Dissertations 4: methodology: methods.
- Introduction & Philosophy
Primary & Secondary Sources, Primary & Secondary Data
When describing your research methods, you can start by stating what kind of secondary and, if applicable, primary sources you used in your research. Explain why you chose such sources, how well they served your research, and identify possible issues encountered using these sources.
There is some confusion on the use of the terms primary and secondary sources, and primary and secondary data. The confusion is also due to disciplinary differences (Lombard 2010). Whilst you are advised to consult the research methods literature in your field, we can generalise as follows:
Secondary sources normally include the literature (books and articles) with the experts' findings, analysis and discussions on a certain topic (Cottrell, 2014, p123). Secondary sources often interpret primary sources.
Primary sources are "first-hand" information such as raw data, statistics, interviews, surveys, law statutes and law cases. Even literary texts, pictures and films can be primary sources if they are the object of research (rather than, for example, documentaries reporting on something else, in which case they would be secondary sources). The distinction between primary and secondary sources sometimes lies on the use you make of them (Cottrell, 2014, p123).
Primary data are data (primary sources) you directly obtained through your empirical work (Saunders, Lewis and Thornhill 2015, p316).
Secondary data are data (primary sources) that were originally collected by someone else (Saunders, Lewis and Thornhill 2015, p316).
Comparison between primary and secondary data
Virtually all research will use secondary sources, at least as background information.
Often, especially at the postgraduate level, it will also use primary sources - secondary and/or primary data. The engagement with primary sources is generally appreciated, as less reliant on others' interpretations, and closer to 'facts'.
The use of primary data, as opposed to secondary data, demonstrates the researcher's effort to do empirical work and find evidence to answer her specific research question and fulfill her specific research objectives. Thus, primary data contribute to the originality of the research.
Ultimately, you should state in this section of the methodology:
What sources and data you are using and why (how are they going to help you answer the research question and/or test the hypothesis.
If using primary data, why you employed certain strategies to collect them.
What the advantages and disadvantages of your strategies to collect the data (also refer to the research in you field and research methods literature).
Quantitative, Qualitative & Mixed Methods
The methodology chapter should reference your use of quantitative research, qualitative research and/or mixed methods. The following is a description of each along with their advantages and disadvantages.
Quantitative research uses numerical data (quantities) deriving, for example, from experiments, closed questions in surveys, questionnaires, structured interviews or published data sets (Cottrell, 2014, p93). It normally processes and analyses this data using quantitative analysis techniques like tables, graphs and statistics to explore, present and examine relationships and trends within the data (Saunders, Lewis and Thornhill, 2015, p496).
Qualitative research is generally undertaken to study human behaviour and psyche. It uses methods like in-depth case studies, open-ended survey questions, unstructured interviews, focus groups, or unstructured observations (Cottrell, 2014, p93). The nature of the data is subjective, and also the analysis of the researcher involves a degree of subjective interpretation. Subjectivity can be controlled for in the research design, or has to be acknowledged as a feature of the research. Subject-specific books on (qualitative) research methods offer guidance on such research designs.
Mixed-method approaches combine both qualitative and quantitative methods, and therefore combine the strengths of both types of research. Mixed methods have gained popularity in recent years.
When undertaking mixed-methods research you can collect the qualitative and quantitative data either concurrently or sequentially. If sequentially, you can for example, start with a few semi-structured interviews, providing qualitative insights, and then design a questionnaire to obtain quantitative evidence that your qualitative findings can also apply to a wider population (Specht, 2019, p138).
Ultimately, your methodology chapter should state:
Whether you used quantitative research, qualitative research or mixed methods.
Why you chose such methods (and refer to research method sources).
Why you rejected other methods.
How well the method served your research.
The problems or limitations you encountered.
Doug Specht, Senior Lecturer at the Westminster School of Media and Communication, explains mixed methods research in the following video:
LinkedIn Learning Video on Academic Research Foundations: Quantitative
The video covers the characteristics of quantitative research, and explains how to approach different parts of the research process, such as creating a solid research question and developing a literature review. He goes over the elements of a study, explains how to collect and analyze data, and shows how to present your data in written and numeric form.
Link to quantitative research video
Some Types of Methods
There are several methods you can use to get primary data. To reiterate, the choice of the methods should depend on your research question/hypothesis.
Whatever methods you will use, you will need to consider:
why did you choose one technique over another? What were the advantages and disadvantages of the technique you chose?
what was the size of your sample? Who made up your sample? How did you select your sample population? Why did you choose that particular sampling strategy?)
ethical considerations (see also tab...)
procedure of the research (see box procedural method...).
Check Stella Cottrell's book Dissertations and Project Reports: A Step by Step Guide for some succinct yet comprehensive information on most methods (the following account draws mostly on her work). Check a research methods book in your discipline for more specific guidance.
Experiments are useful to investigate cause and effect, when the variables can be tightly controlled. They can test a theory or hypothesis in controlled conditions. Experiments do not prove or disprove an hypothesis, instead they support or not support an hypothesis. When using the empirical and inductive method it is not possible to achieve conclusive results. The results may only be valid until falsified by other experiments and observations.
For more information on Scientific Method, click here .
Observational methods are useful for in-depth analyses of behaviours in people, animals, organisations, events or phenomena. They can test a theory or products in real life or simulated settings. They generally a qualitative research method.
Questionnaires and surveys
Questionnaires and surveys are useful to gain opinions, attitudes, preferences, understandings on certain matters. They can provide quantitative data that can be collated systematically; qualitative data, if they include opportunities for open-ended responses; or both qualitative and quantitative elements.
Interviews are useful to gain rich, qualitative information about individuals' experiences, attitudes or perspectives. With interviews you can follow up immediately on responses for clarification or further details. There are three main types of interviews: structured (following a strict pattern of questions, which expect short answers), semi-structured (following a list of questions, with the opportunity to follow up the answers with improvised questions), and unstructured (following a short list of broad questions, where the respondent can lead more the conversation) (Specht, 2019, p142).
This short video on qualitative interviews discusses best practices and covers qualitative interview design, preparation and data collection methods.
In this case, a group of people (normally, 4-12) is gathered for an interview where the interviewer asks questions to such group of participants. Group interactions and discussions can be highly productive, but the researcher has to beware of the group effect, whereby certain participants and views dominate the interview (Saunders, Lewis and Thornhill 2015, p419). The researcher can try to minimise this by encouraging involvement of all participants and promoting a multiplicity of views.
This video focuses on strategies for conducting research using focus groups.
Check out the guidance on online focus groups by Aliaksandr Herasimenka, which is attached at the bottom of this text box.
Case studies are often a convenient way to narrow the focus of your research by studying how a theory or literature fares with regard to a specific person, group, organisation, event or other type of entity or phenomenon you identify. Case studies can be researched using other methods, including those described in this section. Case studies give in-depth insights on the particular reality that has been examined, but may not be representative of what happens in general, they may not be generalisable, and may not be relevant to other contexts. These limitations have to be acknowledged by the researcher.
Content analysis consists in the study of words or images within a text. In its broad definition, texts include books, articles, essays, historical documents, speeches, conversations, advertising, interviews, social media posts, films, theatre, paintings or other visuals. Content analysis can be quantitative (e.g. word frequency) or qualitative (e.g. analysing intention and implications of the communication). It can detect propaganda, identify intentions of writers, and can see differences in types of communication (Specht, 2019, p146). Check this page on collecting, cleaning and visualising Twitter data.
Extra links and resources:
A clear and comprehensive overview of research methods by Emerald Publishing. It includes: crowdsourcing as a research tool; mixed methods research; case study; discourse analysis; ground theory; repertory grid; ethnographic method and participant observation; interviews; focus group; action research; analysis of qualitative data; survey design; questionnaires; statistics; experiments; empirical research; literature review; secondary data and archival materials; data collection.
Doing your dissertation during the COVID-19 pandemic
Resources providing guidance on doing dissertation research during the pandemic: Online research methods; Secondary data sources; Webinars, conferences and podcasts;
- Virtual Focus Groups Guidance on managing virtual focus groups
5 Minute Methods Videos
The following are a series of useful videos that introduce research methods in five minutes. These resources have been produced by lecturers and students with the University of Westminster's School of Media and Communication.
Case Study Research
Quantitative Content Analysis
Qualitative Content Analysis
Social Media Research
Mixed Method Research
In this part, provide an accurate, detailed account of the methods and procedures that were used in the study or the experiment (if applicable!).
Include specifics about participants, sample, materials, design and methods.
If the research involves human subjects, then include a detailed description of who and how many participated along with how the participants were selected.
Describe all materials used for the study, including equipment, written materials and testing instruments.
Identify the study's design and any variables or controls employed.
Write out the steps in the order that they were completed.
Indicate what participants were asked to do, how measurements were taken and any calculations made to raw data collected.
Specify statistical techniques applied to the data to reach your conclusions.
Provide evidence that you incorporated rigor into your research. This is the quality of being thorough and accurate and considers the logic behind your research design.
Highlight any drawbacks that may have limited your ability to conduct your research thoroughly.
You have to provide details to allow others to replicate the experiment and/or verify the data, to test the validity of the research.
Cottrell, S. (2014). Dissertations and project reports: a step by step guide. Hampshire, England: Palgrave Macmillan.
