for dissertations, we’ve explored important methods of qualitative data analysis in dissertation. Qualitative data analysis for dissertations, done through steps like thematic analysis and grounded theory, is like crafting a narrative that adds depth to the data. It’s not just about going through the motions; it’s about revealing valuable insights. 

Understanding the importance of qualitative data analysis in a dissertation is like realizing how these steps build the strong foundation of your research. They act like a guide, ensuring your dissertation not only makes sense but also captures the essence of what you’ve studied. To put it simply, these example of qualitative data analysis empower researchers, showing them how to unravel the complexities and tell a compelling academic story in their dissertations.

Dissertationcanada.com is a Canadian-based company that provides comprehensive dissertation assistance to PhD and Master’s students. They offer a range of services, including writing, editing, statistics, peer review, and formatting for research work. The company has a team of 7 writers, 12 editors, and 3 statisticians who are based in Canada. They provide custom PhD and Master’s dissertation assistance in Canada for conducting research and writing qualitative data analysis for dissertation. Doctorate applicants receive consultations with writing, editing, and research design as well as statistical support. 

The company doesn’t merely advise but gets involved in your dissertation through collaborative pedagogy of their support service. They offer services such as dissertation editing, data analysis, methodology, literature review, and concept paper assistance. Their comprehensive package for dissertation help is value for money. They have in-depth knowledge and provide 24X7 services.  

FAQ Questions

1. what are the three important steps in qualitative data analysis.

Data coding, theme identification, and constant comparison.

2. What is the aim of qualitative research?

To investigate and comprehend underlying viewpoints, experiences, and meanings.

3. What is the main advantage of using Qualitative data analysis in a dissertation?

Provides in-depth insights and context, enriching the research narrative.

4. How do you ensure credibility in qualitative research?

Through methods like member checking, peer debriefing, and triangulation.

How To Write The Discussion Chapter

A Simple Explainer With Examples + Free Template

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

If you’re reading this, chances are you’ve reached the discussion chapter of your thesis or dissertation and are looking for a bit of guidance. Well, you’ve come to the right place ! In this post, we’ll unpack and demystify the typical discussion chapter in straightforward, easy to understand language, with loads of examples .

Overview: The Discussion Chapter

• What  the discussion chapter is
• What to include in your discussion
• How to write up your discussion
• A few tips and tricks to help you along the way
• Free discussion template

What (exactly) is the discussion chapter?

The discussion chapter is where you interpret and explain your results within your thesis or dissertation. This contrasts with the results chapter, where you merely present and describe the analysis findings (whether qualitative or quantitative ). In the discussion chapter, you elaborate on and evaluate your research findings, and discuss the significance and implications of your results.

In this chapter, you’ll situate your research findings in terms of your research questions or hypotheses and tie them back to previous studies and literature (which you would have covered in your literature review chapter). You’ll also have a look at how relevant and/or significant your findings are to your field of research, and you’ll argue for the conclusions that you draw from your analysis. Simply put, the discussion chapter is there for you to interact with and explain your research findings in a thorough and coherent manner.

What should I include in the discussion chapter?

First things first: in some studies, the results and discussion chapter are combined into one chapter .  This depends on the type of study you conducted (i.e., the nature of the study and methodology adopted), as well as the standards set by the university.  So, check in with your university regarding their norms and expectations before getting started. In this post, we’ll treat the two chapters as separate, as this is most common.

Basically, your discussion chapter should analyse , explore the meaning and identify the importance of the data you presented in your results chapter. In the discussion chapter, you’ll give your results some form of meaning by evaluating and interpreting them. This will help answer your research questions, achieve your research aims and support your overall conclusion (s). Therefore, you discussion chapter should focus on findings that are directly connected to your research aims and questions. Don’t waste precious time and word count on findings that are not central to the purpose of your research project.

As this chapter is a reflection of your results chapter, it’s vital that you don’t report any new findings . In other words, you can’t present claims here if you didn’t present the relevant data in the results chapter first.  So, make sure that for every discussion point you raise in this chapter, you’ve covered the respective data analysis in the results chapter. If you haven’t, you’ll need to go back and adjust your results chapter accordingly.

