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Dissertation Methodology – Structure, Example and Writing Guide

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Dissertation Methodology

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

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

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

Types of Dissertation Methodology

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

Experimental Research

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

Survey Research

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

Qualitative Research

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

Quantitative Research

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

Case Study Research

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

Mixed Methods Research

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

Action Research

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

Longitudinal Research

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

Ethnographic Research

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

Structure of Dissertation Methodology

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

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

How to Write Dissertation Methodology

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

1. Introduction

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

2. Approach

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

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

3. Research Design

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

4. Data Collection

Explain in detail how you collected your data.

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

5. Data Analysis

Describe how you analyzed your data.

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

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

7. Reliability and Validity

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

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

8. Limitations

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

9. Conclusion

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

Example of Dissertation Methodology

An Example of Dissertation Methodology is as follows:

Chapter 3: Methodology

• Introduction

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

Research Design

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

Data Collection Methods

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

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

Data Analysis Methods

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

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

Reliability and Validity

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

Ethical Considerations

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

Limitations

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

Where to Write Dissertation Methodology

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

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

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

Advantages of Dissertation Methodology

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

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

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• What Is a Research Methodology? | Steps & Tips

What Is a Research Methodology? | Steps & Tips

Published on 25 February 2019 by Shona McCombes . Revised on 10 October 2022.

Your research methodology discusses and explains the data collection and analysis methods you used in your research. A key part of your thesis, dissertation, or research paper, the methodology chapter explains what you did and how you did it, allowing readers to evaluate the reliability and validity of your research.

It should include:

• The type of research you conducted
• How you collected and analysed your data
• Any tools or materials you used in the research
• Why you chose these methods
• Your methodology section should generally be written in the past tense .
• Academic style guides in your field may provide detailed guidelines on what to include for different types of studies.
• Your citation style might provide guidelines for your methodology section (e.g., an APA Style methods section ).

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Table of contents

How to write a research methodology, why is a methods section important, step 1: explain your methodological approach, step 2: describe your data collection methods, step 3: describe your analysis method, step 4: evaluate and justify the methodological choices you made, tips for writing a strong methodology chapter, frequently asked questions about methodology.

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Your methods section is your opportunity to share how you conducted your research and why you chose the methods you chose. It’s also the place to show that your research was rigorously conducted and can be replicated .

It gives your research legitimacy and situates it within your field, and also gives your readers a place to refer to if they have any questions or critiques in other sections.

You can start by introducing your overall approach to your research. You have two options here.

Option 1: Start with your “what”

What research problem or question did you investigate?

• Aim to describe the characteristics of something?
• Explore an under-researched topic?
• Establish a causal relationship?

And what type of data did you need to achieve this aim?

• Quantitative data , qualitative data , or a mix of both?
• Primary data collected yourself, or secondary data collected by someone else?
• Experimental data gathered by controlling and manipulating variables, or descriptive data gathered via observations?

Option 2: Start with your “why”

Depending on your discipline, you can also start with a discussion of the rationale and assumptions underpinning your methodology. In other words, why did you choose these methods for your study?

• Why is this the best way to answer your research question?
• Is this a standard methodology in your field, or does it require justification?
• Were there any ethical considerations involved in your choices?
• What are the criteria for validity and reliability in this type of research ?

Once you have introduced your reader to your methodological approach, you should share full details about your data collection methods .

Quantitative methods

In order to be considered generalisable, you should describe quantitative research methods in enough detail for another researcher to replicate your study.

Here, explain how you operationalised your concepts and measured your variables. Discuss your sampling method or inclusion/exclusion criteria, as well as any tools, procedures, and materials you used to gather your data.

Surveys Describe where, when, and how the survey was conducted.

• How did you design the questionnaire?
• What form did your questions take (e.g., multiple choice, Likert scale )?
• Were your surveys conducted in-person or virtually?
• What sampling method did you use to select participants?
• What was your sample size and response rate?

Experiments Share full details of the tools, techniques, and procedures you used to conduct your experiment.

• How did you design the experiment ?
• How did you recruit participants?
• How did you manipulate and measure the variables ?
• What tools did you use?

Existing data Explain how you gathered and selected the material (such as datasets or archival data) that you used in your analysis.

• Where did you source the material?
• How was the data originally produced?
• What criteria did you use to select material (e.g., date range)?

The survey consisted of 5 multiple-choice questions and 10 questions measured on a 7-point Likert scale.

The goal was to collect survey responses from 350 customers visiting the fitness apparel company’s brick-and-mortar location in Boston on 4–8 July 2022, between 11:00 and 15:00.

Here, a customer was defined as a person who had purchased a product from the company on the day they took the survey. Participants were given 5 minutes to fill in the survey anonymously. In total, 408 customers responded, but not all surveys were fully completed. Due to this, 371 survey results were included in the analysis.

Qualitative methods

In qualitative research , methods are often more flexible and subjective. For this reason, it’s crucial to robustly explain the methodology choices you made.

Be sure to discuss the criteria you used to select your data, the context in which your research was conducted, and the role you played in collecting your data (e.g., were you an active participant, or a passive observer?)

Interviews or focus groups Describe where, when, and how the interviews were conducted.

• How did you find and select participants?
• How many participants took part?
• What form did the interviews take ( structured , semi-structured , or unstructured )?
• How long were the interviews?
• How were they recorded?

Participant observation Describe where, when, and how you conducted the observation or ethnography .

• What group or community did you observe? How long did you spend there?
• How did you gain access to this group? What role did you play in the community?
• How long did you spend conducting the research? Where was it located?
• How did you record your data (e.g., audiovisual recordings, note-taking)?

Existing data Explain how you selected case study materials for your analysis.

• What type of materials did you analyse?
• How did you select them?

In order to gain better insight into possibilities for future improvement of the fitness shop’s product range, semi-structured interviews were conducted with 8 returning customers.

Here, a returning customer was defined as someone who usually bought products at least twice a week from the store.

Surveys were used to select participants. Interviews were conducted in a small office next to the cash register and lasted approximately 20 minutes each. Answers were recorded by note-taking, and seven interviews were also filmed with consent. One interviewee preferred not to be filmed.

Mixed methods

Mixed methods research combines quantitative and qualitative approaches. If a standalone quantitative or qualitative study is insufficient to answer your research question, mixed methods may be a good fit for you.

Mixed methods are less common than standalone analyses, largely because they require a great deal of effort to pull off successfully. If you choose to pursue mixed methods, it’s especially important to robustly justify your methods here.

Next, you should indicate how you processed and analysed your data. Avoid going into too much detail: you should not start introducing or discussing any of your results at this stage.

In quantitative research , your analysis will be based on numbers. In your methods section, you can include:

• How you prepared the data before analysing it (e.g., checking for missing data , removing outliers , transforming variables)
• Which software you used (e.g., SPSS, Stata or R)
• Which statistical tests you used (e.g., two-tailed t test , simple linear regression )

In qualitative research, your analysis will be based on language, images, and observations (often involving some form of textual analysis ).

Specific methods might include:

• Content analysis : Categorising and discussing the meaning of words, phrases and sentences
• Thematic analysis : Coding and closely examining the data to identify broad themes and patterns
• Discourse analysis : Studying communication and meaning in relation to their social context

Mixed methods combine the above two research methods, integrating both qualitative and quantitative approaches into one coherent analytical process.

Above all, your methodology section should clearly make the case for why you chose the methods you did. This is especially true if you did not take the most standard approach to your topic. In this case, discuss why other methods were not suitable for your objectives, and show how this approach contributes new knowledge or understanding.

In any case, it should be overwhelmingly clear to your reader that you set yourself up for success in terms of your methodology’s design. Show how your methods should lead to results that are valid and reliable, while leaving the analysis of the meaning, importance, and relevance of your results for your discussion section .

• Quantitative: Lab-based experiments cannot always accurately simulate real-life situations and behaviours, but they are effective for testing causal relationships between variables .
• Qualitative: Unstructured interviews usually produce results that cannot be generalised beyond the sample group , but they provide a more in-depth understanding of participants’ perceptions, motivations, and emotions.
• Mixed methods: Despite issues systematically comparing differing types of data, a solely quantitative study would not sufficiently incorporate the lived experience of each participant, while a solely qualitative study would be insufficiently generalisable.

Remember that your aim is not just to describe your methods, but to show how and why you applied them. Again, it’s critical to demonstrate that your research was rigorously conducted and can be replicated.

1. Focus on your objectives and research questions

The methodology section should clearly show why your methods suit your objectives  and convince the reader that you chose the best possible approach to answering your problem statement and research questions .

2. Cite relevant sources

Your methodology can be strengthened by referencing existing research in your field. This can help you to:

• Show that you followed established practice for your type of research
• Discuss how you decided on your approach by evaluating existing research
• Present a novel methodological approach to address a gap in the literature

3. Write for your audience

Consider how much information you need to give, and avoid getting too lengthy. If you are using methods that are standard for your discipline, you probably don’t need to give a lot of background or justification.

Regardless, your methodology should be a clear, well-structured text that makes an argument for your approach, not just a list of technical details and procedures.

Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. interviews, experiments , surveys , statistical tests ).

In a dissertation or scientific paper, the methodology chapter or methods section comes after the introduction and before the results , discussion and conclusion .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

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

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

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How To Write The Methodology Chapter

The what, why & how explained simply (with examples).

By: Jenna Crossley (PhD) | Reviewed By: Dr. Eunice Rautenbach | September 2021 (Updated April 2023)

So, you’ve pinned down your research topic and undertaken a review of the literature – now it’s time to write up the methodology section of your dissertation, thesis or research paper . But what exactly is the methodology chapter all about – and how do you go about writing one? In this post, we’ll unpack the topic, step by step .

Overview: The Methodology Chapter

• The purpose  of the methodology chapter
• Why you need to craft this chapter (really) well
• How to write and structure the chapter
• Methodology chapter example
• Essential takeaways

What (exactly) is the methodology chapter?

The methodology chapter is where you outline the philosophical underpinnings of your research and outline the specific methodological choices you’ve made. The point of the methodology chapter is to tell the reader exactly how you designed your study and, just as importantly, why you did it this way.

Importantly, this chapter should comprehensively describe and justify all the methodological choices you made in your study. For example, the approach you took to your research (i.e., qualitative, quantitative or mixed), who  you collected data from (i.e., your sampling strategy), how you collected your data and, of course, how you analysed it. If that sounds a little intimidating, don’t worry – we’ll explain all these methodological choices in this post .

Why is the methodology chapter important?

The methodology chapter plays two important roles in your dissertation or thesis:

Firstly, it demonstrates your understanding of research theory, which is what earns you marks. A flawed research design or methodology would mean flawed results. So, this chapter is vital as it allows you to show the marker that you know what you’re doing and that your results are credible .

Secondly, the methodology chapter is what helps to make your study replicable. In other words, it allows other researchers to undertake your study using the same methodological approach, and compare their findings to yours. This is very important within academic research, as each study builds on previous studies.

The methodology chapter is also important in that it allows you to identify and discuss any methodological issues or problems you encountered (i.e., research limitations ), and to explain how you mitigated the impacts of these. Every research project has its limitations , so it’s important to acknowledge these openly and highlight your study’s value despite its limitations . Doing so demonstrates your understanding of research design, which will earn you marks. We’ll discuss limitations in a bit more detail later in this post, so stay tuned!

Need a helping hand?

How to write up the methodology chapter

First off, it’s worth noting that the exact structure and contents of the methodology chapter will vary depending on the field of research (e.g., humanities, chemistry or engineering) as well as the university . So, be sure to always check the guidelines provided by your institution for clarity and, if possible, review past dissertations from your university. Here we’re going to discuss a generic structure for a methodology chapter typically found in the sciences.

Before you start writing, it’s always a good idea to draw up a rough outline to guide your writing. Don’t just start writing without knowing what you’ll discuss where. If you do, you’ll likely end up with a disjointed, ill-flowing narrative . You’ll then waste a lot of time rewriting in an attempt to try to stitch all the pieces together. Do yourself a favour and start with the end in mind .

Section 1 – Introduction

As with all chapters in your dissertation or thesis, the methodology chapter should have a brief introduction. In this section, you should remind your readers what the focus of your study is, especially the research aims . As we’ve discussed many times on the blog, your methodology needs to align with your research aims, objectives and research questions. Therefore, it’s useful to frontload this component to remind the reader (and yourself!) what you’re trying to achieve.

In this section, you can also briefly mention how you’ll structure the chapter. This will help orient the reader and provide a bit of a roadmap so that they know what to expect. You don’t need a lot of detail here – just a brief outline will do.

Section 2 – The Methodology

The next section of your chapter is where you’ll present the actual methodology. In this section, you need to detail and justify the key methodological choices you’ve made in a logical, intuitive fashion. Importantly, this is the heart of your methodology chapter, so you need to get specific – don’t hold back on the details here. This is not one of those “less is more” situations.

Let’s take a look at the most common components you’ll likely need to cover. 