Lombard, E. (2010). Primary and secondary sources. The Journal of Academic Librarianship , 36(3), 250-253
Saunders, M.N.K., Lewis, P. and Thornhill, A. (2015). Research Methods for Business Students. New York: Pearson Education.
Specht, D. (2019). The Media And Communications Study Skills Student Guide . London: University of Westminster Press.
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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.
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.
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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- How to Do Thematic Analysis | Step-by-Step Guide & Examples
How to Do Thematic Analysis | Step-by-Step Guide & Examples
Published on September 6, 2019 by Jack Caulfield . Revised on June 22, 2023.
Thematic analysis is a method of analyzing qualitative data . It is usually applied to a set of texts, such as an interview or transcripts . The researcher closely examines the data to identify common themes – topics, ideas and patterns of meaning that come up repeatedly.
There are various approaches to conducting thematic analysis, but the most common form follows a six-step process: familiarization, coding, generating themes, reviewing themes, defining and naming themes, and writing up. Following this process can also help you avoid confirmation bias when formulating your analysis.
This process was originally developed for psychology research by Virginia Braun and Victoria Clarke . However, thematic analysis is a flexible method that can be adapted to many different kinds of research.
Table of contents
When to use thematic analysis, different approaches to thematic analysis, step 1: familiarization, step 2: coding, step 3: generating themes, step 4: reviewing themes, step 5: defining and naming themes, step 6: writing up, other interesting articles.
Thematic analysis is a good approach to research where you’re trying to find out something about people’s views, opinions, knowledge, experiences or values from a set of qualitative data – for example, interview transcripts , social media profiles, or survey responses .
Some types of research questions you might use thematic analysis to answer:
- How do patients perceive doctors in a hospital setting?
- What are young women’s experiences on dating sites?
- What are non-experts’ ideas and opinions about climate change?
- How is gender constructed in high school history teaching?
To answer any of these questions, you would collect data from a group of relevant participants and then analyze it. Thematic analysis allows you a lot of flexibility in interpreting the data, and allows you to approach large data sets more easily by sorting them into broad themes.
However, it also involves the risk of missing nuances in the data. Thematic analysis is often quite subjective and relies on the researcher’s judgement, so you have to reflect carefully on your own choices and interpretations.
Pay close attention to the data to ensure that you’re not picking up on things that are not there – or obscuring things that are.
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Once you’ve decided to use thematic analysis, there are different approaches to consider.
There’s the distinction between inductive and deductive approaches:
- An inductive approach involves allowing the data to determine your themes.
- A deductive approach involves coming to the data with some preconceived themes you expect to find reflected there, based on theory or existing knowledge.
Ask yourself: Does my theoretical framework give me a strong idea of what kind of themes I expect to find in the data (deductive), or am I planning to develop my own framework based on what I find (inductive)?
There’s also the distinction between a semantic and a latent approach:
- A semantic approach involves analyzing the explicit content of the data.
- A latent approach involves reading into the subtext and assumptions underlying the data.
Ask yourself: Am I interested in people’s stated opinions (semantic) or in what their statements reveal about their assumptions and social context (latent)?
After you’ve decided thematic analysis is the right method for analyzing your data, and you’ve thought about the approach you’re going to take, you can follow the six steps developed by Braun and Clarke .
The first step is to get to know our data. It’s important to get a thorough overview of all the data we collected before we start analyzing individual items.
This might involve transcribing audio , reading through the text and taking initial notes, and generally looking through the data to get familiar with it.
Next up, we need to code the data. Coding means highlighting sections of our text – usually phrases or sentences – and coming up with shorthand labels or “codes” to describe their content.
Let’s take a short example text. Say we’re researching perceptions of climate change among conservative voters aged 50 and up, and we have collected data through a series of interviews. An extract from one interview looks like this:
In this extract, we’ve highlighted various phrases in different colors corresponding to different codes. Each code describes the idea or feeling expressed in that part of the text.
At this stage, we want to be thorough: we go through the transcript of every interview and highlight everything that jumps out as relevant or potentially interesting. As well as highlighting all the phrases and sentences that match these codes, we can keep adding new codes as we go through the text.
After we’ve been through the text, we collate together all the data into groups identified by code. These codes allow us to gain a a condensed overview of the main points and common meanings that recur throughout the data.
Next, we look over the codes we’ve created, identify patterns among them, and start coming up with themes.
Themes are generally broader than codes. Most of the time, you’ll combine several codes into a single theme. In our example, we might start combining codes into themes like this:
At this stage, we might decide that some of our codes are too vague or not relevant enough (for example, because they don’t appear very often in the data), so they can be discarded.
Other codes might become themes in their own right. In our example, we decided that the code “uncertainty” made sense as a theme, with some other codes incorporated into it.
Again, what we decide will vary according to what we’re trying to find out. We want to create potential themes that tell us something helpful about the data for our purposes.
Now we have to make sure that our themes are useful and accurate representations of the data. Here, we return to the data set and compare our themes against it. Are we missing anything? Are these themes really present in the data? What can we change to make our themes work better?
If we encounter problems with our themes, we might split them up, combine them, discard them or create new ones: whatever makes them more useful and accurate.
For example, we might decide upon looking through the data that “changing terminology” fits better under the “uncertainty” theme than under “distrust of experts,” since the data labelled with this code involves confusion, not necessarily distrust.
Now that you have a final list of themes, it’s time to name and define each of them.
Defining themes involves formulating exactly what we mean by each theme and figuring out how it helps us understand the data.
Naming themes involves coming up with a succinct and easily understandable name for each theme.
For example, we might look at “distrust of experts” and determine exactly who we mean by “experts” in this theme. We might decide that a better name for the theme is “distrust of authority” or “conspiracy thinking”.
Finally, we’ll write up our analysis of the data. Like all academic texts, writing up a thematic analysis requires an introduction to establish our research question, aims and approach.
We should also include a methodology section, describing how we collected the data (e.g. through semi-structured interviews or open-ended survey questions ) and explaining how we conducted the thematic analysis itself.
The results or findings section usually addresses each theme in turn. We describe how often the themes come up and what they mean, including examples from the data as evidence. Finally, our conclusion explains the main takeaways and shows how the analysis has answered our research question.
In our example, we might argue that conspiracy thinking about climate change is widespread among older conservative voters, point out the uncertainty with which many voters view the issue, and discuss the role of misinformation in respondents’ perceptions.
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.
- Normal distribution
- Measures of central tendency
- Chi square tests
- Confidence interval
- Quartiles & Quantiles
- Cluster sampling
- Stratified sampling
- Discourse analysis
- Cohort study
- Peer review
- Implicit bias
- Cognitive bias
- Conformity bias
- Hawthorne effect
- Availability heuristic
- Attrition bias
- Social desirability bias
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Dissertation Structure & Layout 101: How to structure your dissertation, thesis or research project.
By: Derek Jansen (MBA) Reviewed By: David Phair (PhD) | July 2019
So, you’ve got a decent understanding of what a dissertation is , you’ve chosen your topic and hopefully you’ve received approval for your research proposal . Awesome! Now its time to start the actual dissertation or thesis writing journey.
To craft a high-quality document, the very first thing you need to understand is dissertation structure . In this post, we’ll walk you through the generic dissertation structure and layout, step by step. We’ll start with the big picture, and then zoom into each chapter to briefly discuss the core contents. If you’re just starting out on your research journey, you should start with this post, which covers the big-picture process of how to write a dissertation or thesis .
*The Caveat *
In this post, we’ll be discussing a traditional dissertation/thesis structure and layout, which is generally used for social science research across universities, whether in the US, UK, Europe or Australia. However, some universities may have small variations on this structure (extra chapters, merged chapters, slightly different ordering, etc).
So, always check with your university if they have a prescribed structure or layout that they expect you to work with. If not, it’s safe to assume the structure we’ll discuss here is suitable. And even if they do have a prescribed structure, you’ll still get value from this post as we’ll explain the core contents of each section.
Overview: S tructuring a dissertation or thesis
- Acknowledgements page
- Abstract (or executive summary)
- Table of contents , list of figures and tables
- Chapter 1: Introduction
- Chapter 2: Literature review
- Chapter 3: Methodology
- Chapter 4: Results
- Chapter 5: Discussion
- Chapter 6: Conclusion
- Reference list
As I mentioned, some universities will have slight variations on this structure. For example, they want an additional “personal reflection chapter”, or they might prefer the results and discussion chapter to be merged into one. Regardless, the overarching flow will always be the same, as this flow reflects the research process , which we discussed here – i.e.:
- The introduction chapter presents the core research question and aims .
- The literature review chapter assesses what the current research says about this question.
- The methodology, results and discussion chapters go about undertaking new research about this question.
- The conclusion chapter (attempts to) answer the core research question .
In other words, the dissertation structure and layout reflect the research process of asking a well-defined question(s), investigating, and then answering the question – see below.
To restate that – the structure and layout of a dissertation reflect the flow of the overall research process . This is essential to understand, as each chapter will make a lot more sense if you “get” this concept. If you’re not familiar with the research process, read this post before going further.
Right. Now that we’ve covered the big picture, let’s dive a little deeper into the details of each section and chapter. Oh and by the way, you can also grab our free dissertation/thesis template here to help speed things up.