If you’re struggling to get started, try writing down a bullet point list everything you found in your results chapter. From this, you can make a list of everything you need to cover in your discussion chapter. Also, make sure you revisit your research questions or hypotheses and incorporate the relevant discussion to address these.  This will also help you to see how you can structure your chapter logically.

Need a helping hand?

How to write the discussion chapter

Now that you’ve got a clear idea of what the discussion chapter is and what it needs to include, let’s look at how you can go about structuring this critically important chapter. Broadly speaking, there are six core components that need to be included, and these can be treated as steps in the chapter writing process.

Step 1: Restate your research problem and research questions

The first step in writing up your discussion chapter is to remind your reader of your research problem , as well as your research aim(s) and research questions . If you have hypotheses, you can also briefly mention these. This “reminder” is very important because, after reading dozens of pages, the reader may have forgotten the original point of your research or been swayed in another direction. It’s also likely that some readers skip straight to your discussion chapter from the introduction chapter , so make sure that your research aims and research questions are clear.

Step 2: Summarise your key findings

Next, you’ll want to summarise your key findings from your results chapter. This may look different for qualitative and quantitative research , where qualitative research may report on themes and relationships, whereas quantitative research may touch on correlations and causal relationships. Regardless of the methodology, in this section you need to highlight the overall key findings in relation to your research questions.

Typically, this section only requires one or two paragraphs , depending on how many research questions you have. Aim to be concise here, as you will unpack these findings in more detail later in the chapter. For now, a few lines that directly address your research questions are all that you need.

Some examples of the kind of language you’d use here include:

• The data suggest that…
• The data support/oppose the theory that…
• The analysis identifies…

These are purely examples. What you present here will be completely dependent on your original research questions, so make sure that you are led by them .

Step 3: Interpret your results

Once you’ve restated your research problem and research question(s) and briefly presented your key findings, you can unpack your findings by interpreting your results. Remember: only include what you reported in your results section – don’t introduce new information.

From a structural perspective, it can be a wise approach to follow a similar structure in this chapter as you did in your results chapter. This would help improve readability and make it easier for your reader to follow your arguments. For example, if you structured you results discussion by qualitative themes, it may make sense to do the same here.

Alternatively, you may structure this chapter by research questions, or based on an overarching theoretical framework that your study revolved around. Every study is different, so you’ll need to assess what structure works best for you.

When interpreting your results, you’ll want to assess how your findings compare to those of the existing research (from your literature review chapter). Even if your findings contrast with the existing research, you need to include these in your discussion. In fact, those contrasts are often the most interesting findings . In this case, you’d want to think about why you didn’t find what you were expecting in your data and what the significance of this contrast is.

Here are a few questions to help guide your discussion:

• How do your results relate with those of previous studies ?
• If you get results that differ from those of previous studies, why may this be the case?
• What do your results contribute to your field of research?
• What other explanations could there be for your findings?

When interpreting your findings, be careful not to draw conclusions that aren’t substantiated . Every claim you make needs to be backed up with evidence or findings from the data (and that data needs to be presented in the previous chapter – results). This can look different for different studies; qualitative data may require quotes as evidence, whereas quantitative data would use statistical methods and tests. Whatever the case, every claim you make needs to be strongly backed up.

Step 4: Acknowledge the limitations of your study

The fourth step in writing up your discussion chapter is to acknowledge the limitations of the study. These limitations can cover any part of your study , from the scope or theoretical basis to the analysis method(s) or sample. For example, you may find that you collected data from a very small sample with unique characteristics, which would mean that you are unable to generalise your results to the broader population.

For some students, discussing the limitations of their work can feel a little bit self-defeating . This is a misconception, as a core indicator of high-quality research is its ability to accurately identify its weaknesses. In other words, accurately stating the limitations of your work is a strength, not a weakness . All that said, be careful not to undermine your own research. Tell the reader what limitations exist and what improvements could be made, but also remind them of the value of your study despite its limitations.

Step 5: Make recommendations for implementation and future research

Now that you’ve unpacked your findings and acknowledge the limitations thereof, the next thing you’ll need to do is reflect on your study in terms of two factors:

• The practical application of your findings
• Suggestions for future research

The first thing to discuss is how your findings can be used in the real world – in other words, what contribution can they make to the field or industry? Where are these contributions applicable, how and why? For example, if your research is on communication in health settings, in what ways can your findings be applied to the context of a hospital or medical clinic? Make sure that you spell this out for your reader in practical terms, but also be realistic and make sure that any applications are feasible.