Methodological Choice #1 – Research Philosophy

Research philosophy refers to the underlying beliefs (i.e., the worldview) regarding how data about a phenomenon should be gathered , analysed and used . The research philosophy will serve as the core of your study and underpin all of the other research design choices, so it’s critically important that you understand which philosophy you’ll adopt and why you made that choice. If you’re not clear on this, take the time to get clarity before you make any further methodological choices.

While several research philosophies exist, two commonly adopted ones are positivism and interpretivism . These two sit roughly on opposite sides of the research philosophy spectrum.

Positivism states that the researcher can observe reality objectively and that there is only one reality, which exists independently of the observer. As a consequence, it is quite commonly the underlying research philosophy in quantitative studies and is oftentimes the assumed philosophy in the physical sciences.

Contrasted with this, interpretivism , which is often the underlying research philosophy in qualitative studies, assumes that the researcher performs a role in observing the world around them and that reality is unique to each observer . In other words, reality is observed subjectively .

These are just two philosophies (there are many more), but they demonstrate significantly different approaches to research and have a significant impact on all the methodological choices. Therefore, it’s vital that you clearly outline and justify your research philosophy at the beginning of your methodology chapter, as it sets the scene for everything that follows.

Methodological Choice #2 – Research Type

The next thing you would typically discuss in your methodology section is the research type. The starting point for this is to indicate whether the research you conducted is inductive or deductive .

Inductive research takes a bottom-up approach , where the researcher begins with specific observations or data and then draws general conclusions or theories from those observations. Therefore these studies tend to be exploratory in terms of approach.

Conversely , d eductive research takes a top-down approach , where the researcher starts with a theory or hypothesis and then tests it using specific observations or data. Therefore these studies tend to be confirmatory in approach.

Related to this, you’ll need to indicate whether your study adopts a qualitative, quantitative or mixed  approach. As we’ve mentioned, there’s a strong link between this choice and your research philosophy, so make sure that your choices are tightly aligned . When you write this section up, remember to clearly justify your choices, as they form the foundation of your study.

Methodological Choice #3 – Research Strategy

Next, you’ll need to discuss your research strategy (also referred to as a research design ). This methodological choice refers to the broader strategy in terms of how you’ll conduct your research, based on the aims of your study.

Several research strategies exist, including experimental , case studies , ethnography , grounded theory, action research , and phenomenology . Let’s take a look at two of these, experimental and ethnographic, to see how they contrast.

Experimental research makes use of the scientific method , where one group is the control group (in which no variables are manipulated ) and another is the experimental group (in which a specific variable is manipulated). This type of research is undertaken under strict conditions in a controlled, artificial environment (e.g., a laboratory). By having firm control over the environment, experimental research typically allows the researcher to establish causation between variables. Therefore, it can be a good choice if you have research aims that involve identifying causal relationships.

Ethnographic research , on the other hand, involves observing and capturing the experiences and perceptions of participants in their natural environment (for example, at home or in the office). In other words, in an uncontrolled environment.  Naturally, this means that this research strategy would be far less suitable if your research aims involve identifying causation, but it would be very valuable if you’re looking to explore and examine a group culture, for example.

As you can see, the right research strategy will depend largely on your research aims and research questions – in other words, what you’re trying to figure out. Therefore, as with every other methodological choice, it’s essential to justify why you chose the research strategy you did.

Methodological Choice #4 – Time Horizon

The next thing you’ll need to detail in your methodology chapter is the time horizon. There are two options here: cross-sectional and longitudinal . In other words, whether the data for your study were all collected at one point in time (cross-sectional) or at multiple points in time (longitudinal).

The choice you make here depends again on your research aims, objectives and research questions. If, for example, you aim to assess how a specific group of people’s perspectives regarding a topic change over time , you’d likely adopt a longitudinal time horizon.

Another important factor to consider is simply whether you have the time necessary to adopt a longitudinal approach (which could involve collecting data over multiple months or even years). Oftentimes, the time pressures of your degree program will force your hand into adopting a cross-sectional time horizon, so keep this in mind.

Methodological Choice #5 – Sampling Strategy

Next, you’ll need to discuss your sampling strategy . There are two main categories of sampling, probability and non-probability sampling.

Probability sampling involves a random (and therefore representative) selection of participants from a population, whereas non-probability sampling entails selecting participants in a non-random  (and therefore non-representative) manner. For example, selecting participants based on ease of access (this is called a convenience sample).

The right sampling approach depends largely on what you’re trying to achieve in your study. Specifically, whether you trying to develop findings that are generalisable to a population or not. Practicalities and resource constraints also play a large role here, as it can oftentimes be challenging to gain access to a truly random sample. In the video below, we explore some of the most common sampling strategies.

Methodological Choice #6 – Data Collection Method

Next up, you’ll need to explain how you’ll go about collecting the necessary data for your study. Your data collection method (or methods) will depend on the type of data that you plan to collect – in other words, qualitative or quantitative data.

Typically, quantitative research relies on surveys , data generated by lab equipment, analytics software or existing datasets. Qualitative research, on the other hand, often makes use of collection methods such as interviews , focus groups , participant observations, and ethnography.

So, as you can see, there is a tight link between this section and the design choices you outlined in earlier sections. Strong alignment between these sections, as well as your research aims and questions is therefore very important.

Methodological Choice #7 – Data Analysis Methods/Techniques

The final major methodological choice that you need to address is that of analysis techniques . In other words, how you’ll go about analysing your date once you’ve collected it. Here it’s important to be very specific about your analysis methods and/or techniques – don’t leave any room for interpretation. Also, as with all choices in this chapter, you need to justify each choice you make.

What exactly you discuss here will depend largely on the type of study you’re conducting (i.e., qualitative, quantitative, or mixed methods). For qualitative studies, common analysis methods include content analysis , thematic analysis and discourse analysis . In the video below, we explain each of these in plain language.

For quantitative studies, you’ll almost always make use of descriptive statistics , and in many cases, you’ll also use inferential statistical techniques (e.g., correlation and regression analysis). In the video below, we unpack some of the core concepts involved in descriptive and inferential statistics.

In this section of your methodology chapter, it’s also important to discuss how you prepared your data for analysis, and what software you used (if any). For example, quantitative data will often require some initial preparation such as removing duplicates or incomplete responses . Similarly, qualitative data will often require transcription and perhaps even translation. As always, remember to state both what you did and why you did it.

Section 3 – The Methodological Limitations

With the key methodological choices outlined and justified, the next step is to discuss the limitations of your design. No research methodology is perfect – there will always be trade-offs between the “ideal” methodology and what’s practical and viable, given your constraints. Therefore, this section of your methodology chapter is where you’ll discuss the trade-offs you had to make, and why these were justified given the context.

Methodological limitations can vary greatly from study to study, ranging from common issues such as time and budget constraints to issues of sample or selection bias . For example, you may find that you didn’t manage to draw in enough respondents to achieve the desired sample size (and therefore, statistically significant results), or your sample may be skewed heavily towards a certain demographic, thereby negatively impacting representativeness .

In this section, it’s important to be critical of the shortcomings of your study. There’s no use trying to hide them (your marker will be aware of them regardless). By being critical, you’ll demonstrate to your marker that you have a strong understanding of research theory, so don’t be shy here. At the same time, don’t beat your study to death . State the limitations, why these were justified, how you mitigated their impacts to the best degree possible, and how your study still provides value despite these limitations .

Section 4 – Concluding Summary

Finally, it’s time to wrap up the methodology chapter with a brief concluding summary. In this section, you’ll want to concisely summarise what you’ve presented in the chapter. Here, it can be a good idea to use a figure to summarise the key decisions, especially if your university recommends using a specific model (for example, Saunders’ Research Onion ).

Importantly, this section needs to be brief – a paragraph or two maximum (it’s a summary, after all). Also, make sure that when you write up your concluding summary, you include only what you’ve already discussed in your chapter; don’t add any new information.

Methodology Chapter Example

In the video below, we walk you through an example of a high-quality research methodology chapter from a dissertation. We also unpack our free methodology chapter template so that you can see how best to structure your chapter.

Wrapping Up

And there you have it – the methodology chapter in a nutshell. As we’ve mentioned, the exact contents and structure of this chapter can vary between universities , so be sure to check in with your institution before you start writing. If possible, try to find dissertations or theses from former students of your specific degree program – this will give you a strong indication of the expectations and norms when it comes to the methodology chapter (and all the other chapters!).

Also, remember the golden rule of the methodology chapter – justify every choice ! Make sure that you clearly explain the “why” for every “what”, and reference credible methodology textbooks or academic sources to back up your justifications.

If you need a helping hand with your research methodology (or any other component of your research), be sure to check out our private coaching service , where we hold your hand through every step of the research journey. Until next time, good luck!

Psst... there’s more!

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

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Writing the Dissertation - Guides for Success: The Methodology

• Writing the Dissertation Homepage
• Overview and Planning
• The Literature Review
• The Methodology
• The Results and Discussion
• The Conclusion
• The Abstract
• Getting Started
• What to Avoid

Overview of writing the methodology

The methodology chapter precisely outlines the research method(s) employed in your dissertation and considers any relevant decisions you made, and challenges faced, when conducting your research. Getting this right is crucial because it lays the foundation for what’s to come: your results and discussion.

Disciplinary differences

Please note: this guide is not specific to any one discipline. The methodology can vary depending on the nature of the research and the expectations of the school or department. Please adapt the following advice to meet the demands of your dissertation and the expectations of your school or department. Consult your supervisor for further guidance; you can also check out our  Writing Across Subjects guide .

Guide contents

As part of the Writing the Dissertation series, this guide covers the most common conventions found in a methodology chapter, giving you the necessary knowledge, tips and guidance needed to impress your markers!  The sections are organised as follows:

• Getting Started  - Defines the methodology and its core characteristics.
• Structure  - Provides a detailed walk-through of common subsections or components of the methodology.
• What to Avoid  - Covers a few frequent mistakes you'll want to...avoid!
• FAQs  - Guidance on first- vs. third-person, secondary literature and more.
• Checklist  - Includes a summary of key points and a self-evaluation checklist.

Training and tools

• The Academic Skills team has recorded a Writing the Dissertation workshop series to help you with each section of a standard dissertation, including a video on writing the method/methodology .
• For more on methods and methodologies, you can check out USC's methodology research guide  and Huddersfield's guide to writing the methodology of an undergraduate dissertation .
• The dissertation planner tool can help you think through the timeline for planning, research, drafting and editing.
• iSolutions offers training and a Word template to help you digitally format and structure your dissertation.

What is the methodology?

The methodology of a dissertation is like constructing a house of cards. Having strong and stable foundations for your research relies on your ability to make informed and rational choices about the design of your study. Everything from this point on – your results and discussion –  rests on these decisions, like the bottom layer of a house of cards.

The methodology is where you explicitly state, in relevant detail, how you conduced your study in direct response to your research question(s) and/or hypotheses. You should work through the linear process of devising your study to implementing it, covering the important choices you made and any potential obstacles you faced along the way.

Methods or methodology?

Some disciplines refer to this chapter as the research methods , whilst others call it the methodology . The two are often used interchangeably, but they are slightly different. The methods chapter outlines the techniques used to conduct the research and the specific steps taken throughout the research process. The methodology also outlines how the research was conducted, but is particularly interested in the philosophical underpinning that shapes the research process. As indicated by the suffix, -ology , meaning the study of something, the methodology is like the study of research, as opposed to simply stating how the research was conducted.

This guide focuses on the methodology, as opposed to the methods, although the content and guidance can be tailored to a methods chapter. Every dissertation is different and every methodology has its own nuances, so ensure you adapt the content here to your research and always consult your supervisor for more detailed guidance.

What are my markers looking for?

Your markers are looking   for your understanding of the complex process behind original (see definition) research. They are assessing your ability to...

• Demonstrate   an understanding of the impact that methodological choices can have on the reliability and validity of your findings, meaning you should engage with ‘why’ you did that, as opposed to simply ‘what’ you did.
• Make   informed methodological choices that clearly relate to your research question(s).

But what does it mean to engage in 'original' research? Originality doesn’t strictly mean you should be inventing something entirely new. Originality comes in many forms, from updating the application of a theory, to adapting a previous experiment for new purposes – it’s about making a worthwhile contribution.

Structuring your methodology

The methodology chapter should outline the research process undertaken, from selecting the method to articulating the tool or approach adopted to analyse your results. Because you are outlining this process, it's important that you structure your methodology in a linear way, showing how certain decisions have impacted on subsequent choices.

Scroll to continue reading, or click a link below to jump immediately to that section:

The 'research onion'

To ensure you write your methodology in a linear way, it can be useful to think of the methodology in terms of layers, as shown in the figure below.

Figure: 'Research onion' from Saunders et al. (2007).

You don't need to precisely follow these exact layers as some won't be relevant to your research. However, the layered 'out to in' structure developed by Saunders et al. (2007) is appropriate for any methodology chapter because it guides your reader through the process in a linear fashion, demonstrating how certain decisions impacted on others. For example, you need to state whether your research is qualitative, quantitative or mixed before articulating your precise research method. Likewise, you need to explain how you collected your data before you inform the reader of how you subsequently analysed that data.