The title page of your dissertation is the very first impression the marker will get of your work, so it pays to invest some time thinking about your title. But what makes for a good title? A strong title needs to be 3 things:
- Succinct (not overly lengthy or verbose)
- Specific (not vague or ambiguous)
- Representative of the research you’re undertaking (clearly linked to your research questions)
Typically, a good title includes mention of the following:
- The broader area of the research (i.e. the overarching topic)
- The specific focus of your research (i.e. your specific context)
- Indication of research design (e.g. quantitative , qualitative , or mixed methods ).
A quantitative investigation [research design] into the antecedents of organisational trust [broader area] in the UK retail forex trading market [specific context/area of focus].
Again, some universities may have specific requirements regarding the format and structure of the title, so it’s worth double-checking expectations with your institution (if there’s no mention in the brief or study material).
This page provides you with an opportunity to say thank you to those who helped you along your research journey. Generally, it’s optional (and won’t count towards your marks), but it is academic best practice to include this.
So, who do you say thanks to? Well, there’s no prescribed requirements, but it’s common to mention the following people:
- Your dissertation supervisor or committee.
- Any professors, lecturers or academics that helped you understand the topic or methodologies.
- Any tutors, mentors or advisors.
- Your family and friends, especially spouse (for adult learners studying part-time).
There’s no need for lengthy rambling. Just state who you’re thankful to and for what (e.g. thank you to my supervisor, John Doe, for his endless patience and attentiveness) – be sincere. In terms of length, you should keep this to a page or less.
Abstract or executive summary
The dissertation abstract (or executive summary for some degrees) serves to provide the first-time reader (and marker or moderator) with a big-picture view of your research project. It should give them an understanding of the key insights and findings from the research, without them needing to read the rest of the report – in other words, it should be able to stand alone .
For it to stand alone, your abstract should cover the following key points (at a minimum):
- Your research questions and aims – what key question(s) did your research aim to answer?
- Your methodology – how did you go about investigating the topic and finding answers to your research question(s)?
- Your findings – following your own research, what did do you discover?
- Your conclusions – based on your findings, what conclusions did you draw? What answers did you find to your research question(s)?
So, in much the same way the dissertation structure mimics the research process, your abstract or executive summary should reflect the research process, from the initial stage of asking the original question to the final stage of answering that question.
In practical terms, it’s a good idea to write this section up last , once all your core chapters are complete. Otherwise, you’ll end up writing and rewriting this section multiple times (just wasting time). For a step by step guide on how to write a strong executive summary, check out this post .
Need a helping hand?
Table of contents
This section is straightforward. You’ll typically present your table of contents (TOC) first, followed by the two lists – figures and tables. I recommend that you use Microsoft Word’s automatic table of contents generator to generate your TOC. If you’re not familiar with this functionality, the video below explains it simply:
If you find that your table of contents is overly lengthy, consider removing one level of depth. Oftentimes, this can be done without detracting from the usefulness of the TOC.
Right, now that the “admin” sections are out of the way, its time to move on to your core chapters. These chapters are the heart of your dissertation and are where you’ll earn the marks. The first chapter is the introduction chapter – as you would expect, this is the time to introduce your research…
It’s important to understand that even though you’ve provided an overview of your research in your abstract, your introduction needs to be written as if the reader has not read that (remember, the abstract is essentially a standalone document). So, your introduction chapter needs to start from the very beginning, and should address the following questions:
- What will you be investigating (in plain-language, big picture-level)?
- Why is that worth investigating? How is it important to academia or business? How is it sufficiently original?
- What are your research aims and research question(s)? Note that the research questions can sometimes be presented at the end of the literature review (next chapter).
- What is the scope of your study? In other words, what will and won’t you cover ?
- How will you approach your research? In other words, what methodology will you adopt?
- How will you structure your dissertation? What are the core chapters and what will you do in each of them?
These are just the bare basic requirements for your intro chapter. Some universities will want additional bells and whistles in the intro chapter, so be sure to carefully read your brief or consult your research supervisor.
If done right, your introduction chapter will set a clear direction for the rest of your dissertation. Specifically, it will make it clear to the reader (and marker) exactly what you’ll be investigating, why that’s important, and how you’ll be going about the investigation. Conversely, if your introduction chapter leaves a first-time reader wondering what exactly you’ll be researching, you’ve still got some work to do.
Now that you’ve set a clear direction with your introduction chapter, the next step is the literature review . In this section, you will analyse the existing research (typically academic journal articles and high-quality industry publications), with a view to understanding the following questions:
- What does the literature currently say about the topic you’re investigating?
- Is the literature lacking or well established? Is it divided or in disagreement?
- How does your research fit into the bigger picture?
- How does your research contribute something original?
- How does the methodology of previous studies help you develop your own?
Depending on the nature of your study, you may also present a conceptual framework towards the end of your literature review, which you will then test in your actual research.
Again, some universities will want you to focus on some of these areas more than others, some will have additional or fewer requirements, and so on. Therefore, as always, its important to review your brief and/or discuss with your supervisor, so that you know exactly what’s expected of your literature review chapter.
Now that you’ve investigated the current state of knowledge in your literature review chapter and are familiar with the existing key theories, models and frameworks, its time to design your own research. Enter the methodology chapter – the most “science-ey” of the chapters…
In this chapter, you need to address two critical questions:
- Exactly HOW will you carry out your research (i.e. what is your intended research design)?
- Exactly WHY have you chosen to do things this way (i.e. how do you justify your design)?
Remember, the dissertation part of your degree is first and foremost about developing and demonstrating research skills . Therefore, the markers want to see that you know which methods to use, can clearly articulate why you’ve chosen then, and know how to deploy them effectively.
Importantly, this chapter requires detail – don’t hold back on the specifics. State exactly what you’ll be doing, with who, when, for how long, etc. Moreover, for every design choice you make, make sure you justify it.
In practice, you will likely end up coming back to this chapter once you’ve undertaken all your data collection and analysis, and revise it based on changes you made during the analysis phase. This is perfectly fine. Its natural for you to add an additional analysis technique, scrap an old one, etc based on where your data lead you. Of course, I’m talking about small changes here – not a fundamental switch from qualitative to quantitative, which will likely send your supervisor in a spin!
You’ve now collected your data and undertaken your analysis, whether qualitative, quantitative or mixed methods. In this chapter, you’ll present the raw results of your analysis . For example, in the case of a quant study, you’ll present the demographic data, descriptive statistics, inferential statistics , etc.
Typically, Chapter 4 is simply a presentation and description of the data, not a discussion of the meaning of the data. In other words, it’s descriptive, rather than analytical – the meaning is discussed in Chapter 5. However, some universities will want you to combine chapters 4 and 5, so that you both present and interpret the meaning of the data at the same time. Check with your institution what their preference is.
Now that you’ve presented the data analysis results, its time to interpret and analyse them. In other words, its time to discuss what they mean, especially in relation to your research question(s).
What you discuss here will depend largely on your chosen methodology. For example, if you’ve gone the quantitative route, you might discuss the relationships between variables . If you’ve gone the qualitative route, you might discuss key themes and the meanings thereof. It all depends on what your research design choices were.
Most importantly, you need to discuss your results in relation to your research questions and aims, as well as the existing literature. What do the results tell you about your research questions? Are they aligned with the existing research or at odds? If so, why might this be? Dig deep into your findings and explain what the findings suggest, in plain English.
The final chapter – you’ve made it! Now that you’ve discussed your interpretation of the results, its time to bring it back to the beginning with the conclusion chapter . In other words, its time to (attempt to) answer your original research question s (from way back in chapter 1). Clearly state what your conclusions are in terms of your research questions. This might feel a bit repetitive, as you would have touched on this in the previous chapter, but its important to bring the discussion full circle and explicitly state your answer(s) to the research question(s).
Next, you’ll typically discuss the implications of your findings? In other words, you’ve answered your research questions – but what does this mean for the real world (or even for academia)? What should now be done differently, given the new insight you’ve generated?
Lastly, you should discuss the limitations of your research, as well as what this means for future research in the area. No study is perfect, especially not a Masters-level. Discuss the shortcomings of your research. Perhaps your methodology was limited, perhaps your sample size was small or not representative, etc, etc. Don’t be afraid to critique your work – the markers want to see that you can identify the limitations of your work. This is a strength, not a weakness. Be brutal!
This marks the end of your core chapters – woohoo! From here on out, it’s pretty smooth sailing.
The reference list is straightforward. It should contain a list of all resources cited in your dissertation, in the required format, e.g. APA , Harvard, etc.
It’s essential that you use reference management software for your dissertation. Do NOT try handle your referencing manually – its far too error prone. On a reference list of multiple pages, you’re going to make mistake. To this end, I suggest considering either Mendeley or Zotero. Both are free and provide a very straightforward interface to ensure that your referencing is 100% on point. I’ve included a simple how-to video for the Mendeley software (my personal favourite) below:
Some universities may ask you to include a bibliography, as opposed to a reference list. These two things are not the same . A bibliography is similar to a reference list, except that it also includes resources which informed your thinking but were not directly cited in your dissertation. So, double-check your brief and make sure you use the right one.
The very last piece of the puzzle is the appendix or set of appendices. This is where you’ll include any supporting data and evidence. Importantly, supporting is the keyword here.