The next discussion point is the opportunity for future research . In other words, how can other studies build on what you’ve found and also improve the findings by overcoming some of the limitations in your study (which you discussed a little earlier). In doing this, you’ll want to investigate whether your results fit in with findings of previous research, and if not, why this may be the case. For example, are there any factors that you didn’t consider in your study? What future research can be done to remedy this? When you write up your suggestions, make sure that you don’t just say that more research is needed on the topic, also comment on how the research can build on your study.

Step 6: Provide a concluding summary

Finally, you’ve reached your final stretch. In this section, you’ll want to provide a brief recap of the key findings – in other words, the findings that directly address your research questions . Basically, your conclusion should tell the reader what your study has found, and what they need to take away from reading your report.

When writing up your concluding summary, bear in mind that some readers may skip straight to this section from the beginning of the chapter.  So, make sure that this section flows well from and has a strong connection to the opening section of the chapter.

Tips and tricks for an A-grade discussion chapter

Now that you know what the discussion chapter is , what to include and exclude , and how to structure it , here are some tips and suggestions to help you craft a quality discussion chapter.

• When you write up your discussion chapter, make sure that you keep it consistent with your introduction chapter , as some readers will skip from the introduction chapter directly to the discussion chapter. Your discussion should use the same tense as your introduction, and it should also make use of the same key terms.
• Don’t make assumptions about your readers. As a writer, you have hands-on experience with the data and so it can be easy to present it in an over-simplified manner. Make sure that you spell out your findings and interpretations for the intelligent layman.
• Have a look at other theses and dissertations from your institution, especially the discussion sections. This will help you to understand the standards and conventions of your university, and you’ll also get a good idea of how others have structured their discussion chapters. You can also check out our chapter template .
• Avoid using absolute terms such as “These results prove that…”, rather make use of terms such as “suggest” or “indicate”, where you could say, “These results suggest that…” or “These results indicate…”. It is highly unlikely that a dissertation or thesis will scientifically prove something (due to a variety of resource constraints), so be humble in your language.
• Use well-structured and consistently formatted headings to ensure that your reader can easily navigate between sections, and so that your chapter flows logically and coherently.

If you have any questions or thoughts regarding this post, feel free to leave a comment below. Also, if you’re looking for one-on-one help with your discussion chapter (or thesis in general), consider booking a free consultation with one of our highly experienced Grad Coaches to discuss how we can help you.

Psst... there’s more!

This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...

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36 Comments

Thank you this is helpful!

This is very helpful to me… Thanks a lot for sharing this with us 😊

This has been very helpful indeed. Thank you.

This is actually really helpful, I just stumbled upon it. Very happy that I found it, thank you.

Me too! I was kinda lost on how to approach my discussion chapter. How helpful! Thanks a lot!

This is really good and explicit. Thanks

Thank you, this blog has been such a help.

Thank you. This is very helpful.

Dear sir/madame

Thanks a lot for this helpful blog. Really, it supported me in writing my discussion chapter while I was totally unaware about its structure and method of writing.

With regards

Syed Firoz Ahmad PhD, Research Scholar

I agree so much. This blog was god sent. It assisted me so much while I was totally clueless about the context and the know-how. Now I am fully aware of what I am to do and how I am to do it.

Thanks! This is helpful!

thanks alot for this informative website

Dear Sir/Madam,

Truly, your article was much benefited when i structured my discussion chapter.

Thank you very much!!!

This is helpful for me in writing my research discussion component. I have to copy this text on Microsoft word cause of my weakness that I cannot be able to read the text on screen a long time. So many thanks for this articles.

This was helpful

Thanks Jenna, well explained.

Thank you! This is super helpful.