Using this linear approach from 'outer' layer to 'inner' layer, the next sections will take you through the most common layers used to structure a methodology chapter.

Introduction and research outline

Like any chapter, you should open your methodology with an introduction. It's good to start by briefly restating the research problem, or gap, that you're addressing, along with your research question(s) and/or hypotheses. Following this, it's common to provide a very condensed statement that outlines the most important elements of your research design. Here's a short example:

This study adopted qualitative research through a series of semi-structured interviews with seven experienced industry professionals.

Like any other introduction, you can then provide a brief statement outlining what the chapter is about and how it's structured (e.g., an essay map ).

Restating the research problem (or gap) and your research question(s) and/or hypotheses creates a natural transition from your previous review of the literature - which helped you to identify the gap or problem - to how you are now going to address such a problem. Your markers are also going to assess the relevance and suitability of your method and methodological choices against your research question(s), so it's good to 'frame' the entire chapter around the research question(s) by bringing them to the fore.

Research philosophy

A research philosophy is an underlying belief that shapes the way research is conducted. For this reason, as featured in the 'research onion' above, the philosophy should be the outermost layer - the first methodological issue you deal with following the introduction and research outline - because every subsequent choice, from the method employed to the way you analyse data, is directly influenced by your philosophical stance.

You can say something about other philosophies, but it's best to directly relate this to your research and the philosophy you have selected - why the other philosophy isn't appropriate for you to adopt, for instance. Otherwise, explain to your reader the philosophy you have selected (using secondary literature), its underlying principles, and why this philosophy, therefore, is particularly relevant to your research.

The research philosophy is sometimes featured in a methodology chapter, but not always. It depends on the conventions within your school or discipline , so only include this if it's expected.

The reason for outlining the research philosophy is to show your understanding of the role that your chosen philosophy plays in shaping the design and approach of your research study. The philosophy you adopt also indicates your worldview (in the context of this research), which is an important way of highlighting the role you, the researcher, play in shaping new knowledge.

Research method

This is where you state whether you're doing qualitative, quantitative or mixed-methods research before outlining the exact instrument or strategy (see definition) adopted for research (interviews, case study, etc.). It's also important that you explain why you have chosen that particular method and strategy. You can also explain why you're not adopting an alternate form of research, or why you haven't used a particular instrument, but keep this brief and use it to reinforce why you have chosen your method and strategy.

Your research method, more than anything else, is going to directly influence how effectively you answer your research question(s). For that reason, it's crucial that you emphasise the suitability of your chosen method and instrument for the purposes of your research.                       

Data collection

The data collection part of your methodology explain the process of how you accessed and collected your data. Using an interview as a qualitative example, this might include the criteria for selecting participants, how you recruited the participants and how and where you conducted the interviews. There is often some overlap with data collection and research method, so don't worry about this. Just make sure you get the essential information across to your reader.

The details of how you accessed and collected your data are important for replicability purposes - the ability for someone to adopt the same approach and repeat the study. It's also important to include this information for reliability and consistency purposes (see  validity and reliability  on the next tab of this guide for more).

Data analysis

After describing how you collected the data, you need to identify your chosen method of data analysis. Inevitably, this will vary depending on whether your research is qualitative or quantitative (see note below).

Qualitative research tends to be narrative-based where forms of ‘coding’ are employed to categorise and group the data into meaningful themes and patterns (Bui, 2014). Quantitative deals with numerical data meaning some form of statistical approach is taken to measure the results against the research question(s).

Tell your reader which data analysis software (such as SPSS or Atlast.ti) or method you’ve used and why, using relevant literature. Again, you can mention other data analysis tools that you haven’t used, but keep this brief and relate it to your discussion of your chosen approach. This isn’t to be confused with the results and discussion chapters where you actually state and then analyse your results. This is simply a discussion of the approach taken, how you applied this approach to your data and why you opted for this method of data analysis.

Detail of how you analysed your data helps to contextualise your results and discussion chapters. This is also a validity issue (see next tab of guide), as you need to ensure that your chosen method for data analysis helps you to answer your research question(s) and/or respond to your hypotheses. To use an example from Bui (2014: 155), 'if one of the research questions asks whether the participants changed their behaviour before and after the study, then one of the procedures for data analysis needs to be a comparison of the pre- and postdata'.

Validity and reliability

Validity simply refers to whether the research method(s) and instrument(s) applied are directly suited to meet the purposes of your research – whether they help you to answer your research question(s), or allow you to formulate a response to your hypotheses.

Validity can be separated into two forms: internal and external. The difference between the two is defined by what exists inside the study (internal) and what exists outside the study (external).

• Internal validity is the extent to which ‘the results obtained can be attributed to the manipulation of the independent variable' (Salkind, 2011: 147).
• External validity refers to the application of your study’s findings outside the setting of your study. This is known as generalisability , meaning to what extent are the results applicable to a wider context or population.

Reliability

Reliability refers to the consistency with which you designed and implemented your research instrument(s). The idea behind this is to ensure that someone else could replicate your study and, by applying the instrument in the exact same way, would achieve the same results. This is crucial to quantitative and scientific based research, but isn’t strictly the case with qualitative research given the subjective nature of the data.

With qualitative data, it’s important to emphasise that data was collected in a consistent way to avoid any distortions. For example, let’s say you’ve circulated a questionnaire to participants. You would want to ensure that every participant receives the exact same questionnaire with precisely the same questions and wording, unless different questionnaires are required for different members of the sample for the purposes of the research.

Ethical considerations

Any research involving human participants needs to consider ethical factors. In response, you need to show your markers that you have implemented the necessary measures to cover the relevant ethical issues. These are some of the factors that are typically included:

• How did you gain the consent of participants, and how did you formally record this consent?
• What measures did you take to ensure participants had enough understanding of their role to make an informed decision, including the right to withdraw at any stage?
• What measures did you take to maintain the confidentiality of participants during the research and, potentially, for the write-up?
• What measures did you take to store the raw data and protect it from external access and use prior to the write-up?

These are only a few examples of the ethical factors you need to write about in your methodology. Depending on the nature of your research, ethical considerations might form a significant part of your methodology chapter, or may only constitute a few sentences. Either way, it’s imperative that you show your markers that you’ve considered the relevant ethical implications of your research.

Limitations

Don’t make the mistake of ignoring the limitations of your study (see the next tab, 'What to Avoid', for more on this) – it’s a common part of research and should be confronted. Limitations of research can be diverse, but tend to be logistical issues relating to time, scope and access . Whilst accepting that your study has certain limitations, the key is to put a positive spin on it, like the example below:

Despite having a limited sample size compared to other similar studies, the number of participants is enough to provide sufficient data, whilst the in-depth nature of the interviews facilitates detailed responses from participants.

• Bui, Y. N. (2014) How to Write a Master’s Thesis. 2dn Edtn. Thousand Oaks, CA: Sage.
• Guba, E. G. and Lincoln, Y. S. (1994) ‘Competing paradigms in qualitative research’, in Denzin, N. K. and Lincoln, N. S. (eds.) Handbook of Qualitative Research. Thousand Oaks, CA: Sage, pp. 105-117.
• Salkind, N. J. (2011) ‘Internal and external validity’, in Moutinho, L. and Hutchenson, G. D. (eds.) The SAGE Dictionary of Quantitative Management Research . Thousand Oaks, CA: Sage, pp. 147-149.
• Saunders, M., Lewis, P. and Thornhill, A. (2007) Research Methods for Business Students . 4th Edtn. Harlow: Pearson.

What to avoid

This portion of the guide will cover some common missteps you should try to avoid in writing your methodology.

Ignoring limitations

It might seem instinctive to hide any flaws or limitations with your research to protect yourself from criticism. However, you need to highlight any problems you encountered during the research phase, or any limitations with your approach. Your markers are expecting you to engage with these limitations and highlight the kind of impact they may have had on your research.

Just be careful that you don’t overstress these limitations. Doing so could undermine the reliability and validity of your results, and your credibility as a researcher.

Literature review of methods

Don’t mistake your methodology chapter as a detailed review of methods employed in other studies. This level of detail should, where relevant, be incorporated in the literature review chapter, instead (see our Writing the Literature Review guide ). Any reference to methodological choices made by other researchers should come into your methodology chapter, but only in support of the decisions you made.

Unnecessary detail

It’s important to be thorough in a methodology chapter. However, don’t include unnecessary levels of detail. You should provide enough detail that allows other researchers to replicate or adapt your study, but don’t bore your reader with obvious or extraneous detail.

Any materials or content that you think is worth including, but not essential in the chapter, could be included in an appendix (see definition). These don’t count towards your word count (unless otherwise stated), and they can provide further detail and context for your reader. For instance, it’s quite common to include a copy of a questionnaire in an appendix, or a list of interview questions.

Q: Should the methodology be in the past or present tense?

A: The past tense. The study has already been conducted and the methodological decisions have been implemented, meaning the chapter should be written in the past tense. For example...

Data was collected over the course of four weeks.

I informed participants of their right to withdraw at any time.

The surveys included ten questions about job satisfaction and ten questions about familial life (see Appendix).

Q: Should the methodology include secondary literature?

A: Yes, where relevant. Unlike the literature review, the methodology is driven by what you did rather than what other people have done. However, you should still draw on secondary sources, when necessary, to support your methodological decisions.

Q: Do you still need to write a methodology for secondary research?

A: Yes, although it might not form a chapter, as such. Including some detail on how you approached the research phase is always a crucial part of a dissertation, whether primary or secondary. However, depending on the nature of your research, you may not have to provide the same level of detail as you would with a primary-based study.

For example, if you’re analysing two particular pieces of literature, then you probably need to clarify how you approached the analysis process, how you use the texts (whether you focus on particular passages, for example) and perhaps why these texts are scrutinised, as opposed to others from the relevant literary canon.

In such cases, the methodology may not be a chapter, but might constitute a small part of the introduction. Consult your supervisor for further guidance.

Q: Should the methodology be in the first-person or third?

A: It’s important to be consistent , so you should use whatever you’ve been using throughout your dissertation. Third-person is more commonly accepted, but certain disciplines are happy with the use of first-person. Just remember that the first-person pronoun can be a distracting, but powerful device, so use it sparingly. Consult your supervisor for further guidance.

It’s important to remember that all research is different and, as such, the methodology chapter is likely to be very different from dissertation to dissertation. Whilst this guide has covered the most common and essential layers featured in a methodology, your methodology might be very different in terms of what you focus on, the depth of focus and the wording used.

What’s important to remember, however, is that every methodology chapter needs to be structured in a linear, layered way that guides the reader through the methodological process in sequential order. Through this, your marker can see how certain decisions have impacted on others, showing your understanding of the research process.

Here’s a final checklist for writing your methodology. Remember that not all of these points will be relevant for your methodology, so make sure you cover whatever’s appropriate for your dissertation. The asterisk (*) indicates any content that might not be relevant for your dissertation. You can download a copy of the checklist to save and edit via the Word document, below.

• Methodology self-evaluation checklist

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• Next: The Results and Discussion >>
• Last Updated: Apr 19, 2024 12:38 PM
• URL: https://library.soton.ac.uk/writing_the_dissertation

• How it works

Writing a Methodology for your Dissertation | Complete Guide & Steps

What is a methodology.

The methodology is perhaps the most challenging and laborious part of the dissertation . Essentially, the methodology helps in understanding the broad, philosophical approach behind the methods of research you chose to employ in your study. The research methodology elaborates on the ‘how’ part of your research.

This means that your methodology chapter should clearly state whether you chose to use quantitative or qualitative data collection techniques or a mix of both.

Your research methodology should explain the following:

• What was the purpose of your research?
• What type of research method was used?
• What were the data-collecting methods?
• How did you analyse the data?
• What kind of resources were used in your research?
• Why did you choose these methods?

You will be required to provide justifications as to why you preferred a certain method over the others. If you are trying to figure out exactly how to write methodology or the structure of a methodology for a dissertation, this article will point you in the right direction.

Students must be sure of why they chose a certain research method over another. “I figured out” or “In my opinion” statements will not be an acceptable justification. So, you will need to come up with concrete academic reasons for your selection of research methods.

What are the Standard Contents of a Research Methodology?

The methodology generally acts as a guideline or plan for exactly how you intend to carry out your research. This is especially true for students who must submit their methodology chapter before carrying out the research.

Your methodology should link back to the literature review and clearly state why you chose certain data collection and analysis methods for your research/dissertation project.

The methodology chapter consists of the following:

• Research Design
• Philosophical Approach
• Data Collection Methods
• Research Limitations
• Ethical Considerations (If Any)
• Data Analysis Methods

For those who are submitting their dissertation as a single paper, their methodology should also touch on any modifications they had to make as their work progressed.

However, it is essential to provide academic justifications for all choices made by the researcher.

How to Choose your Dissertation Methodology and Research Design?

The theme of your research methodology chapter should be related to your literature review and research question (s).

You can visit your college or university library to find textbooks and articles that provide information about the commonly employed research methods .

An intensive reading of such books can help you devise your research philosophy and choose the appropriate methods. Any limitations or weaknesses of your chosen research approach should also be explained, as well as the strategies to overcome them.