Your appendices should provide additional “nice to know”, depth-adding information, which is not critical to the core analysis. Appendices should not be used as a way to cut down word count (see this post which covers how to reduce word count ). In other words, don’t place content that is critical to the core analysis here, just to save word count. You will not earn marks on any content in the appendices, so don’t try to play the system!
Time to recap…
And there you have it – the traditional dissertation structure and layout, from A-Z. To recap, the core structure for a dissertation or thesis is (typically) as follows:
- Acknowledgments page
Most importantly, the core chapters should reflect the research process (asking, investigating and answering your research question). Moreover, the research question(s) should form the golden thread throughout your dissertation structure. Everything should revolve around the research questions, and as you’ve seen, they should form both the start point (i.e. introduction chapter) and the endpoint (i.e. conclusion chapter).
I hope this post has provided you with clarity about the traditional dissertation/thesis structure and layout. If you have any questions or comments, please leave a comment below, or feel free to get in touch with us. Also, be sure to check out the rest of the Grad Coach Blog .
Psst… there’s more (for free)
This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project.
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many thanks i found it very useful
Glad to hear that, Arun. Good luck writing your dissertation.
Such clear practical logical advice. I very much needed to read this to keep me focused in stead of fretting.. Perfect now ready to start my research!
what about scientific fields like computer or engineering thesis what is the difference in the structure? thank you very much
Thanks so much this helped me a lot!
Very helpful and accessible. What I like most is how practical the advice is along with helpful tools/ links.
Thank you so much sir.. It was really helpful..
Hi! How many words maximum should contain the abstract?
Thank you so much 😊 Find this at the right moment
You’re most welcome. Good luck with your dissertation.
best ever benefit i got on right time thank you
Many times Clarity and vision of destination of dissertation is what makes the difference between good ,average and great researchers the same way a great automobile driver is fast with clarity of address and Clear weather conditions .
I guess Great researcher = great ideas + knowledge + great and fast data collection and modeling + great writing + high clarity on all these
You have given immense clarity from start to end.
Morning. Where will I write the definitions of what I’m referring to in my report?
Thank you so much Derek, I was almost lost! Thanks a tonnnn! Have a great day!
Thanks ! so concise and valuable
This was very helpful. Clear and concise. I know exactly what to do now.
Thank you for allowing me to go through briefly. I hope to find time to continue.
Really useful to me. Thanks a thousand times
Very interesting! It will definitely set me and many more for success. highly recommended.
Thank you soo much sir, for the opportunity to express my skills
Usefull, thanks a lot. Really clear
That was incredibly useful. Thanks Grad Coach Crew!
My stress level just dropped at least 15 points after watching this. Just starting my thesis for my grad program and I feel a lot more capable now! Thanks for such a clear and helpful video, Emma and the GradCoach team!
Do we need to mention the number of words the dissertation contains in the main document?
It depends on your university’s requirements, so it would be best to check with them 🙂
Such a helpful post to help me get started with structuring my masters dissertation, thank you!
Great video; I appreciate that helpful information
It is so necessary or avital course
This blog is very informative for my research. Thank you
Doctoral students are required to fill out the National Research Council’s Survey of Earned Doctorates
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This is so good
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How to Structure a Dissertation – A Step by Step Guide
Published by Owen Ingram at August 11th, 2021 , Revised On September 20, 2023
A dissertation – sometimes called a thesis – is a long piece of information backed up by extensive research. This one, huge piece of research is what matters the most when students – undergraduates and postgraduates – are in their final year of study.
On the other hand, some institutions, especially in the case of undergraduate students, may or may not require students to write a dissertation. Courses are offered instead. This generally depends on the requirements of that particular institution.
If you are unsure about how to structure your dissertation or thesis, this article will offer you some guidelines to work out what the most important segments of a dissertation paper are and how you should organise them. Why is structure so important in research, anyway?
One way to answer that, as Abbie Hoffman aptly put it, is because: “Structure is more important than content in the transmission of information.”
Also Read: How to write a dissertation – step by step guide .
How to Structure a Dissertation or Thesis
It should be noted that the exact structure of your dissertation will depend on several factors, such as:
- Your research approach (qualitative/quantitative)
- The nature of your research design (exploratory/descriptive etc.)
- The requirements set for forth by your academic institution.
- The discipline or field your study belongs to. For instance, if you are a humanities student, you will need to develop your dissertation on the same pattern as any long essay .
This will include developing an overall argument to support the thesis statement and organizing chapters around theories or questions. The dissertation will be structured such that it starts with an introduction , develops on the main idea in its main body paragraphs and is then summarised in conclusion .
However, if you are basing your dissertation on primary or empirical research, you will be required to include each of the below components. In most cases of dissertation writing, each of these elements will have to be written as a separate chapter.
But depending on the word count you are provided with and academic subject, you may choose to combine some of these elements.
For example, sciences and engineering students often present results and discussions together in one chapter rather than two different chapters.
If you have any doubts about structuring your dissertation or thesis, it would be a good idea to consult with your academic supervisor and check your department’s requirements.
Parts of a Dissertation or Thesis
Your dissertation will start with a t itle page that will contain details of the author/researcher, research topic, degree program (the paper is to be submitted for), and research supervisor. In other words, a title page is the opening page containing all the names and title related to your research.
The name of your university, logo, student ID and submission date can also be presented on the title page. Many academic programs have stringent rules for formatting the dissertation title page.
The acknowledgments section allows you to thank those who helped you with your dissertation project. You might want to mention the names of your academic supervisor, family members, friends, God, and participants of your study whose contribution and support enabled you to complete your work.
However, the acknowledgments section is usually optional.
Tip: Many students wrongly assume that they need to thank everyone…even those who had little to no contributions towards the dissertation. This is not the case. You only need to thank those who were directly involved in the research process, such as your participants/volunteers, supervisor(s) etc.
Perhaps the smallest yet important part of a thesis, an abstract contains 5 parts:
- A brief introduction of your research topic.
- The significance of your research.
- A line or two about the methodology that was used.
- The results and what they mean (briefly); their interpretation(s).
- And lastly, a conclusive comment regarding the results’ interpretation(s) as conclusion .
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Tip: Make sure to highlight key points to help readers figure out the scope and findings of your research study without having to read the entire dissertation. The abstract is your first chance to impress your readers. So, make sure to get it right. Here are detailed guidelines on how to write abstract for dissertation .
Table of Contents
Table of contents is the section of a dissertation that guides each section of the dissertation paper’s contents. Depending on the level of detail in a table of contents, the most useful headings are listed to provide the reader the page number on which said information may be found at.
Table of contents can be inserted automatically as well as manually using the Microsoft Word Table of Contents feature.
List of Figures and Tables
If your dissertation paper uses several illustrations, tables and figures, you might want to present them in a numbered list in a separate section . Again, this list of tables and figures can be auto-created and auto inserted using the Microsoft Word built-in feature.
List of Abbreviations
Dissertations that include several abbreviations can also have an independent and separate alphabetised list of abbreviations so readers can easily figure out their meanings.
If you think you have used terms and phrases in your dissertation that readers might not be familiar with, you can create a glossary that lists important phrases and terms with their meanings explained.
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Introduction chapter briefly introduces the purpose and relevance of your research topic.
Here, you will be expected to list the aim and key objectives of your research so your readers can easily understand what the following chapters of the dissertation will cover. A good dissertation introduction section incorporates the following information:
- It provides background information to give context to your research.
- It clearly specifies the research problem you wish to address with your research. When creating research questions , it is important to make sure your research’s focus and scope are neither too broad nor too narrow.
- it demonstrates how your research is relevant and how it would contribute to the existing knowledge.
- It provides an overview of the structure of your dissertation. The last section of an introduction contains an outline of the following chapters. It could start off with something like: “In the following chapter, past literature has been reviewed and critiqued. The proceeding section lays down major research findings…”
- Theoretical framework – under a separate sub-heading – is also provided within the introductory chapter. Theoretical framework deals with the basic, underlying theory or theories that the research revolves around.
All the information presented under this section should be relevant, clear, and engaging. The readers should be able to figure out the what, why, when, and how of your study once they have read the introduction. Here are comprehensive guidelines on how to structure the introduction to the dissertation .
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The literature review chapter presents previous research performed on the topic and improves your understanding of the existing literature on your chosen topic. This is usually organised to complement your primary research work completed at a later stage.
Make sure that your chosen academic sources are authentic and up-to-date. The literature review chapter must be comprehensive and address the aims and objectives as defined in the introduction chapter. Here is what your literature research chapter should aim to achieve:
- Data collection from authentic and relevant academic sources such as books, journal articles and research papers.
- Analytical assessment of the information collected from those sources; this would involve a critiquing the reviewed researches that is, what their strengths/weaknesses are, why the research method they employed is better than others, importance of their findings, etc.
- Identifying key research gaps, conflicts, patterns, and theories to get your point across to the reader effectively.
While your literature review should summarise previous literature, it is equally important to make sure that you develop a comprehensible argument or structure to justify your research topic. It would help if you considered keeping the following questions in mind when writing the literature review:
- How does your research work fill a certain gap in exiting literature?
- Did you adopt/adapt a new research approach to investigate the topic?
- Does your research solve an unresolved problem?
- Is your research dealing with some groundbreaking topic or theory that others might have overlooked?