Thanks very much. I have appreciated the six steps on writing the Discussion chapter which are (i) Restating the research problem and questions (ii) Summarising the key findings (iii) Interpreting the results linked to relating to previous results in positive and negative ways; explaining whay different or same and contribution to field of research and expalnation of findings (iv) Acknowledgeing limitations (v) Recommendations for implementation and future resaerch and finally (vi) Providing a conscluding summary

My two questions are: 1. On step 1 and 2 can it be the overall or you restate and sumamrise on each findings based on the reaerch question? 2. On 4 and 5 do you do the acknowlledgement , recommendations on each research finding or overall. This is not clear from your expalanattion.

Please respond.

This post is very useful. I’m wondering whether practical implications must be introduced in the Discussion section or in the Conclusion section?

Sigh, I never knew a 20 min video could have literally save my life like this. I found this at the right time!!!! Everything I need to know in one video thanks a mil ! OMGG and that 6 step!!!!!! was the cherry on top the cake!!!!!!!!!

Thanks alot.., I have gained much

This piece is very helpful on how to go about my discussion section. I can always recommend GradCoach research guides for colleagues.

Many thanks for this resource. It has been very helpful to me. I was finding it hard to even write the first sentence. Much appreciated.

Thanks so much. Very helpful to know what is included in the discussion section

this was a very helpful and useful information

This is very helpful. Very very helpful. Thanks for sharing this online!

it is very helpfull article, and i will recommend it to my fellow students. Thank you.

Superlative! More grease to your elbows.

Powerful, thank you for sharing.

Wow! Just wow! God bless the day I stumbled upon you guys’ YouTube videos! It’s been truly life changing and anxiety about my report that is due in less than a month has subsided significantly!

Simplified explanation. Well done.

The presentation is enlightening. Thank you very much.

Thanks for the support and guidance

This has been a great help to me and thank you do much

I second that “it is highly unlikely that a dissertation or thesis will scientifically prove something”; although, could you enlighten us on that comment and elaborate more please?

Sure, no problem.

Scientific proof is generally considered a very strong assertion that something is definitively and universally true. In most scientific disciplines, especially within the realms of natural and social sciences, absolute proof is very rare. Instead, researchers aim to provide evidence that supports or rejects hypotheses. This evidence increases or decreases the likelihood that a particular theory is correct, but it rarely proves something in the absolute sense.

Dissertations and theses, as substantial as they are, typically focus on exploring a specific question or problem within a larger field of study. They contribute to a broader conversation and body of knowledge. The aim is often to provide detailed insight, extend understanding, and suggest directions for further research rather than to offer definitive proof. These academic works are part of a cumulative process of knowledge building where each piece of research connects with others to gradually enhance our understanding of complex phenomena.

Furthermore, the rigorous nature of scientific inquiry involves continuous testing, validation, and potential refutation of ideas. What might be considered a “proof” at one point can later be challenged by new evidence or alternative interpretations. Therefore, the language of “proof” is cautiously used in academic circles to maintain scientific integrity and humility.

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Convergence and Scaling Analysis of Large-Eddy Simulations of a Pool Fire

Grid convergence and scaling analyses have not been done rigorously for practical large-eddy simulations (LES). The challenge arises from the fact that there are two grid-related length scales: grid size and LES filter width. It causes the numerical and model errors in LES to be inherently coupled, making the convergence of either error difficult to analyze. This study works to overcome the challenge by developing scaling laws that can be used to guide the convergence analysis of errors in LES. Three different convergence cases are considered, and their respective scaling laws are developed by varying the ratio between grid size and filter width. A pool fire is adopted as a test case for the convergence analysis of LES. Qualitative and quantitative assessments of the LES results are made first to ensure reliable numerical solutions. In the subsequent scaling analysis, it is found that the results are consistent with their respective scaling laws. The results provide strong support to the developed scaling laws. The work is significant as it proposes a rigorous way to guide convergence analysis of LES errors. In a world where LES already has a wide range of applicability and is still becoming more prominent, it is imperative to have a thorough understanding of how it works including its convergence and scaling laws with respect to the change of grid size and filter width.

Degree Type

• Master of Science
• Aeronautics and Astronautics

Campus location

• West Lafayette

Advisor/Supervisor/Committee Chair

Additional committee member 2, additional committee member 3, usage metrics.

• Computational methods in fluid flow, heat and mass transfer (incl. computational fluid dynamics)
• Turbulent flows