To research well, you should read well! Read as many research articles (from reputed journals) as you can. Seeing how other researchers use methods in their studies and why will help you justify, in the long run, your own research method(s).

Regardless of the chosen research approach, you will find researchers who either support it or don’t. Use the arguments for and against articulated in the literature to clarify why you decided to choose the selected research design and why the research limitations are irrelevant to your research.

How to Structure your Dissertation Methodology?

The typical structure of the methodology chapter is as follows:

• Research Design And Strategy
• Methods Of Data Collection And Data Analysis
• Ethical Considerations, Reliability , Limitations And Generalisability

In research jargon, generalisability is termed external validity . It means how generalisable your research findings are to other contexts, places, times, people, etc. External validity is expected to be significantly high, especially in quantitative studies.

According to USC-Research Guides (2017) , a research design’s primary function is to enable the researcher to answer the research questions through evidence effectively. Generally, this section will shed light on how you collected your data.

The researcher will have to justify their choice of data collection methods, such as the one that was reviewed, the use of data tools (interviews, phone surveys, questionnaires, observation, online surveys , etc.) and the like.

Moreover, data sampling choice should also be clearly explained with a focus on how you chose the ethnicity, group, profession and age of the participants.

• What type of questions do you intend to ask the respondents?
• How will they help to answer your research questions ?
• How will they help to test the hypothesis of the dissertation?

It is recommended to prepare these questions at the start of your research. You should develop your research problem and questions. This approach can allow the room to change or modify research questions if your data collection methods do not give the desired results.

It’s a good practice to keep referring to your research questions whilst planning or writing the research design section. This will help your reader recall what the research is about; why you have done what you did. Even though this technique is recommended to be applied at the start of every section within a dissertation, it’s especially beneficial in the methodology section.

In short, you will need to make sure that the data you are going to collect relates to the topic you are exploring. The complexity and length of the research design section will vary depending on your academic subject and the scope of your research, but a well-written research design will have the following characteristics:

• It sheds light on alternative research design options and justifies why your chosen design is the best to address the research problem.
• Clearly specifies the research questions that the research aims to address or the hypothesis to validate.
• Explain how the collected data will help address the research problem and discusses your research methodology to collect the data.

Philosophical Approach Behind Writing a Methodology

This will discuss your chosen philosophy to strengthen your research and the research model. Commonly employed philosophies in academia are

• Interpretivism,
• Positivism/Post-Positivism
• Constructivism

There are several other research philosophies that you could adopt.

The choice of philosophy will depend on many factors, including your academic subject and the type and complexity of the research study. Regardless of which philosophy is used, you will be required to make different assumptions about the world.

Once you have chosen your research philosophy, the next step will describe your research context to answer all the questions, including when, where, why, how and what of your research.

Essentially, as a researcher, you will be required to decide whether you will be using a qualitative method, a quantitative method or a mix of both.

Did you know?

Using both qualitative and quantitative methods leads to the use of a mixed-methods approach. This approach also goes by another seldom-used name: eclectic approach.

The process of data collection is different for each method. Typically, you would want to decide whether you will adopt the positivist approach, defining your hypothesis and testing it against reality.

If this is the case, you will be required to take the quantitative approach, collecting numerical data at a large scale (from 30 or more respondents) and testing your hypotheses with this data.

Collecting data from at least 30 respondents/participants ensures reliable statistical analysis . This is especially true for quantitative studies. If the data contains less than 30 responses, it won’t be enough to carry out reliable statistical analyses on such data.

The other option for you would be to base your research on a qualitative approach, which will point you in a direction where you will be investigating broader areas by identifying people’s emotions and perceptions of a subject.

With a qualitative approach, you will have to collect responses from respondents and look at them in all their richness to develop theories about the field you are exploring.

Finally, you can also use a mix of qualitative and quantitative methods (which is becoming increasingly popular among researchers these days). This method is beneficial if you are interested in putting quantitative data into a real-world context or reflecting different perspectives on a subject.

Research philosophy in the ‘research onion.’

Methods of Data Collection and Data Analysis

This section will require you to clearly specify how you gathered the data and briefly discuss the tools you used to analyse it. For example, you may choose to conduct surveys and/or interviews as part of the data collection process.

Similarly, if you used software such as Excel or SPSS to process the data , you will have to justify your software choice. In this section of your methodology chapter , you will also have to explain how you arrived at your findings and how reliable they are.

It is important to note that your readers or supervisor would want to see a correlation between your findings and the hypothesis/research questions you based your study on at the very beginning.

Your supervisor or dissertation research assistant can play a key role in helping you write the methodology chapter according to established research standards. So, keep your supervisor in the loop to get their contributions and recommendations throughout the process.

In this section, you should briefly describe the methods you’ve used to analyse the data you’ve collected.

Qualitative Methods

The qualitative method includes analysing language, images, audio, videos, or any textual data (textual analysis). The following types of methods are used in textual analysis .

Discourse analysis:

Discourse analysis is an essential aspect of studying a language and its uses in day-to-day life.

Content analysis:

It is a method of studying and retrieving meaningful information from documents Thematic analysis:

It’s a method of identifying patterns of themes in the collected information, such as face-to-face interviews, texts, and transcripts.

Example: After collecting the data, it was checked thoroughly to find the missing information. The interviews were transcribed, and textual analysis was conducted. The repetitions of the text, types of colours displayed, and the tone of the speakers was measured.

Quantitative Methods

Quantitative data analysis is used for analysing numerical data. Include the following points:

• The methods of preparing data before analysing it.
• Which statistical test you have used? (one-ended test, two-ended test)
• The type of software you’ve used.

Ethical Considerations, Reliability and Limitations of a Dissertation Methodology

Other important sections of your methodology are:

Ethical Considerations

Always consider how your research will influence other individuals who are beyond the scope of the study. This is especially true for human subjects. As a researcher, you are always expected to make sure that your research and ideas do not harm anyone in any way.Discussion concerning data protection, data handling and data confidentiality will also be included in this brief segment.

• How did you ensure your participants’/respondents’ anonymity and/or confidentiality?
• Did you remove any identifiable markers after conducting the study (post-test stage) so that readers wouldn’t be able to guess the identity of the participant/respondent?
• Was personal information collected according to the purpose of the research? (For instance, asking respondents their age when it wasn’t even relevant in the study). All such ethical considerations need to be mentioned.

Even though there is no established rule to include ethical considerations and limitations within the methodology section, it’s generally recommended to include it in this section, as it makes more sense than including it, say, after the discussions section or within the conclusion.

This is mainly because limitations almost always occur in the methodology stage of research. And ethical considerations need to be taken while sampling, an important aspect of the research methodology.

Here are some examples of ethical issues that you should be mindful of

• Does your research involve participants recalling episodes of suffering and pain?
• Are you trying to find answers to questions considered culturally sensitive either by participants or the readers?
• Are your research, analysis and findings based on a specific location or a group of people?

All such issues should be categorically addressed and a justification provided for your chosen research methodology by highlighting the study’s benefits.

Reliability

Is your research study and findings reliable for other researchers in your field of work? To establish yourself as a reliable researcher, your study should be both authentic and reliable.

Reliability means the extent to which your research can yield similar results if it was replicated in another setting, at a different time, or under different circumstances. If replication occurs and different findings come to light, your (original) research would be deemed unreliable.

Limitations

Good dissertation writers will always acknowledge the limitations of their research study. Limitations in data sampling can decrease your results’ reliability.

A classic example of research limitation is collecting responses from people of a certain age group when you could have targeted a more representative cross-section of the population.Be humble and admit to your own study’s limitations. Doing so makes your referees, editors, supervisors, readers and anyone else involved in the research enterprise aware that you were also aware of the things that limited your study.

Limitations are NOT the same as implications. Sometimes, the two can be confused. Limitations lead to implications, that is, due to a certain factor being absent in the study (limitation) for instance, future research could be carried out in a setting where that factor is present (implication).

Dissertation Methodology Example

At this point, you might have a basic understanding of how to craft a well-written, organised, accurate methodology section for your dissertation. An example might help bring all the aforementioned points home. Here is a dissertation methodology example in pdf to better understand how to write methodology for a dissertation.

Sample Dissertation Methodology

Does your Research Methodology Have the Following?

• Great Research/Sources
• Perfect Language
• Accurate Sources

If not, we can help. Our panel of experts makes sure to keep the 3 pillars of Research Methodology strong.

Types of Methodologies

A scientific or lab-based study.

A methodology section for a scientific study will need to elaborate on reproducibility and meticulousness more than anything else. If your methods have obvious flaws, the readers are not going to be impressed. Therefore, it is important to ensure that your chosen research methodology is vigorous in nature.

Any information related to the procedure, setup and equipment should be clearly stated so other researchers in your field of study can work with the same method in the future if needed.

Variables that are likely to falsify your data must be taken into the equation to avoid ambiguities. It is recommended to present a comprehensive strategy to deal with these variables when gathering and analysing the data and drawing conclusions.

Statistical models employed as part of your scientific study will have to be justified, and so your methodology should include details of those statistical models.

Another scholar in the future might use any aspect of your methodology as the starting point for their research. For example, they might base their research on your methodology but analyse the data using other statistical models. Hence, this is something you should be mindful of.

Behavioural or Social Sciences-Based Dissertation

Like scientific or lab-based research, a behavioural and social sciences methodology needs to be built along the same lines. The chosen methodology should demonstrate reproducibility and firmness so other scholars can use your whole dissertation methodology or a part of it based on their research needs.

But there are additional issues that the researcher must take into consideration when working with human subjects. As a starting point, you will need to decide whether your analysis will be based on qualitative data, quantitative data or mixed-method of research, where qualitative data is used to provide contextual background to quantitative data or the other way around.

Here are some questions for you to consider:

• Will you observe the participants undertaking some activity, ask them to fill out a questionnaire, or record their responses during the interviews ?
• Will you base your research on existing evidence and datasets and avoid working with human subjects?
• What are the length, width, and reach of your data? Define its scope.
• Is the data highly explicit to the location or cultural setting you carried your study in, or can it be generalised to other situations and frameworks (reliability)? What are your reasons and justifications?

While you will be required to demonstrate that you have taken care of the above questions, it is equally important to make sure that you address your research study’s ethical issues side-by-side.

Of course, the first step in that regard will be to obtain formal approval for your research design from the ethics bodies (such as IRBs – institutional review boards), but still, there will be many more issues that could trigger a sense of grief and discomfort among some of the readers.

Humanities and Arts Dissertation Project

The rigour and dependability of the methods of research employed remain undisputed and unquestionable for humanities and arts-based dissertations as well. However, the way you convince your readers of your dissertation’s thoroughness is slightly different.

Unlike social science dissertation or a scientific study, the methodology of dissertations in arts and humanities subjects needs to be directly linked to the literature review regardless of how innovative your dissertation’s topic might be.

For example, you could demonstrate the relationship between A and B to discover a new theoretical background or use existing theories in a new framework.

The methodology section of humanities and arts-based dissertations is less complex, so there might be no need to justify it in detail. Students can achieve a seamless transition from the literature review to the analysis section.

However, like with every other type of research methodology, it is important to provide a detailed justification of your chosen methodology and relate it to the research problem.

Failing to do so could leave some readers unconvinced of your theoretical foundations’ suitability, which could potentially jeopardise your whole research.

Make sure that you are paying attention to and giving enough information about the social and historical background of the theoretical frameworks your research methodology is based on. This is especially important if there is an essential difference of opinion between your research and the research done on the subject in the past.

A justification of why opposing schools of thought disagree and why you still went ahead to use aspects of these schools of thought in your methodology should be clearly presented for the readers to understand how they would support your readings.

A Dissertation in Creative Arts

Some degree programs in the arts allow students to undertake a portfolio of artworks or creative writing rather than produce an extended dissertation research project.However, in practice, your creative research will be required to be submitted along with a comprehensive evaluative paper, including background information and an explanation that hypothesises your innovative exercise.

While this might seem like an easy thing to do, critical evaluation of someone’s work is highly complex and notorious in nature. This further reinforces the argument of developing a rigorous methodology and adhering to it.

As a scholar, you will be expected to showcase the ability to critically analyse your methodology and show that you are capable of critically evaluating your own creative work.Such an approach will help you justify your method of creating the work, which will give the readers the impression that your research is grounded in theory.

What to Avoid in Methodology?

All chapters of a dissertation paper are interconnected. This means that there will undoubtedly be some information that would overlap between the different chapters of the dissertation .

For example, some of the text material may seem appropriate to both the literature review and methodology sections; you might even end up moving information from pillar to post between different chapters as you edit and improve your dissertation .

However, make sure that you are not making the following a part of your dissertation methodology, even though it may seem appropriate to fit them in there:

A Long Review of Methods Employed by Previous Researchers

It might seem relevant to include details of the models your dissertation methodology is based on. However, a detailed review of models and precedents used by other scholars and theorists will better fit in the literature review chapter, which you can link back to. This will help the readers understand why you decided to go in favour of or against a certain tactic.