- Is your research taking forward an existing theoretical discussion?
- Does your research strengthen and build on current knowledge within your area of study? This is otherwise known as ‘adding to the existing body of knowledge’ in academic circles.
Tip: You might want to establish relationships between variables/concepts to provide descriptive answers to some or all of your research questions. For instance, in case of quantitative research, you might hypothesise that variable A is positively co-related to variable B that is, one increases and so does the other one.
The methods and techniques ( secondary and/or primar y) employed to collect research data are discussed in detail in the Methodology chapter. The most commonly used primary data collection methods are:
- focus groups
Essentially, the methodology chapter allows the researcher to explain how he/she achieved the findings, why they are reliable and how they helped him/her test the research hypotheses or address the research problem.
You might want to consider the following when writing methodology for the dissertation:
- Type of research and approach your work is based on. Some of the most widely used types of research include experimental, quantitative and qualitative methodologies.
- Data collection techniques that were employed such as questionnaires, surveys, focus groups, observations etc.
- Details of how, when, where, and what of the research that was conducted.
- Data analysis strategies employed (for instance, regression analysis).
- Software and tools used for data analysis (Excel, STATA, SPSS, lab equipment, etc.).
- Research limitations to highlight any hurdles you had to overcome when carrying our research. Limitations might or might not be mentioned within research methodology. Some institutions’ guidelines dictate they be mentioned under a separate section alongside recommendations.
- Justification of your selection of research approach and research methodology.
Here is a comprehensive article on how to structure a dissertation methodology .
In this section, you present your research findings. The dissertation findings chapter is built around the research questions, as outlined in the introduction chapter. Report findings that are directly relevant to your research questions.
Any information that is not directly relevant to research questions or hypotheses but could be useful for the readers can be placed under the Appendices .
As indicated above, you can either develop a standalone chapter to present your findings or combine them with the discussion chapter. This choice depends on the type of research involved and the academic subject, as well as what your institution’s academic guidelines dictate.
For example, it is common to have both findings and discussion grouped under the same section, particularly if the dissertation is based on qualitative research data.
On the other hand, dissertations that use quantitative or experimental data should present findings and analysis/discussion in two separate chapters. Here are some sample dissertations to help you figure out the best structure for your own project.
Tip: Try to present as many charts, graphs, illustrations and tables in the findings chapter to improve your data presentation. Provide their qualitative interpretations alongside, too. Refrain from explaining the information that is already evident from figures and tables.
The findings are followed by the Discussion chapter , which is considered the heart of any dissertation paper. The discussion section is an opportunity for you to tie the knots together to address the research questions and present arguments, models and key themes.
This chapter can make or break your research.
The discussion chapter does not require any new data or information because it is more about the interpretation(s) of the data you have already collected and presented. Here are some questions for you to think over when writing the discussion chapter:
- Did your work answer all the research questions or tested the hypothesis?
- Did you come up with some unexpected results for which you have to provide an additional explanation or justification?
- Are there any limitations that could have influenced your research findings?
Here is an article on how to structure a dissertation discussion .
Conclusions corresponding to each research objective are provided in the Conclusion section . This is usually done by revisiting the research questions to finally close the dissertation. Some institutions may specifically ask for recommendations to evaluate your critical thinking.
By the end, the readers should have a clear apprehension of your fundamental case with a focus on what methods of research were employed and what you achieved from this research.
Quick Question: Does the conclusion chapter reflect on the contributions your research work will make to existing knowledge?
Answer: Yes, the conclusion chapter of the research paper typically includes a reflection on the research’s contributions to existing knowledge. In the “conclusion chapter”, you have to summarise the key findings and discuss how they add value to the existing literature on the current topic.
All academic sources that you collected information from should be cited in-text and also presented in a reference list (or a bibliography in case you include references that you read for the research but didn’t end up citing in the text), so the readers can easily locate the source of information when/if needed.
At most UK universities, Harvard referencing is the recommended style of referencing. It has strict and specific requirements on how to format a reference resource. Other common styles of referencing include MLA, APA, Footnotes, etc.
Each chapter of the dissertation should have relevant information. Any information that is not directly relevant to your research topic but your readers might be interested in (interview transcripts etc.) should be moved under the Appendices section .
Things like questionnaires, survey items or readings that were used in the study’s experiment are mostly included under appendices.
An Outline of Dissertation/Thesis Structure
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FAQs About Structure a Dissertation
What does the title page of a dissertation contain.
The title page will contain details of the author/researcher, research topic , degree program (the paper is to be submitted for) and research supervisor’s name(s). The name of your university, logo, student number and submission date can also be presented on the title page.
What is the purpose of adding acknowledgement?
The acknowledgements section allows you to thank those who helped you with your dissertation project. You might want to mention the names of your academic supervisor, family members, friends, God and participants of your study whose contribution and support enabled you to complete your work.
Can I omit the glossary from the dissertation?
Yes, but only if you think that your paper does not contain any terms or phrases that the reader might not understand. If you think you have used them in the paper, you must create a glossary that lists important phrases and terms with their meanings explained.
What is the purpose of appendices in a dissertation?
Any information that is not directly relevant to research questions or hypotheses but could be useful for the readers can be placed under the Appendices, such as questionnaire that was used in the study.
Which referencing style should I use in my dissertation?
You can use any of the referencing styles such as APA, MLA, and Harvard, according to the recommendation of your university; however, almost all UK institutions prefer Harvard referencing style .
What is the difference between references and bibliography?
References contain all the works that you read up and used and therefore, cited within the text of your thesis. However, in case you read on some works and resources that you didn’t end up citing in-text, they will be referenced in what is called a bibliography.
Additional readings might also be present alongside each bibliography entry for readers.
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This brief introductory section aims to deal with the definitions of two paradigms, positivism and post-positivism, as well as their importance in research.
Anyone who supports you in your research should be acknowledged in dissertation acknowledgments. Learn more on how to write dissertation acknowledgements.
Dissertation discussion is where you explore the relevance and significance of results. Here are guidelines to help you write the perfect discussion chapter.
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Writing the Research Methodology Section of Your Thesis
This article explains the meaning of research methodology and the purpose and importance of writing a research methodology section or chapter for your thesis paper. It discusses what to include and not include in a research methodology section, the different approaches to research methodology that can be used, and the steps involved in writing a robust research methodology section.
What is a thesis research methodology?
A thesis research methodology explains the type of research performed, justifies the methods that you chose by linking back to the literature review , and describes the data collection and analysis procedures. It is included in your thesis after the Introduction section . Most importantly, this is the section where the readers of your study evaluate its validity and reliability.
What should the research methodology section in your thesis include?
- The aim of your thesis
- An outline of the research methods chosen (qualitative, quantitative, or mixed methods)
- Background and rationale for the methods chosen, explaining why one method was chosen over another
- Methods used for data collection and data analysis
- Materials and equipment used—keep this brief
- Difficulties encountered during data collection and analysis. It is expected that problems will occur during your research process. Use this as an opportunity to demonstrate your problem-solving abilities by explaining how you overcame all obstacles. This builds your readers’ confidence in your study findings.
- A brief evaluation of your research explaining whether your results were conclusive and whether your choice of methodology was effective in practice
What should not be included in the research methodology section of your thesis?
- Irrelevant details, for example, an extensive review of methodologies (this belongs in the literature review section) or information that does not contribute to the readers’ understanding of your chosen methods
- A description of basic procedures
- Excessive details about materials and equipment used. If an extremely long and detailed list is necessary, add it as an appendix
Types of methodological approaches
The choice of which methodological approach to use depends on your field of research and your thesis question. Your methodology should establish a clear relationship with your thesis question and must also be supported by your literature review . Types of methodological approaches include quantitative, qualitative, or mixed methods.
Quantitative studies generate data in the form of numbers to count, classify, measure, or identify relationships or patterns. Information may be collected by performing experiments and tests, conducting surveys, or using existing data. The data are analyzed using statistical tests and presented as charts or graphs. Quantitative data are typically used in the Sciences domain.
For example, analyzing the effect of a change, such as alterations in electricity consumption by municipalities after installing LED streetlights.
The raw data will need to be prepared for statistical analysis by identifying variables and checking for missing data and outliers. Details of the statistical software program used (name of the package, version number, and supplier name and location) must also be mentioned.
Qualitative studies gather non-numerical data using, for example, observations, focus groups, and in-depth interviews. Open-ended questions are often posed. This yields rich, detailed, and descriptive results. Qualitative studies are usually subjective and are helpful for investigating social and cultural phenomena, which are difficult to quantify. Qualitative studies are typically used in the Humanities and Social Sciences (HSS) domain.
For example, determining customer perceptions on the extension of a range of baking utensils to include silicone muffin trays.
The raw data will need to be prepared for analysis by coding and categorizing ideas and themes to interpret the meaning behind the responses given.
Mixed methods use a combination of quantitative and qualitative approaches to present multiple findings about a single phenomenon. T his enables triangulation: verification of the data from two or more sources.
Explain the rationale behind the sampling procedure you have chosen. This could involve probability sampling (a random sample from the study population) or non-probability sampling (does not use a random sample).
For quantitative studies, describe the sampling procedure and whether statistical tests were used to determine the sample size .
Following our example of analyzing the changes in electricity consumption by municipalities after installing LED streetlights, you will need to determine which municipal areas will be sampled and how the information will be gathered (e.g., a physical survey of the streetlights or reviewing purchase orders).
For qualitative research, describe how the participants were chosen and how the data is going to be collected.
Following our example about determining customer perceptions on the extension of a range of baking utensils to include silicone muffin trays, you will need to decide the criteria for inclusion as a study participant (e.g., women aged 20–70 years, bakeries, and bakery supply shops) and how the information will be collected (e.g., interviews, focus groups, online or in-person questionnaires, or video recordings) .
For quantitative research, describe what tests you plan to perform and why you have chosen them. Popular data analysis methods in quantitative research include:
- Descriptive statistics (e.g., means, medians, modes)
- Inferential statistics (e.g., correlation, regression, structural equation modeling)
For qualitative research, describe how the data is going to be analyzed and justify your choice. Popular data analysis methods in qualitative research include:
- Qualitative content analysis
- Thematic analysis
- Discourse analysis
- Narrative analysis
- Grounded theory
- Interpretative phenomenological analysis (IPA)
Evaluate and justify your methodological choices
You need to convince the reader that you have made the correct methodological choices. Once again, this ties back to your thesis question and literature review . Write using a persuasive tone, and use rhetoric to convince the reader of the quality, reliability, and validity of your research.
- The young researcher should maintain objectivity at all times
- All participants have the right to privacy and anonymity
- Research participation must be voluntary
- All subjects have the right to withdraw from the research at any time
- Consent must be obtained from all participants before starting the research
- Confidentiality of data provided by individuals must be maintained
- Consider how the interpretation and reporting of the data will affect the participants
Tips for writing a robust thesis research methodology
- Determine what kind of knowledge you are trying to uncover. For example, subjective or objective, experimental or interpretive.
- A thorough literature review is the best starting point for choosing your methods.
- Ensure that there is continuity throughout the research process. The authenticity of your research depends upon the validity of the research data, the reliability of your data measurements, and the time taken to conduct the analysis.
- Choose a research method that is achievable. Consider the time and funds available, feasibility, ethics, and access and availability of equipment to measure the phenomenon or answer your thesis question correctly.
- If you are struggling with a concept, ask for help from your supervisor, academic staff members, or fellow students.
A thesis methodology justifies why you have chosen a specific approach to address your thesis question. It explains how you will collect the data and analyze it. Above all, it allows the readers of your study to evaluate its validity and reliability.
A thesis is the most crucial document that you will write during your academic studies. For professional thesis editing and thesis proofreading services, visit Enago Thesis Editing for more information.
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Introduce your methodological approach , for example, quantitative, qualitative, or mixed methods.
Explain why your chosen approach is relevant to the overall research design and how it links with your thesis question.
Justify your chosen method and why it is more appropriate than others.
Provide background information on methods that may be unfamiliar to readers of your thesis.
Introduce the tools that you will use for data collection , and explain how you plan to use them (e.g., surveys, interviews, experiments, or existing data).
Explain how you will analyze your results. The type of analysis used depends on the methods you chose. For example, exploring theoretical perspectives to support your explanation of observed behaviors in a qualitative study or using statistical analyses in a quantitative study.
Mention any research limitations. All studies are expected to have limitations, such as the sample size, data collection method, or equipment. Discussing the limitations justifies your choice of methodology despite the risks. It also explains under which conditions the results should be interpreted and shows that you have taken a holistic approach to your study.
What is the difference between methodology and methods? +
Methodology refers to the overall rationale and strategy of your thesis project. It involves studying the theories or principles behind the methods used in your field so that you can explain why you chose a particular method for your research approach. Methods , on the other hand, refer to how the data were collected and analyzed (e.g., experiments, surveys, observations, interviews, and statistical tests).
What is the difference between reliability and validity? +
Reliability refers to whether a measurement is consistent (i.e., the results can be reproduced under the same conditions). Validity refers to whether a measurement is accurate (i.e., the results represent what was supposed to be measured). For example, when investigating linguistic and cultural guidelines for administration of the Preschool Language Scales, Fifth Edition (PLS5) in Arab-American preschool children, the normative sample curves should show the same distribution as a monolingual population, which would indicate that the test is valid. The test would be considered reliable if the results obtained were consistent across different sampling sites.
What tense is used to write the methods section? +
The methods section is written in the past tense because it describes what was done.
What software programs are recommended for statistical analysis? +
Recommended programs include Statistical Analysis Software (SAS) , Statistical Package for the Social Sciences (SPSS) , JMP , R software, MATLAB , Microsoft Excel, GraphPad Prism , and Minitab .
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The Top 3 Types of Dissertation Research Explained
Preparing for your doctoral dissertation takes serious perseverance. You’ve endured years of studies and professional development to get to this point. After sleepless nights and labor-intensive research, you’re ready to present the culmination of all of your hard work. Even with a strong base knowledge, it can be difficult — even daunting — to decide how you will begin writing.
By taking a wide-lens view of the dissertation research process , you can best assess the work you have ahead of you and any gaps in your current research strategy. Subsequently, you’ll begin to develop a timeline so you can work efficiently and cross that finish line with your degree in hand.
What Is a Dissertation?
A dissertation is a published piece of research on a novel topic in your chosen field. Students complete a dissertation as part of a doctoral or PhD program. For most students, a dissertation is the first substantive piece of academic research they will write.
Because a dissertation becomes a published piece of academic literature that other academics may cite, students must defend it in front of a board of experts consisting of peers in their field, including professors, their advisor, and other industry experts.
For many students, a dissertation is the first piece of research in a long career full of research. As such, it’s important to choose a topic that’s interesting and engaging.
Types of Dissertation Research
Dissertations can take on many forms, based on research and methods of presentation in front of a committee board of academics and experts in the field. Here, we’ll focus on the three main types of dissertation research to get you one step closer to earning your doctoral degree.
The first type of dissertation is known as a qualitative dissertation . A qualitative dissertation mirrors the qualitative research that a doctoral candidate would conduct throughout their studies. This type of research relies on non-numbers-based data collected through things like interviews, focus groups and participant observation.
The decision to model your dissertation research according to the qualitative method will depend largely on the data itself that you are collecting. For example, dissertation research in the field of education or psychology may lend itself to a qualitative approach, depending on the essence of research. Within a qualitative dissertation research model, a candidate may pursue one or more of the following:
- Case study research
- Narrative research
- Grounded theory
Although individual approaches may vary, qualitative dissertations usually include certain foundational characteristics. For example, the type of research conducted to develop a qualitative dissertation often follows an emergent design, meaning that the content and research strategy changes over time. Candidates also rely on research paradigms to further strategize how best to collect and relay their findings. These include critical theory, constructivism and interpretivism, to name a few.
Because qualitative researchers integrate non-numerical data, their methods of collection often include unstructured interview, focus groups and participant observations. Of course, researchers still need rubrics from which to assess the quality of their findings, even though they won’t be numbers-based. To do so, they subject the data collected to the following criteria: dependability, transferability and validity.
When it comes time to present their findings, doctoral candidates who produce qualitative dissertation research have several options. Some choose to include case studies, personal findings, narratives, observations and abstracts. Their presentation focuses on theoretical insights based on relevant data points.
Quantitative dissertation research, on the other hand, focuses on the numbers. Candidates employ quantitative research methods to aggregate data that can be easily categorized and analyzed. In addition to traditional statistical analysis, quantitative research also hones specific research strategy based on the type of research questions. Quantitative candidates may also employ theory-driven research, replication-based studies and data-driven dissertations.
When conducting research, some candidates who rely on quantitative measures focus their work on testing existing theories, while others create an original approach. To refine their approach, quantitative researchers focus on positivist or post-positivist research paradigms. Quantitative research designs focus on descriptive, experimental or relationship-based designs, to name a few.
To collect the data itself, researchers focus on questionnaires and surveys, structured interviews and observations, data sets and laboratory-based methods. Then, once it’s time to assess the quality of the data, quantitative researchers measure their results against a set of criteria, including: reliability, internal/external validity and construct validity. Quantitative researchers have options when presenting their findings. Candidates convey their results using graphs, data, tables and analytical statements.
Many PhD candidates also use a hybrid model in which they employ both qualitative and quantitative methods of research. Mixed dissertation research models are fairly new and gaining traction. For a variety of reasons, a mixed-method approach offers candidates both versatility and credibility. It’s a more comprehensive strategy that allows for a wider capture of data with a wide range of presentation optimization.
In the most common cases, candidates will first use quantitative methods to collect and categorize their data. Then, they’ll rely on qualitative methods to analyze that data and draw meaningful conclusions to relay to their committee panel.
With a mixed-method approach, although you’re able to collect and analyze a more broad range of data, you run the risk of widening the scope of your dissertation research so much that you’re not able to reach succinct, sustainable conclusions. This is where it becomes critical to outline your research goals and strategy early on in the dissertation process so that the techniques you use to capture data have been thoroughly examined.
How to Choose a Type of Dissertation Research That’s Right for You
After this overview of application and function, you may still be wondering how to go about choosing a dissertation type that’s right for you and your research proposition. In doing so, you’ll have a couple of things to consider:
- What are your personal motivations?
- What are your academic goals?