Unnecessary Details Readers Might Not be Interested In

There is absolutely no need to provide extensive details of things like lab equipment and experiment procedures. Having such information in the methodology chapter would discourage some readers who might not be interested in your equipment, setup, lab environment, etc.

Your aim as the author of the document will be to retain the readers’ interest and make the methodology chapter as readable as possible.

While it is important to get all the information relating to how others can reproduce your experiment, it is equally important to ensure your methodology section isn’t unnecessarily long. Again, additional information is better to be placed within the appendices chapter.

The methodology is not the section to provide raw data, even if you are only discussing the data collection process. All such information should be moved to the appendices section.

Even if you feel some finding or numerical data is crucial to be presented within the methodology section, you can, at most, make brief comments about such data. Its discussion, however, is only allowed in the discussions section .

What Makes your Methodology Stand Out?

The factors which can determine if your dissertation methodology is ‘great’ depend on many factors, including the level of study you are currently enrolled in.

Undergraduate dissertations are, of course, less complex and less demanding. At most universities in the UK, undergraduate students are required to exhibit the ability to conduct thorough research as they engage for the first time with theoretical and conceptual frameworks in their chosen research area.

As an undergraduate student, you will be expected to showcase the capacity to reproduce what you have learnt from theorists in your academic subject, transform your leanings into a methodology that would help you address the research problem, and test the research hypothesis, as mentioned in the introduction chapter.

A great undergraduate-level dissertation will incorporate different schools of thought and make a valuable contribution to existing knowledge. However, in general, undergraduate-level dissertations’ focus should be to show thorough desk-based and independent research skills.

Postgraduate dissertation papers are much more compound and challenging because they are expected to make a substantial contribution to existing knowledge.

Depending on the academic institute, some postgraduate students are even required to develop a project published by leading academic journals as an approval of their research skills.

It is important to recognise the importance of a postgraduate dissertation towards building your professional career, especially if your work is considered impactful in your area of study and receives citations from multiple scholars, enhancing your reputation in academic communities.

Even if some academics cite your literature review and conclusion in their own work, it is a well-known fact that your methodology framework will result in many more citations regardless of your academic subject.

Other scholars and researchers in your area of study are likely to give much more value to a well-crafted methodology, especially one they can use as the starting point for their own research.

Of course, they can alter, refine and enhance your methodology in one way or another. They can even apply your methodological framework to a new data set or apply it in a completely new situation that is irrelevant to your work.

Finally, postgraduate dissertations are expected to be highly convincing and demonstrate in-depth engagement. They should be reproducible and show rigour, so the findings and conclusions can be regarded as authentic and reliable among scientific and academic communities.

The methodology is the door to success when it comes to dissertation projects. An original methodology that takes into consideration all aspects of research is likely to have an impact on the field of study.

As a postgraduate student, you should ask yourself, Is my dissertation methodology reproducible and transferable? Producing a methodology that others can reproduce in the future is as important as answering research questions .

The methodology chapter can either make or break the grade of your research/dissertation paper. It’s one of the research elements that leave a memorable impression on your readers. So, it would help if you took your time when it comes to choosing the right design and philosophical approach for your research.

Always use authentic academic sources and discuss your plans in detail with your supervisor if you believe your research design or approach has flaws in it.

Did this article help you learn how to write a dissertation methodology and how to structure a dissertation methodology? Let us know in your comments.

Are you struggling to create a thorough and well-rounded dissertation methodology?

Avail of our dissertation writing services ! At ResearchProspect, we have Master’s and PhD qualified dissertation writers for all academic subjects, so you can be confident that the writer we will assign to your dissertation order will be an expert in your field of study. They can help you with your whole dissertation or just a part of it. You decide how much or how little help you need.

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Dissertations 4: methodology: start.

• Introduction & Philosophy
• Methodology

The Methodology Chapter

The methodology chapter flows organically from the literature review. This means that at this stage you should have reviewed the literature in your field of study, analysed research that has been conducted and highlighted how it was conducted. In turn, this should reflect the foundation of your own project as you will have to link it to your chosen research method.  

The methodology chapter also involves describing your method in detail and justifying the approach you are going to adopt, taking into consideration the limitations and ethical implications of your model. Your description should be detailed enough that someone reading your methodology can recreate your approach. 

Therefore, the methodology requires you to:

• describe your methods
• demonstrate a clear connection between your research question (or hypothesis) and the means by which you will reach your conclusions 
• present justification (strengths) and limitations (weaknesses) of your methods  

What are Methods & Methodology?

Methods 

In order to appreciate what methods are, let us remember what research is about. Research can be summarised into three points (Cottrell, 2014, p9): 

A question 

Methods of arriving at an answer 

The answer 

Thus, methods are the means to research and answer the research question, or test the hypothesis. Methods include techniques and procedures used to obtain and analyse data (Saunders, Lewis and Thornhill, 2015, p4). Your methods can consist of primary and secondary sources, qualitative, quantitative and mixed methods, as illustrated in this guide.  

Methodology 

Methodology is sometimes used interchangeably with methods, or as the set of methods used in a research. More specifically, as the name would suggest, methodo-logy is the logos, the reasoning, on the methods. It is also referred to as the theory of how research should be undertaken (Saunders, Lewis and Thornhill, 2015, p4). This is why you normally would have a methodology, rather than methods, chapter in a dissertation.  

First Key Tip

We hope this guide will be helpful, but it is of fundamental importance that you also use a  research methods book  (or other authoritative source) for your discipline . The book will guide you on best methods for your research, give you practical guidance, and present critical insights and limitations of the methods.

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• Last Updated: Sep 14, 2022 12:58 PM
• URL: https://libguides.westminster.ac.uk/methodology-for-dissertations

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Writing your Dissertation: Methodology

A key part of your dissertation or thesis is the methodology. This is not quite the same as ‘methods’.

The methodology describes the broad philosophical underpinning to your chosen research methods, including whether you are using qualitative or quantitative methods, or a mixture of both, and why.

You should be clear about the academic basis for all the choices of research methods that you have made. ' I was interested ' or ' I thought... ' is not enough; there must be good academic reasons for your choice.

What to Include in your Methodology

If you are submitting your dissertation in sections, with the methodology submitted before you actually undertake the research, you should use this section to set out exactly what you plan to do.

The methodology should be linked back to the literature to explain why you are using certain methods, and the academic basis of your choice.

If you are submitting as a single thesis, then the Methodology should explain what you did, with any refinements that you made as your work progressed. Again, it should have a clear academic justification of all the choices that you made and be linked back to the literature.

Common Research Methods for the Social Sciences

There are numerous research methods that can be used when researching scientific subjects, you should discuss which are the most appropriate for your research with your supervisor.

The following research methods are commonly used in social science, involving human subjects:

One of the most flexible and widely used methods for gaining qualitative information about people’s experiences, views and feelings is the interview.

An interview can be thought of as a guided conversation between a researcher (you) and somebody from whom you wish to learn something (often referred to as the ‘informant’).

The level of structure in an interview can vary, but most commonly interviewers follow a semi-structured format.  This means that the interviewer will develop a guide to the topics that he or she wishes to cover in the conversation, and may even write out a number of questions to ask.

However, the interviewer is free to follow different paths of conversation that emerge over the course of the interview, or to prompt the informant to clarify and expand on certain points. Therefore, interviews are particularly good tools for gaining detailed information where the research question is open-ended in terms of the range of possible answers.

Interviews are not particularly well suited for gaining information from large numbers of people. Interviews are time-consuming, and so careful attention needs to be given to selecting informants who will have the knowledge or experiences necessary to answer the research question.  

See our page: Interviews for Research for more information.

Observations

If a researcher wants to know what people do under certain circumstances, the most straightforward way to get this information is sometimes simply to watch them under those circumstances.

Observations can form a part of either quantitative or qualitative research.  For instance, if a researcher wants to determine whether the introduction of a traffic sign makes any difference to the number of cars slowing down at a dangerous curve, she or he could sit near the curve and count the number of cars that do and do not slow down.  Because the data will be numbers of cars, this is an example of quantitative observation.

A researcher wanting to know how people react to a billboard advertisement might spend time watching and describing the reactions of the people.  In this case, the data would be descriptive , and would therefore be qualitative.

There are a number of potential ethical concerns that can arise with an observation study. Do the people being studied know that they are under observation?  Can they give their consent?  If some people are unhappy with being observed, is it possible to ‘remove’ them from the study while still carrying out observations of the others around them?

See our page: Observational Research and Secondary Data for more information.

Questionnaires

If your intended research question requires you to collect standardised (and therefore comparable) information from a number of people, then questionnaires may be the best method to use.

Questionnaires can be used to collect both quantitative and qualitative data, although you will not be able to get the level of detail in qualitative responses to a questionnaire that you could in an interview.

Questionnaires require a great deal of care in their design and delivery, but a well-developed questionnaire can be distributed to a much larger number of people than it would be possible to interview. 

Questionnaires are particularly well suited for research seeking to measure some parameters for a group of people (e.g., average age, percentage agreeing with a proposition, level of awareness of an issue), or to make comparisons between groups of people (e.g., to determine whether members of different generations held the same or different views on immigration).

See our page: Surveys and Survey Design for more information.

Documentary Analysis

Documentary analysis involves obtaining data from existing documents without having to question people through interview, questionnaires or observe their behaviour. Documentary analysis is the main way that historians obtain data about their research subjects, but it can also be a valuable tool for contemporary social scientists.

Documents are tangible materials in which facts or ideas have been recorded.  Typically, we think of items written or produced on paper, such as newspaper articles, Government policy records, leaflets and minutes of meetings.  Items in other media can also be the subject of documentary analysis, including films, songs, websites and photographs.

Documents can reveal a great deal about the people or organisation that produced them and the social context in which they emerged. 

Some documents are part of the public domain and are freely accessible, whereas other documents may be classified, confidential or otherwise unavailable to public access.  If such documents are used as data for research, the researcher must come to an agreement with the holder of the documents about how the contents can and cannot be used and how confidentiality will be preserved.

How to Choose your Methodology and Precise Research Methods

Your methodology should be linked back to your research questions and previous research.

Visit your university or college library and ask the librarians for help; they should be able to help you to identify the standard research method textbooks in your field. See also our section on Research Methods for some further ideas.

Such books will help you to identify your broad research philosophy, and then choose methods which relate to that. This section of your dissertation or thesis should set your research in the context of its theoretical underpinnings.

The methodology should also explain the weaknesses of your chosen approach and how you plan to avoid the worst pitfalls, perhaps by triangulating your data with other methods, or why you do not think the weakness is relevant.

For every philosophical underpinning, you will almost certainly be able to find researchers who support it and those who don’t.

Use the arguments for and against expressed in the literature to explain why you have chosen to use this methodology or why the weaknesses don’t matter here.

Structuring your Methodology

It is usually helpful to start your section on methodology by setting out the conceptual framework in which you plan to operate with reference to the key texts on that approach.

You should be clear throughout about the strengths and weaknesses of your chosen approach and how you plan to address them. You should also note any issues of which to be aware, for example in sample selection or to make your findings more relevant.

You should then move on to discuss your research questions, and how you plan to address each of them.

This is the point at which to set out your chosen research methods, including their theoretical basis, and the literature supporting them. You should make clear whether you think the method is ‘tried and tested’ or much more experimental, and what kind of reliance you could place on the results. You will also need to discuss this again in the discussion section.

Your research may even aim to test the research methods, to see if they work in certain circumstances.

You should conclude by summarising your research methods, the underpinning approach, and what you see as the key challenges that you will face in your research. Again, these are the areas that you will want to revisit in your discussion.

Your methodology, and the precise methods that you choose to use in your research, are crucial to its success.

It is worth spending plenty of time on this section to ensure that you get it right. As always, draw on the resources available to you, for example by discussing your plans in detail with your supervisor who may be able to suggest whether your approach has significant flaws which you could address in some way.

Continue to: Research Methods Designing Research

See Also: Dissertation: Results and Discussion Writing a Literature Review | Writing a Research Proposal Writing a Dissertation: The Introduction

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What are acceptable dissertation research methods?

August 16, 2023

Reading time:  3–4 minutes

Doctoral research is the cornerstone of a PhD program .

In order to write a dissertation, you must complete extensive, detailed research. Depending on your area of study, different types of research methods will be appropriate to complete your work.

“The choice of research method depends on the questions you hope to answer with your research,” says Curtis Brant, PhD, Capella University dean of research and scholarship.

Once you’ve identified your research problem, you’ll employ the methodology best suited for solving the problem.

There are two primary dissertation research methods: qualitative and quantitative.

Qualitative

Qualitative research focuses on examining the topic via cultural phenomena, human behavior or belief systems. This type of research uses interviews, open-ended questions or focus groups to gain insight into people’s thoughts and beliefs around certain behaviors and systems.

Dr. Brant says there are several approaches to qualitative inquiry. The three most routinely used include:

Generic qualitative inquiry. The researcher focuses on people’s experiences or perceptions in the real world. This often includes, but is not limited to, subjective opinions, attitudes and beliefs .

Case study. The researcher performs an in-depth exploration of a program, event, activity or process with an emphasis on the experience of one or more individuals. The focus of this kind of inquiry must be defined and often includes more than one set of data, such as interviews and field notes, observations or other qualitative data.