It’s important to discern exactly what you hope to get out of your doctoral program . Of course, the presentation of your dissertation is, formally speaking, the pinnacle of your research. However, doctoral candidates must also consider:
- Which contributions they will make to the field
- Who they hope to collaborate with throughout their studies
- What they hope to take away from the experience personally, professionally and academically
To discern which type of dissertation research to choose, you have to take a closer look at your learning style, work ethic and even your personality.
Quantitative research tends to be sequential and patterned-oriented. Steps move in a logical order, so it becomes clear what the next step should be at all times. For most candidates, this makes it easier to devise a timeline and stay on track. It also keeps you from getting overwhelmed by the magnitude of research involved. You’ll be able to assess your progress and make simple adjustments to stay on target.
On the other hand, maybe you know that your research will involve many interviews and focus groups. You anticipate that you’ll have to coordinate participants’ schedules, and this will require some flexibility. Instead of creating a rigid schedule from the get-go, allowing your research to flow in a non-linear fashion may actually help you accomplish tasks more efficiently, albeit out of order. This also allows you the personal versatility of rerouting research strategy as you collect new data that leads you down other paths.
After examining the research you need to conduct, consider more broadly: What type of student and researcher are you? In other words, What motivates you to do your best work?
You’ll need to make sure that your methodology is conducive to the data you’re collecting, and you also need to make sure that it aligns with your work ethic so you set yourself up for success. If jumping from one task to another will cause you extra stress, but planning ahead puts you at ease, a quantitative research method may be best, assuming the type of research allows for this.
The skills you master while working on your dissertation will serve you well beyond the day you earn your degree. Take into account the skills you’d like to develop for your academic and professional future. In addition to the hard skills you will develop in your area of expertise, you’ll also develop soft skills that are transferable to nearly any professional or academic setting. Perhaps you want to hone your ability to strategize a timeline, gather data efficiently or draw clear conclusions about the significance of your data collection.
If you have considerable experience with quantitative analysis, but lack an extensive qualitative research portfolio, now may be your opportunity to explore — as long as you’re willing to put in the legwork to refine your skills or work closely with your mentor to develop a strategy together.
For many doctoral candidates who hope to pursue a professional career in the world of academia, writing your dissertation is a practice in developing general research strategies that can be applied to any academic project.
Candidates who are unsure which dissertation type best suits their research should consider whether they will take a philosophical or theoretical approach or come up with a thesis that addresses a specific problem or idea. Narrowing down this approach can sometimes happen even before the research begins. Other times, candidates begin to refine their methods once the data begins to tell a more concrete story.
Next Step: Structuring Your Dissertation Research Schedule
Once you’ve chosen which type of dissertation research you’ll pursue, you’ve already crossed the first hurdle. The next hurdle becomes when and where to fit dedicated research time and visits with your mentor into your schedule. The busyness of day-to-day life shouldn’t prevent you from making your academic dream a reality. In fact, search for programs that assist, not impede, your path to higher levels of academic success.
Find out more about SNU’s online and on-campus education opportunities so that no matter where you are in life, you can choose the path that’s right for you.
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School of Public Health 2023–2024
- Yale University Publications /
- School of Public Health /
- Appendix II: Thesis Guidelines /
Types of Theses
The following five types of theses are acceptable:
The investigative thesis takes an in-depth look at a specific health problem or topic, describing its public health importance and analyzing it from a disciplined perspective. This thesis should include the following:
- Definition of the problem,
- Presentation of the study population and the methods by which data were acquired,
- Analysis of the results,
- Discussion of the implications of the results, and
Research Study Demonstrating Mastery of Methodology
This type of thesis requires sophisticated analysis and application. Consequently, students should be sure of their readiness to undertake it. This thesis should include the following:
- Statement of methodological problem;
- Comparison of available solutions, discussing the advantages and disadvantages of each; and
- Either (a) choice and application of one of the available solutions, or (b) development of a new solution with discussion of the advantages and disadvantages of that solution.
Administrative Case Study
An administrative thesis defines, describes, analyzes, and interprets an actual administrative, problem-solving activity undertaken during a student’s field work. A variety of standard case study formats may be employed. An administrative case study thesis should be planned in advance with appropriate techniques for systematic observation and recording of data as the project progresses. This thesis usually includes the following:
- Definition of the problem;
- Description of setting, structure, function, and relationships;
- Relationship of student to problem (authority and accountability);
- Procedural description (case description, process, outcome);
- Analysis of events with reference to theory; and
- Assessment of the administrative solution.
Program Analysis, Evaluation, or Projection
This type of thesis examines either retrospectively or prospectively some particular health problem. This thesis should include the following:
- Definition of the problem that the program addresses,
- Statement of program goals and objectives, and
- Target population (characteristics, distribution, levels of protection, morbidity);
- Historical information, goals, politics;
- Resources and use of resources (acceptability, accessibility);
- Basis of intervention, data on knowledge, attitudes and practices;
- Cost analysis; and
- Specification of further data needs.
This type of thesis incorporates a product useful in the teaching or practice of public health such as a curriculum, syllabus, or course for a school program or on-the-job training; specific educational aids (perhaps a computer-assisted learning experience, a programmed instruction course, or a training manual); a movie, videotape, or slide package; a pamphlet for use in health information; a set of formal administrative guidelines to implement a law or administrative decision; or architectural plans for a health facility.
In addition to the product, the student must produce a written analysis that includes the following:
- A rationale for the product and the anticipated audience/users;
- Review of relevant literature;
- Reasons for the selection of the chosen medium/method, including relevant theory;
- Proposal for method to evaluate the product; and
- Discussion of the limitations of the product.
The special project may require review by the Committee on Academic Progress.
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Methodology chapter of your dissertation should include discussions about the methods of data analysis. You have to explain in a brief manner how you are going to analyze the primary data you will collect employing the methods explained in this chapter.
There are differences between qualitative data analysis and quantitative data analysis . In qualitative researches using interviews, focus groups, experiments etc. data analysis is going to involve identifying common patterns within the responses and critically analyzing them in order to achieve research aims and objectives.
Data analysis for quantitative studies, on the other hand, involves critical analysis and interpretation of figures and numbers, and attempts to find rationale behind the emergence of main findings. Comparisons of primary research findings to the findings of the literature review are critically important for both types of studies – qualitative and quantitative.
Data analysis methods in the absence of primary data collection can involve discussing common patterns, as well as, controversies within secondary data directly related to the research area.
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How Do You Analyze Data for Dissertation
- March 4, 2020
- Dissertation Center
How do you analyze data for a dissertation?
These steps will guide you through a step-by-step guide in analyzing data.
Step 1: Data organization – The researcher should be able to identify the difference between the topics/questions including those that have been comprised in the interview guide as essential.
Step 2: organizing and finding ideas and concepts – acknowledge the frequently used phrases as well as ideas emanating from the interviewee
Step 3: Constructing all-embracing themes – Every response category should entail one or more linked ideas that issue an in-depth meaning of the data.
Step 4: Guaranteeing reliability and validity in data analysis – Ensuring safety necessitates diligent determinations and an obligation to consistency all through interviewing, transcribing, and analyzing the outcomes.
Step 5: Identifying any possible and plausible clarifications for findings – this will enable the researcher to tie themes and come up with a better idea of the results attained.
Step 6: A summary of the last steps – The research findings should assist not only in identifying the strategies but also in bringing about change and being responsive to the needs of a community.
How do you write a data analysis chapter for a dissertation?
Your dissertation data analysis section should consist of the following:
- An in-depth description of the hypothesis and the research questions.
- A brief overview that includes; the study purpose, steps in conducting the research, description of the type of data, data collection instruments that had been used, including assumptions made during the study.
- A conclusion of every question distinctly and the intuition drew by the researcher from the analysis.
- Detailed data collected, and the numerous mathematical, statistical, and qualitative analyses performed.
- A summary paragraph with a brief review of the chapter
Some of the best practices to follow while writing the analysis section
- Once any new theme surfaces from the analysis, then the researcher should acknowledge that linking such to an appropriate conclusion drawn from the study.
- Provide a judgment and critical view for the results provided by the analysis.
- Ensure to reference the analysis with the literature review, i.e., through cross-referencing.
- Avoiding jargon and defining technical terms used in the analysis
- Ensure the introductory article explains the chapter.
- Follow a theme based structure that is the same as that of the literature review.
What to include in the data analysis section
- The objective of the study
- Listing of data set
- Discussion of results and conclusions
- Review of findings relative to previous studies
- Recommendations for future studies
- Description of all statistical methodologies
- Study design and data collection methods
- Statistical and graphical summaries of data
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What is data analysis?
Data analysis infers to a process of cleaning, inspecting, and modeling data and to discover valuable information, bringing to a conclusion and that which supports decision making. Analyzing data entails numerous facets and approaches necessitating varied techniques under various names and domains.
What is the data analysis technique?
Numerous types of analysis techniques exist based on technology and business; significant data analysis techniques include:
This analysis combines the insight from the previous study in determining which action to take in the immediate decision or problem.
Also identified as data mining, this method helps in discovering patterns in large sets of data using databases or data mining tools. This used to transform the raw data into information. In a general view, text analysis offers a way to extract and examine data alongside deriving patterns and finally interpreting the data.