Phenomenological. The researcher identifies lived experiences associated with how an individual encounters and engages with the real world .

Qualitative research questions seek to discover:

• A participant’s verbal descriptions of a phenomenon being investigated
•  A researcher’s observations of the phenomenon being investigated
• An integrated interpretation of participant’s descriptions and researchers observations

Quantitative

Quantitative research involves the empirical investigation of observable and measurable variables. It is used for theory testing, predicting outcomes or determining relationships between and among variables using statistical analysis.

According to Dr. Brant, there are two primary data sources for quantitative research.

Surveys: Surveys involve asking people a set of questions, usually testing for linear relationships, statistical differences or statistical independence. This approach is common in correlation research designs.

Archival research (secondary data analysis). Archival research involves using preexisting data to answer research questions instead of collecting data from active human participants.

Quantitative research questions seek to address:

• Descriptions of variables being investigated
• Measurements of relationships between (at least two) variables
• Differences between two or more groups’ scores on a variable or variables

Which method should you choose?

Choosing a qualitative or quantitative methodology for your research will be based on the nature of the questions you ask, the preferred method in your field, the feasibility of the approach and other factors. Many programs offer doctoral mentors and support teams that can help guide you throughout the process.

Capella University offers PhD and professional doctorate degree programs ranging from business to education and health to technology. Learn more about Capella doctoral programs and doctoral support.

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What Is a Dissertation Methodology?

How to choose your methodology, final thoughts, how to write your dissertation methodology.

Updated September 30, 2021

Due to the complexities of the different research methods, writing your dissertation methodology can often be the most challenging and time-consuming part of your postgraduate dissertation .

This article focuses on the importance of writing a good PhD or master's dissertation methodology – and how to achieve this.

A postgraduate dissertation (or thesis) is usually formed of several detailed sections, including:

Abstract – A summary of your research topic.

Introduction – Provides background information on your topic, putting it into context. You will also confirm the main focus of your study, explain why it will add value to your area of interest and specify your key objectives.

Literature Review – A critical review of literature that relates to your chosen research topic. You will also need to identify which gap in the literature your study aims to address.

Methodology – Focuses on the research methods used within your research.

Results – Used to report on your main findings and how these relate to your research question.

Conclusion – Used to confirm the answer to your main research question, reflect on the research process and offer recommendations on future research.

The dissertation methodology forms the skeleton of any research project. It provides the reader with a clear outline of the methods you decided to use when carrying out your research.

By studying your dissertation methodology, the reader will be able to assess your research in terms of its validity and reliability.

In line with the outline given above, the methodology chapter usually appears after the literature review . Your methodology should be closely linked to the research that you conducted as part of this review, as well as the questions you aim to answer through your research and analysis.

Taking the time to find out about the different types of research available to you will allow you to identify any potential drawbacks to the method you have chosen to use. You should then be able to make allowances or adjustments to address these when it comes to carrying out your research.

Choosing your methodology will largely depend on the discipline of the qualification you are studying for and the question your dissertation will seek to answer. In most cases, you will use quantitative or qualitative research methods, although some projects will benefit from using a combination of both.

Quantitative research methods are used to gather numerical information. This research method is particularly useful if you are seeking to count, categorise, measure or identify patterns in data. To collect quantitative data, you might choose to conduct experiments, tests or surveys.

Qualitative research methods are used to gather non-statistical data. Instead of using numbers to create charts or graphs, you will need to categorise the information according to identifiers. This research method is most useful if you are seeking to develop a hypothesis. To collect qualitative data, you might choose to conduct focus groups, interviews or observations.

What to Include in Your Dissertation Methodology

Below is a dissertation methodology example to show you what information to include:

You will need to reiterate your research topic or question and give an overview of how you plan to investigate this. If there were any ethical or philosophical considerations to be made, give details.

For example, you may have sought informed consent from the people taking part in interviews or surveys.

Outline of the Methods Chosen

Confirm whether you have chosen to use quantitative research, qualitative research or a combination of both.

When choosing between qualitative and quantitative research methods, you will need to carry out initial literature and textbook research to establish the standard research methods that are normally used within your chosen area of research.

If you are not sure where to start, you could visit the library at your college or university and ask one of the librarians to help you to identify the most relevant texts.

Explanation of the Methods Chosen

Explain your rationale for selecting your chosen research methods. You should also give an overview of why these were more appropriate than using another research method.

Think about where and when the research took place and who was involved. For example, this might include information on the venue used for interviews or focus groups, dates and timescales, and whether participants were part of a particular demographic group.

Here are some examples of the type of information you may wish to include:

Qualitative Research Methods

Personal observations – Where and when did you conduct the observations? Who did you observe? Were they part of a particular community or group? How long did each observation take? How did you record your findings – did you collect audio recordings, video footage or written observations?

Focus groups – Where and when did the focus group take place? Who was involved? How were they selected? How many people took part? Were the questions asked structured, unstructured or semi-structured? Remember to include a copy of the questions that were used as an appendix.

Interviews – Where and when did the interviews take place? Who took part? How did you select the participants? What type of questions did you ask? How did you record your findings? Remember to include a copy of the questions that were used as an appendix.

The researcher’s objective was to find out customer perceptions on improving the product range currently offered by Company Y. Semi-structured interviews were held with 15 returning customers from the key target demographic for Company Y (18- to 35-year-olds). For research purposes, a returning customer was defined as somebody who purchased products from Company Y at least two times per week during the past three months. The interviews were held in an office in the staff area of the retail premises. Each interview lasted approximately 25 minutes. Responses were recorded through note-taking as none of the respondents wished to give their consent to be filmed.

Quantitative Research Methods

Existing information or data – What were the sources of the material used? How did you select material? Did you only use data published within a particular time frame?

Experiments – What tools or equipment did you use? What techniques were required? Note that when conducting experiments, it is particularly important to provide enough information to allow another researcher to conduct the experiment and obtain the same results.

Surveys – Were respondents asked to answer multiple-choice questions or complete free-text fields? How many questions were used? How long were people given to answer all of the questions? What were the demographics of the participants? Remember to include a copy of the survey in the appendices.

The survey was made up of 10 multiple-choice questions and 5 questions to be rated using a 5-point Lickert scale. The objective was to have 250 customers of Company Z complete the survey at the Company Z HQ between 1st and 5th February 2019, between the hours of 12 p.m. and 5 p.m. For research purposes, a customer was defined as any person who had purchased a product from Company Z during 2018. Customers completing the survey were allowed a maximum of 10 minutes to answer all of the questions. 200 customers responded, however not all of the surveys were completed in full, so only 150 survey results were able to be used in the data analysis.

How Was the Data Analysed?

If you have chosen to use quantitative research methods, you will need to prepare the data before analysing it – for example, you will need to check for variables, missing data and outliers. If you have used computer software to aid with analysis, information on this should also be included.

For qualitative data, you will need to categorise and code the ideas and themes that are identified from the raw data. You may also need to use techniques such as narrative analysis or discourse analysis to interpret the meaning behind responses given.

What Materials and Equipment Were Used During the Research?

This could include anything from laboratory equipment used in a scientific experiment to computer software used to analyse the results.

Were There Any Hurdles or Difficulties Faced During the Research?

If so, what were they and how did you manage to overcome them? This could be anything from difficulties in finding participants, problems obtaining consent or a shortage of the required resources needed to conduct a scientific experiment.

This paragraph should be used to evaluate the research you have conducted and justify your reasons for choosing this approach.

You do not need to go into great detail, as you will present and discuss your results in-depth within your dissertation’s ‘Results’ section.

You will need to briefly explain whether your results were conclusive, whether there were any variables and whether your choice of methodology was effective in practice.

Tips for Writing Your Dissertation Methodology

The objective for the methodology is not only to describe the methods that you used for your research. You will also need to demonstrate why you chose to use them and how you applied them.

The key point is to show that your research was conducted meticulously.

Try to keep your writing style concise and clear; this will ensure that it is easy for the reader to understand and digest.

Here are five top tips to consider when writing your dissertation methodology:

1. Look at Other Methodology Sections

Ask your supervisor to provide you with a few different examples of previously written dissertations. Reading through methodologies that have been written by past students will give you a good idea of what your finished methodology section should look like.

2. Plan Your Structure

Whichever research methods you have chosen to use, your dissertation methodology should be a clearly structured, well written section that gives a strong and justified argument for your chosen research methods.

You may wish to use headings such as:

• Research methods
• Explanation of research methods chosen
• Data analysis and references

Once you have drafted an outline, ask your supervisor for advice on whether there is anything you have missed and whether your structure looks logical.

3. Consider Your Audience

When writing your methodology, have regard for the people who are likely to be reading it. For example, if you have chosen to use research methods that are commonly chosen within your area of research or discipline, there is no need to give a great deal of justification or background information.

If you decide to use a less popular approach, it is advisable to give much more detailed information on how and why you chose to use this method.

4. Remain Focused on Your Aims and Research Questions

Your dissertation methodology should give a clear indication as to why the research methods you have chosen are suitable for the aims of your research.

When writing your dissertation methodology, ensure that you link your research choices back to the overall aims and objectives of your dissertation. To help you to remain focused, it can be helpful to include a clear definition of the question you are aiming to answer at the start of your methodology section.

5. Refer to Any Obstacles or Difficulties That You Dealt With

If you faced any problems during the data collection or analysis phases, use the methodology section to talk about what you did to address these issues and minimise the impact.

Whether you are completing a PhD or master's degree, writing your thesis or dissertation methodology is often considered to be the most difficult and time-consuming part of completing your major research project.

The key to success when writing a methodology section is to have a clear structure. Remember, the purpose of the methodology section of your research project is to ensure that the reader has a full understanding of the methods you have chosen.

You should use your methodology section to provide clear justification as to why you have chosen a particular research method instead of other potential methods. Avoid referring to your personal opinions, thoughts or interests within your methodology; keep the information that you include factual and ensure that everything is backed up by appropriate academic references.

You might also be interested in these other Wikijob articles:

Or explore the Postgraduate / PHD sections.

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Guide for Thesis Research

• Introduction to the Thesis Process
• Project Planning
• Literature Review
• Theoretical Frameworks
• Research Methodology
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Basics of Methodology

Research is a process of inquiry that is carried out in a pondered, organized, and strategic manner. In order to obtain high quality results, it is important to understand methodology.

Research methodology refers to how your project will be designed, what you will observe or measure, and how you will collect and analyze data. The methods you choose must be appropriate for your field and for the specific research questions you are setting out to answer.

A strong understanding of methodology will help you:

• apply appropriate research techniques
• design effective data collection instruments
• analyze and interpret your data
• develop well-founded conclusions

Below, you will find resources that mostly cover general aspects of research methodology. In the left column, you will find resources that specifically cover qualitative, quantitative, and mixed methods research.

General Works on Methodology

Qualitative Research

Quantitative Research

Mixed Methods Research

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Organizing Your Social Sciences Research Paper

• 6. The Methodology
• Purpose of Guide
• Design Flaws to Avoid
• Independent and Dependent Variables
• Glossary of Research Terms
• Reading Research Effectively
• Narrowing a Topic Idea
• Broadening a Topic Idea
• Extending the Timeliness of a Topic Idea
• Academic Writing Style
• Applying Critical Thinking
• Choosing a Title
• Making an Outline
• Paragraph Development
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• Executive Summary
• The C.A.R.S. Model
• Background Information
• The Research Problem/Question
• Theoretical Framework
• Citation Tracking
• Content Alert Services
• Evaluating Sources
• Primary Sources
• Secondary Sources
• Tiertiary Sources
• Scholarly vs. Popular Publications
• Qualitative Methods
• Quantitative Methods
• Insiderness
• Using Non-Textual Elements
• Limitations of the Study
• Common Grammar Mistakes
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The methods section describes actions taken to investigate a research problem and the rationale for the application of specific procedures or techniques used to identify, select, process, and analyze information applied to understanding the problem, thereby, allowing the reader to critically evaluate a study’s overall validity and reliability. The methodology section of a research paper answers two main questions: How was the data collected or generated? And, how was it analyzed? The writing should be direct and precise and always written in the past tense.

Kallet, Richard H. "How to Write the Methods Section of a Research Paper." Respiratory Care 49 (October 2004): 1229-1232.

Importance of a Good Methodology Section

You must explain how you obtained and analyzed your results for the following reasons:

• Readers need to know how the data was obtained because the method you chose affects the results and, by extension, how you interpreted their significance in the discussion section of your paper.
• Methodology is crucial for any branch of scholarship because an unreliable method produces unreliable results and, as a consequence, undermines the value of your analysis of the findings.
• In most cases, there are a variety of different methods you can choose to investigate a research problem. The methodology section of your paper should clearly articulate the reasons why you have chosen a particular procedure or technique.
• The reader wants to know that the data was collected or generated in a way that is consistent with accepted practice in the field of study. For example, if you are using a multiple choice questionnaire, readers need to know that it offered your respondents a reasonable range of answers to choose from.
• The method must be appropriate to fulfilling the overall aims of the study. For example, you need to ensure that you have a large enough sample size to be able to generalize and make recommendations based upon the findings.
• The methodology should discuss the problems that were anticipated and the steps you took to prevent them from occurring. For any problems that do arise, you must describe the ways in which they were minimized or why these problems do not impact in any meaningful way your interpretation of the findings.
• In the social and behavioral sciences, it is important to always provide sufficient information to allow other researchers to adopt or replicate your methodology. This information is particularly important when a new method has been developed or an innovative use of an existing method is utilized.