The statistical analysis illustrates the happenings by using past data in the form of a dashboard. The statistical analysis includes data analysis, collection, presentation, interpretation, and modelling. (Descriptive analysis and inferential analysis)
The following analysis predicts future outcomes founded on the present or past data. The accuracy in the subsequent investigation is based on how much detailed information one has and how much the researcher digs in it.
This illustrates why it happened by identifying the cause of the insight found in statistical analysis. This analysis is essential as it determines the behavior pattern of data.
What is the Data analysis process?
In summary, below are the necessary steps to analyze data and solve problems
- Define Analytic Objective – As said, defining your question is 50% of the solution, so you need to set your problem and the scope of your analysis.
- Extract Input data – Based on the problem description, you will need to select your input data and extract them for analysis carefully.
- Validate input data – Check the input data for accuracy and consistency.
- Repair input data – Fix what could be there in data like null values.
- Transform input data – Apply the required transformations for each field if necessary.
- Apply analysis – Perform your analysis using your preferred tool and algorithm.
- Generate deployment method – Build the deployment package for your model.
- Assess results – Check and validate your conclusion to make sure they are accurate.
- Refine analytic objective – Refine your algorithm or analysis method if required
What are the types of Data analysis?
There exist four forms of data analysis implemented across all sectors. Whereas these are separated into categories, these are built upon each other and linked together. While you begin moving from the most straightforward style of analytics forward, the level of difficulty and resources also hikes. Similarly, the level of added insight and value also rises. The four types of data analysis include:
- Predictive analysis – attempts to answer the question of what is likely to happen.
- Prescriptive analysis – this merges the insight from the past reviews and in determining the actions taken in solving a current problem and formulating a decision.
- Descriptive analysis – this an analysis that gives answers to the “what happened” by summarizing past data, usually in the form of dashboards’
- Diagnostic analysis – answers the “why did it happen?” that builds off descriptive analysis.
What are the methods of data analysis ?
There are numerous methods used in analyzing data, all of which fall under two primary approaches that include quantitative analysis and qualitative data analysis.
Qualitative data analysis
The data obtained through this method consist of pictures, words, observations, and symbols. The following type of analysis infers to a process utilized for the data analysis and to provide some level of understanding, interpretation, or understanding. This type of data can be collected in numerous approaches, such as:
- Content analysis – this used to analyze behavioral or verbal data; this data consists of communication artifacts or documents in various formats, audio, or pictures.
- Narrative analysis – this majorly implemented, and it involves data from numerous sources such as surveys, field notes, and interviews. This includes reformulating the stories issued by individuals, depending on one’s experiences and variance in context.
- Grounded theory – this a form of analysis that is majorly implemented by researchers; this includes the creation of causal explanations of the single occurrence from the study of one or more cases. In further conducting the research, an example is altered until the researchers arrive at a statement that brings together all the circumstances.
This used for the qualification of data, which enables the generalization of the results obtained from a sample to a population’s interest. Some of the methodologies that fall under quantitative data include:
- Mean – also identified as the average, mean is the most common method of analyzing data whereby the sum of the lists of the number is divided by the number of items in the same list.
- Hypothesis testing – this mainly used in business research and is done to assess whether a given hypothesis or theory for a population or data set is precise.
- Sample size determination – when researching a large population, small sample-sized is taken into consideration, analyzed, and the results considered almost the same for every member of the community.
How do you analyze a dissertation interview?
Qualitative analysis of interview data
1. Reading the transcripts
- Quickly browse through the entire transcript.
- Create notes about your first impression.
- Re-read the transcripts again.
2. Labeling the relevant pieces
- Label the appropriate phrase, word, section, or sentence; the labels can be about activities, actions, opinions, processes, differences, or that which is relevant.
3. Decide which codes are relevant and create categories by bringing the systems together.
- Revising the codes in the previous step
- Create categories.
4. Labeling categories and determine which are relevant and their connection
- Label categories include adaptation, problem-solving, and seeking information.
- Describe connection
- Decide on the hierarchy available among the categories.
- Draw a figure in summarizing the results.
- Determine an essential category.
6. Write up the results
- Describe categories and their connection.
- Writer interpretation and discuss the results.
How do you analyze dissertation findings?
The dissertation finding chapter needs to provide a context for comprehending the results. The research problem should be repeated with the research goals stated. The above approach will enable the researcher to gain the reader’s attention toward the research problem. The first step entails finding, which results in specific, should be presented in the section. It is essential to perform all the results relevant to the study question, as this will help the researcher stay on board as to whether or not the hypothesis is supported.
How do you write a data analysis paragraph?
The data analysis paragraph should provide an illustration of how the data should be organized, the statistical tests applied, and how to obtain and evaluate the results. Some of the tips to consider include:
- Indicate whether the research is qualitative or quantitative.
- Avoid analyzing the results in the data analysis section.
- Ensure to include the full name of the statistical tests implemented.
- Mention the data transformations in case there is any, including the normalizing data.
- Provide the main research question and the method of analysis applied in answering the questions.
- Mention the software used to analyze and gather information.
- Provide a list of the data sources, including the online reports and electronic archives.
- Explain how the data had been summarized, and the measures were taken of variability used.
- What are the five chapters of the dissertation?
- Chapter 1 -Introduction: provides background to the study and clarifies problems, objectives, hypothesis/questions, significance, delimitation, and critical terminology of the study.
- Chapter 2 – Review of Relevant Literature: evaluates existing theory and empirical evidence relevant to the topic under study intending to clarify and advance a coherent conceptual and theoretical framework to ground the study, and at the same time, drawing insights and lessons from limitations and lacuna in previous work.
- Chapter 3 variously called Methodology or Materials & Methods: details the general approach to the research (research design), population and samples + sampling techniques, instrumentation used or Apparatus and materials, validity and reliability of the instrumentation, procedures for data collection and analysis, criteria for acceptance/rejection of the hypothesis.
- Chapter 4 – Results & Discussion: reports and analyses findings, confirming or rejecting the hypothesis, and anchoring results in theoretical framework or literature.
- Chapter 5 – Conclusions & Recommendations: draws inferences from the findings of the study, points out implications, making recombination for theory, practice and further research.
What is the popular dissertation referencing methods?
You should be consistent not only with appendix references but with other recommendations. For example, if you would refer to section 2 as “section 2”. Then you should probably see Appendix A as “appendix A” and figure 3.2 as “figure 3.2”. Another consistent choice would be “§2”, “§A,” and “fig. 3.2”.
The main text should also flow in such a manner that it presents a continuously advanced argument, indicated by the results of applying for a specific research methodology, for instance, statistical or textual. In case of any doubt, check with your supervisor and department. The researcher should state in the main footage or text that a specific material is in the appendix.
- Dissertation Data Analysis Tips
2024 Theses Doctoral
Three-dimensional magnetic fields: from coils to reconnection
Elder, Todd M.
This thesis is a work divided into two parts on aspects of three-dimensional (3D) magnetic fields: (I) magnetic reconnection treated from a strictly 3D viewpoint and (II) the design of coils for producing the 3D magnetic fields of optimized stellarators. In astrophysical settings, magnetic fields are generically 3D. 3D divergence-free fields have rich topological structures such as magnetic nulls and chaotic field line structures. Standard reconnection literature identifies magnetic nulls as locations of magnetic reconnection, and that intense currents will build up around them. This idea is explored with a key realization that by placing a vanishingly small sphere around the null, boundary conditions on field lines passing through the sphere may be sorted out. The main result here is (1) the dismissal of the notion that nulls are crucial places for magnetic reconnection and current accumulation, instead identifying separatrices of topological type on the boundaries of null-passing field lines to be crucial. Standard reconnection literature dismisses chaotic flows yet 3D fields generically have chaotic flows. An inherent property of chaotic flows is exponentiation. The main result here is (2) the identification of exponentiation as a natural mechanism for magnetic reconnection and that the associated current builds up linearly in time in contradiction to standard results requiring the formation of high-density current sheets. The magnetic fields of optimized stellarators are intricate, producing complex 3D magnetic surfaces. These fields are conventionally generated by non-planar electromagnetic coils, though these coils are costly to manufacture, slow device assembly, and hinder stellarator maintenance. Part II of this thesis explores methods of stellarator coil simplification that do not involve modular coils. All of this work uses current potentials, which are stream functions of the current sheets that produce magnetic surfaces. We begin with a result found using analytic methods on current potentials that (1) there may be an inherent limitation in the ability of modular coils to produce fields at a distance. This result is not surprising, though further analysis is necessary to work out some complexities of the result. Next, (2) a novel method to produce localized patches of current potential, representative of patches of current sheets, is developed and used to identify crucial locations of current placement for shaping magnetic surfaces. Most notably, these current sheet patches are able to produce much of the surface shaping while occupying a small fraction of the winding surface, resulting in good open-access stellarator coil configurations. Continuing the trend away from modular coils, (3) helical coils are optimized to support stellarator magnetic fields. This work agrees with related work on the optimization of helical coils, finding them unsuitable to the precise production of equilibria generated by modular coils. To improve this result, we use coil sets of mixed-type: helical coils with windowpane coils or permanent magnets, to mitigate field error left behind by the helical coils. Finally, (4) the development of a generalized method to cut modular, helical, and windowpane coils out of current potentials and to identify the associated coil currents is developed and used in coil optimization.
- Plasma (Ionized gases)
- Magnetic fields
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