Bem, Daryl J. Writing the Empirical Journal Article. Psychology Writing Center. University of Washington; Denscombe, Martyn. The Good Research Guide: For Small-Scale Social Research Projects . 5th edition. Buckingham, UK: Open University Press, 2014; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008.

Structure and Writing Style

I.  Groups of Research Methods

There are two main groups of research methods in the social sciences:

• The e mpirical-analytical group approaches the study of social sciences in a similar manner that researchers study the natural sciences . This type of research focuses on objective knowledge, research questions that can be answered yes or no, and operational definitions of variables to be measured. The empirical-analytical group employs deductive reasoning that uses existing theory as a foundation for formulating hypotheses that need to be tested. This approach is focused on explanation.
• The i nterpretative group of methods is focused on understanding phenomenon in a comprehensive, holistic way . Interpretive methods focus on analytically disclosing the meaning-making practices of human subjects [the why, how, or by what means people do what they do], while showing how those practices arrange so that it can be used to generate observable outcomes. Interpretive methods allow you to recognize your connection to the phenomena under investigation. However, the interpretative group requires careful examination of variables because it focuses more on subjective knowledge.

II.  Content

The introduction to your methodology section should begin by restating the research problem and underlying assumptions underpinning your study. This is followed by situating the methods you used to gather, analyze, and process information within the overall “tradition” of your field of study and within the particular research design you have chosen to study the problem. If the method you choose lies outside of the tradition of your field [i.e., your review of the literature demonstrates that the method is not commonly used], provide a justification for how your choice of methods specifically addresses the research problem in ways that have not been utilized in prior studies.

The remainder of your methodology section should describe the following:

• Decisions made in selecting the data you have analyzed or, in the case of qualitative research, the subjects and research setting you have examined,
• Tools and methods used to identify and collect information, and how you identified relevant variables,
• The ways in which you processed the data and the procedures you used to analyze that data, and
• The specific research tools or strategies that you utilized to study the underlying hypothesis and research questions.

In addition, an effectively written methodology section should:

• Introduce the overall methodological approach for investigating your research problem . Is your study qualitative or quantitative or a combination of both (mixed method)? Are you going to take a special approach, such as action research, or a more neutral stance?
• Indicate how the approach fits the overall research design . Your methods for gathering data should have a clear connection to your research problem. In other words, make sure that your methods will actually address the problem. One of the most common deficiencies found in research papers is that the proposed methodology is not suitable to achieving the stated objective of your paper.
• Describe the specific methods of data collection you are going to use , such as, surveys, interviews, questionnaires, observation, archival research. If you are analyzing existing data, such as a data set or archival documents, describe how it was originally created or gathered and by whom. Also be sure to explain how older data is still relevant to investigating the current research problem.
• Explain how you intend to analyze your results . Will you use statistical analysis? Will you use specific theoretical perspectives to help you analyze a text or explain observed behaviors? Describe how you plan to obtain an accurate assessment of relationships, patterns, trends, distributions, and possible contradictions found in the data.
• Provide background and a rationale for methodologies that are unfamiliar for your readers . Very often in the social sciences, research problems and the methods for investigating them require more explanation/rationale than widely accepted rules governing the natural and physical sciences. Be clear and concise in your explanation.
• Provide a justification for subject selection and sampling procedure . For instance, if you propose to conduct interviews, how do you intend to select the sample population? If you are analyzing texts, which texts have you chosen, and why? If you are using statistics, why is this set of data being used? If other data sources exist, explain why the data you chose is most appropriate to addressing the research problem.
• Provide a justification for case study selection . A common method of analyzing research problems in the social sciences is to analyze specific cases. These can be a person, place, event, phenomenon, or other type of subject of analysis that are either examined as a singular topic of in-depth investigation or multiple topics of investigation studied for the purpose of comparing or contrasting findings. In either method, you should explain why a case or cases were chosen and how they specifically relate to the research problem.
• Describe potential limitations . Are there any practical limitations that could affect your data collection? How will you attempt to control for potential confounding variables and errors? If your methodology may lead to problems you can anticipate, state this openly and show why pursuing this methodology outweighs the risk of these problems cropping up.

NOTE :   Once you have written all of the elements of the methods section, subsequent revisions should focus on how to present those elements as clearly and as logically as possibly. The description of how you prepared to study the research problem, how you gathered the data, and the protocol for analyzing the data should be organized chronologically. For clarity, when a large amount of detail must be presented, information should be presented in sub-sections according to topic. If necessary, consider using appendices for raw data.

ANOTHER NOTE : If you are conducting a qualitative analysis of a research problem , the methodology section generally requires a more elaborate description of the methods used as well as an explanation of the processes applied to gathering and analyzing of data than is generally required for studies using quantitative methods. Because you are the primary instrument for generating the data [e.g., through interviews or observations], the process for collecting that data has a significantly greater impact on producing the findings. Therefore, qualitative research requires a more detailed description of the methods used.

YET ANOTHER NOTE :   If your study involves interviews, observations, or other qualitative techniques involving human subjects , you may be required to obtain approval from the university's Office for the Protection of Research Subjects before beginning your research. This is not a common procedure for most undergraduate level student research assignments. However, i f your professor states you need approval, you must include a statement in your methods section that you received official endorsement and adequate informed consent from the office and that there was a clear assessment and minimization of risks to participants and to the university. This statement informs the reader that your study was conducted in an ethical and responsible manner. In some cases, the approval notice is included as an appendix to your paper.

III.  Problems to Avoid

Irrelevant Detail The methodology section of your paper should be thorough but concise. Do not provide any background information that does not directly help the reader understand why a particular method was chosen, how the data was gathered or obtained, and how the data was analyzed in relation to the research problem [note: analyzed, not interpreted! Save how you interpreted the findings for the discussion section]. With this in mind, the page length of your methods section will generally be less than any other section of your paper except the conclusion.

Unnecessary Explanation of Basic Procedures Remember that you are not writing a how-to guide about a particular method. You should make the assumption that readers possess a basic understanding of how to investigate the research problem on their own and, therefore, you do not have to go into great detail about specific methodological procedures. The focus should be on how you applied a method , not on the mechanics of doing a method. An exception to this rule is if you select an unconventional methodological approach; if this is the case, be sure to explain why this approach was chosen and how it enhances the overall process of discovery.

Problem Blindness It is almost a given that you will encounter problems when collecting or generating your data, or, gaps will exist in existing data or archival materials. Do not ignore these problems or pretend they did not occur. Often, documenting how you overcame obstacles can form an interesting part of the methodology. It demonstrates to the reader that you can provide a cogent rationale for the decisions you made to minimize the impact of any problems that arose.

Literature Review Just as the literature review section of your paper provides an overview of sources you have examined while researching a particular topic, the methodology section should cite any sources that informed your choice and application of a particular method [i.e., the choice of a survey should include any citations to the works you used to help construct the survey].

It’s More than Sources of Information! A description of a research study's method should not be confused with a description of the sources of information. Such a list of sources is useful in and of itself, especially if it is accompanied by an explanation about the selection and use of the sources. The description of the project's methodology complements a list of sources in that it sets forth the organization and interpretation of information emanating from those sources.

Azevedo, L.F. et al. "How to Write a Scientific Paper: Writing the Methods Section." Revista Portuguesa de Pneumologia 17 (2011): 232-238; Blair Lorrie. “Choosing a Methodology.” In Writing a Graduate Thesis or Dissertation , Teaching Writing Series. (Rotterdam: Sense Publishers 2016), pp. 49-72; Butin, Dan W. The Education Dissertation A Guide for Practitioner Scholars . Thousand Oaks, CA: Corwin, 2010; Carter, Susan. Structuring Your Research Thesis . New York: Palgrave Macmillan, 2012; Kallet, Richard H. “How to Write the Methods Section of a Research Paper.” Respiratory Care 49 (October 2004):1229-1232; Lunenburg, Frederick C. Writing a Successful Thesis or Dissertation: Tips and Strategies for Students in the Social and Behavioral Sciences . Thousand Oaks, CA: Corwin Press, 2008. Methods Section. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Rudestam, Kjell Erik and Rae R. Newton. “The Method Chapter: Describing Your Research Plan.” In Surviving Your Dissertation: A Comprehensive Guide to Content and Process . (Thousand Oaks, Sage Publications, 2015), pp. 87-115; What is Interpretive Research. Institute of Public and International Affairs, University of Utah; Writing the Experimental Report: Methods, Results, and Discussion. The Writing Lab and The OWL. Purdue University; Methods and Materials. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College.

Writing Tip

Statistical Designs and Tests? Do Not Fear Them!

Don't avoid using a quantitative approach to analyzing your research problem just because you fear the idea of applying statistical designs and tests. A qualitative approach, such as conducting interviews or content analysis of archival texts, can yield exciting new insights about a research problem, but it should not be undertaken simply because you have a disdain for running a simple regression. A well designed quantitative research study can often be accomplished in very clear and direct ways, whereas, a similar study of a qualitative nature usually requires considerable time to analyze large volumes of data and a tremendous burden to create new paths for analysis where previously no path associated with your research problem had existed.

To locate data and statistics, GO HERE .

Another Writing Tip

Knowing the Relationship Between Theories and Methods

There can be multiple meaning associated with the term "theories" and the term "methods" in social sciences research. A helpful way to delineate between them is to understand "theories" as representing different ways of characterizing the social world when you research it and "methods" as representing different ways of generating and analyzing data about that social world. Framed in this way, all empirical social sciences research involves theories and methods, whether they are stated explicitly or not. However, while theories and methods are often related, it is important that, as a researcher, you deliberately separate them in order to avoid your theories playing a disproportionate role in shaping what outcomes your chosen methods produce.

Introspectively engage in an ongoing dialectic between the application of theories and methods to help enable you to use the outcomes from your methods to interrogate and develop new theories, or ways of framing conceptually the research problem. This is how scholarship grows and branches out into new intellectual territory.

Reynolds, R. Larry. Ways of Knowing. Alternative Microeconomics . Part 1, Chapter 3. Boise State University; The Theory-Method Relationship. S-Cool Revision. United Kingdom.

Yet Another Writing Tip

Methods and the Methodology

Do not confuse the terms "methods" and "methodology." As Schneider notes, a method refers to the technical steps taken to do research . Descriptions of methods usually include defining and stating why you have chosen specific techniques to investigate a research problem, followed by an outline of the procedures you used to systematically select, gather, and process the data [remember to always save the interpretation of data for the discussion section of your paper].

The methodology refers to a discussion of the underlying reasoning why particular methods were used . This discussion includes describing the theoretical concepts that inform the choice of methods to be applied, placing the choice of methods within the more general nature of academic work, and reviewing its relevance to examining the research problem. The methodology section also includes a thorough review of the methods other scholars have used to study the topic.

Bryman, Alan. "Of Methods and Methodology." Qualitative Research in Organizations and Management: An International Journal 3 (2008): 159-168; Schneider, Florian. “What's in a Methodology: The Difference between Method, Methodology, and Theory…and How to Get the Balance Right?” PoliticsEastAsia.com. Chinese Department, University of Leiden, Netherlands.

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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.

1. Qualitative

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
• Autoethnographies
• 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. 

2. Quantitative

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.

3. Mixed-Method

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

Personal Considerations

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. 

Professional Considerations

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. 

Academic Considerations

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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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.

Data collection

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) .

Data analysis

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.

Ethical considerations

• 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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Key Elements of a Well-Written Dissertation Methodology – (Examples Included)

As a researcher, you need to write a perfect methodology chapter to describe your work to the reader like how you did it. Dissertation methodology comes after the literature review when writing your dissertation, research project, or thesis. This section is crucial for demonstrating the validity and reliability of the research. Therefore, it should be accurate, clear, and precise.

According to the University of Wolverhampton, for an 8000 to 10,000 words dissertation, your methodology chapter should be 1500 to 2000 words long. We understand your worries that summarising your whole research work, whether it is quantitative or qualitative becomes difficult. In such circumstances, getting an expert’s advice is crucial to explaining your burning research questions of research methodology dissertation.

In this article, we will discuss all the key elements that you must consider to write a well-written dissertation methodology. Furthermore, getting assistance from dissertation writing services is also a good way to ensure your success. Their highly skilled team solve student’s queries and design their work in the most professional way.

What is Dissertation Methodology?

During the dissertation writing journey, after introducing your topic and describing the literature review, the stage of methodology writing comes. In this part, students describe each step they have taken to investigate and study a particular problem. Its main purpose is to explain how you designed your study and why you chose that approach.

The University of Southampton states that dissertation methodology covers everything from the research methods used in your dissertation to the decisions you made and challenges you encountered during the process. Students should mainly focus on this part because it sets the stage for what follows your results and discussion.

Why is Dissertation Methodology Important in a Research Project?

Dissertation methodology is important because it explains to the readers about how you did your research and why you chose it that way. Firstly, it shows your understanding of the method you selected which is crucial for the credibility of results. Secondly, it creates a smooth path for other people to use your methods of study for their own. By doing so, they would be able to compare the results which is an important factor in academic research.

Furthermore, your dissertation methodology explains the whole journey of data collection, sampling strategies, experimentation, and data analysis techniques. Explaining everything clearly helps people to trust the conclusions made from your work. In other words, it is like a roadmap that guides your readers about what you have done and achieved in your research work.

If this seems stressful, don’t worry – we’ll break down these methodological choices in detail in this post.

9 Key Elements to Include in Your Dissertation Methodology

Wondering about what are the key elements of a dissertation methodology? Well, the structure of the methodology includes several important points, such as:

• Introduction
• Research Design

Sampling Strategy

• Data Collection Methods
• Data Analysis Procedures
• Validity and Reliability
• Ethical Considerations
• Limitations

After getting an idea of the dissertation methodology structure, let’s now explore these essentials in detail.

Setting the Stage with Introduction

Just like starting everything with a brief introduction, the methodology also demands you to introduce your research aims and questions once again. You should remind your readers about what you are working on and what your aims are to accomplish from it. So, after describing it, you should just add a hint at the techniques you’ll be using during this whole procedure. In addition, if you really want to attract your reader’s attention, think about using an interesting starting sentence to create a hook.

Research design is of great importance in dissertation methodology as it describes the techniques, you’ll use to collect your data from different sources. Keep in mind that the techniques you select should directly answer your research questions. There are basically three types of research methods:

• Quantitative Research Method: This method uses numbers and statistics to collect and analyse the given data. It is very common in science subjects which use experiments, surveys, tests or already existing data to get a clear picture.
• Qualitative Research Method: It includes all non-numerical data and uses words and lengthy explanations to understand something in the dissertation methodology. For example, interviews, observations, and focus groups fall under this category and are commonly used in social science and theoretical humanities studies.
• Mixed Research Method: It is the combination of both above-mentioned methods. It mixes statistical data with a brief explanation of everything to provide a well-rounded picture of everything.

A sampling strategy is a method used to select an appropriate number of subjects from a wider population to study. In this step, you should describe the process you used to choose study participants or data sources. It includes sample size, process of selection and any sampling methods you are using. We mostly divide sampling strategies of dissertation methodology into two types:

• Probability Sampling: In this method, the group is chosen at random. Since each member of the population has a known probability of being selected, the results allow for more confident inferences about the entire group.
• Non-Probability Sampling: In this form, the group is chosen based on the researcher’s choice. Although it’s quicker and simpler, the results could not accurately reflect the full population.

While describing the research methodology for the dissertation, you need to explain how you collected your data to give more credibility to your work. To do so, students often conduct interviews and surveys, keenly observe everything related to their work, and go through a deep analysis of the collected data. Such as:

• Surveys and Questionnaires: Students conduct surveys and get the opinions of different people on a particular thing they are working on. Give an overview of the main features of your survey instrument, the sampling technique, and the survey medium.
• Interviews: Describe the format of the interview in your dissertation methodology. Also, talk about how you created the whole interview setup and how the participants were chosen.
• Observations: You should explain the observational context, data-gathering methods, and ethical issues if there are any.
• Analysis of Pre-existing Data: If you use already existing datasets, describe their source, the selection criteria, and any steps taken to clean the data.

Methods of Data Analysis

Data analysis techniques are the methods that students use during their research to analyse the data and interpret results from it. It helps them better understand the collected data and draw purposeful conclusions from it. There are various different types of methods that you can use in your dissertation methodology, including:

• Quantitative Methods: Give a brief description of the statistical instruments (such as hypothesis testing and descriptive statistics) that you will use to analyse your data.
• Qualitative Methods: Describe the methodology you plan to use to analyse qualitative data (e.g., grounded theory, theme analysis).

During this step, you should avoid using too much technical language so that a non-technical person can also understand your written work. So, you should explain the techniques in a way that is understandable to a general academic audience. In addition, don’t forget to add citations to the information you get from others because it is crucial to back up your claims.

Trust-Building Factors

To write a solid dissertation methodology, there is no need just to explain the positive aspects of your study. Rather, you should prioritise explaining every potential flaw or restriction in your research work. It shows that you have critically analysed everything, being a neutral researcher, which builds confidence in your research. So, along with discussing the plus points of your methodology, you should also cover any limitations or disadvantages as well.

• Advantages of Your Selected Strategies: You should discuss the benefits of the approaches you have chosen to answer your dissertation methodology research questions.
• Restrictions and Possible Flaws: Find out any potential flaws in your methodology which can be either in small sample size or self-reported data and talk about how to address them.
• Moral Aspects to Take into Account: You should also address any ethical issues that may arise from your data-gathering procedure. So, always prefer to get their permission to maintain work ethics.

At the end, you should summarise your whole dissertation methodology, including the main techniques you’ll use and how they relate to your study objectives. You should also discuss what were the circumstances when you conducted this study and how it went. After describing the methods, you can also give a hint about the next upcoming chapters to create suspense. If appropriate, you can also discuss a little about the methods of data analysis you’ll use in the following chapters.

At any step of dissertation writing, if you find something tough to work on, you can ask for dissertation help online from professionals in this field. Dissertation writers have all the expertise and knowledge to design your whole dissertation effectively including this methodology part.

Dissertation Methodology Examples

Before starting to write your own methodology chapter, you should first get an idea about it from different examples available on the Internet. It helps you to understand how to start and end it successfully and how to add some attractive visuals to explain each step. For example, in the thesis ”Quality Attribute Variability in Software Product Lines: Varying Performance and Security Purposefully”, the following visuals were added to explain the research design.

What are the 4 Steps of Research Methodology?

Research dissertation methodology is a wide chapter but if we summarise it into 4 steps, it would be:

• Creating a hypothesis or research questions
• Formulating your research design to conduct a study
• Describing your data collection methods
• Analysing and interpreting the data

What are the 7 Components of Research Methodology?

The following are the 7 main parts of the research methodology starting from the introduction and ending at the conclusion:

• Data Analysis Techniques
• Strengths and Limitations

What are the 4 Major Types of Research Methods?

There are many different methods by which you can conduct your research for dissertation methodology. Majorly, the 4 types of research methods are:

• Descriptive research
• Qualitative research
• Quantitative research
• Mixed research

Indeed, a well-written dissertation methodology is not everyone’s cup of tea that’s why many students search for a thorough guide to get assistance for it. Understanding your situation, we have built up this complete article on research methodology to help you ease your burden. By going through it, you will get to know everything from key elements to using effective methods and examples to perfectly write your methodology section.

This dissertation part is very time-consuming as well as demands your full focus on the subject. That’s why, most students buy dissertation online to save their time and as a result, earn top grades with expert assistance.

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Title: mean-field and cumulant approaches to modelling organic polariton physics.

Abstract: In this thesis we develop methods for many-body open quantum systems and apply them to systems of organic polaritons. The methods employ a mean-field approach to reduce the dimensionality of large-scale problems. Initially assuming the absence of correlations in the many-body state, this approach is built upon in two ways. First, we show how the mean-field approximation can be combined with matrix product operator methods to efficiently simulate the non-Markovian dynamics of a many-body system with strong coupling to multiple environments. We apply this method to calculate the threshold and photoluminescence for a realistic model of an organic laser. Second, we extend the mean-field description by systematically including higher-order correlations via cumulant expansions of the Heisenberg equations of motion. We investigate the validity and convergence properties of these expansions, both with respect to expansion order and system size, for many-body systems with many-to-one network structures. We then show how the cumulant expansions may be used to calculate spatially resolved dynamics of organic polaritons. This enables a study of organic polariton transport in which we observe reversible conversion to dark exciton states and sub-group-velocity propagation. The methods established in this work offer versatile tools for analysing large, many-body open quantum systems and investigating finite-size effects. Their application reveals the intricate dynamics of organic polaritons resulting from the interplay of strong light-matter coupling and vibrational effects.

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CS&E Announces 2024-25 Doctoral Dissertation Fellowship (DDF) Award Winners

Seven Ph.D. students working with CS&E professors have been named Doctoral Dissertation Fellows for the 2024-25 school year. The Doctoral Dissertation Fellowship is a highly competitive fellowship that gives the University’s most accomplished Ph.D. candidates an opportunity to devote full-time effort to an outstanding research project by providing time to finalize and write a dissertation during the fellowship year. The award includes a stipend of $25,000, tuition for up to 14 thesis credits each semester, and subsidized health insurance through the Graduate Assistant Health Plan.

CS&E congratulates the following students on this outstanding accomplishment:

• Athanasios Bacharis (Advisor: Nikolaos Papanikolopoulos )
• Karin de Langis (Advisor:  Dongyeop Kang )
• Arshia Zernab Hassan (Advisors: Chad Myers )
• Xinyue Hu (Advisors: Zhi-Li Zhang )
• Lucas Kramer (Advisors: Eric Van Wyk )
• Yijun Lin (Advisors: Yao-Yi Chiang )
• Mingzhou Yang (Advisors: Shashi Shekhar )

Athanasios Bacharis

Bacharis’ work centers around the robot-vision area, focusing on making autonomous robots act on visual information. His research includes active vision approaches, namely, view planning and next-best-view, to tackle the problem of 3D reconstruction via different optimization frameworks. The acquisition of 3D information is crucial for automating tasks, and active vision methods obtain it via optimal inference. Areas of impact include agriculture and healthcare, where 3D models can lead to reduced use of fertilizers via phenotype analysis of crops and effective management of cancer treatments. Bacharis has a strong publication record, with two peer-reviewed conference papers and one journal paper already published. He also has one conference paper under review and two journal papers in the submission process. His publications are featured in prestigious robotic and automation venues, further demonstrating his expertise and the relevance of his research in the field.

Karin de Langis

Karin's thesis works at the intersection of Natural Language Processing (NLP) and cognitive science. Her work uses eye-tracking and other cognitive signals to improve NLP systems in their performance and cognitive interpretability, and to create NLP systems that process language more similarly to humans. Her human-centric approach to NLP is motivated by the possibility of addressing the shortcomings of current statistics-based NLP systems, which often become stuck on explainability and interpretability, resulting in potential biases. This work has most recently been accepted and presented at SIGNLL Conference on Computational Natural Language Learning (CoNLL) conference which has a special focus on theoretically, cognitively and scientifically motivated approaches to computational linguistics.

Arshia Zernab Hassan

Hassan's thesis work delves into developing computational methods for interpreting data from genome wide CRISPR/Cas9 screens. CRISPR/Cas9 is a new approach for genome editing that enables precise, large-scale editing of genomes and construction of mutants in human cells. These are powerful data for inferring functional relationships among genes essential for cancer growth. Moreover, chemical-genetic CRISPR screens, where population of mutant cells are grown in the presence of chemical compounds, help us understand the effect the chemicals have on cancer cells and formulate precise drug solutions. Given the novelty of these experimental technologies, computational methods to process and interpret the resulting data and accurately quantify the various genetic interactions are still quite limited, and this is where Hassan’s dissertation is focused on. Her research extends to developing deep-learning based methods that leverage CRISPR chemical-genetic and other genomic datasets to predict cancer sensitivity to candidate drugs. Her methods on improving information content in CRISPR screens was published in the Molecular Systems Biology journal, a highly visible journal in the computational biology field. 

Hu's Ph.D. dissertation is concentrated on how to effectively leverage the power of artificial intelligence and machine learning (AI/ML) – especially deep learning – to tackle challenging and important problems in the design and development of reliable, effective and secure (independent) physical infrastructure networks. More specifically, her research focuses on two critical infrastructures: power grids and communication networks, in particular, emerging 5G networks, both of which not only play a critical role in our daily life but are also vital to the nation’s economic well-being and security. Due to the enormous complexity, diversity, and scale of these two infrastructures, traditional approaches based on (simplified) theoretical models and heuristics-based optimization are no longer sufficient in overcoming many technical challenges in the design and operations of these infrastructures: data-driven machine learning approaches have become increasingly essential. The key question now is: how does one leverage the power of AI/ML without abandoning the rich theory and practical expertise that have accumulated over the years? Hu’s research has pioneered a new paradigm – (domain) knowledge-guided machine learning (KGML) – in tackling challenging and important problems in power grid and communications (e.g., 5G) network infrastructures.

Lucas Kramer

Kramer is now the driving force in designing tools and techniques for building extensible programming languages, with the Minnesota Extensible Language Tools (MELT) group. These are languages that start with a host language such as C or Java, but can then be extended with new syntax (notations) and new semantics (e.g. error-checking analyses or optimizations) over that new syntax and the original host language syntax. One extension that Kramer created was to embed the domain-specific language Halide in MELT's extensible specification of C, called ableC. This extension allows programmers to specify how code working on multi-dimensional matrices is transformed and optimized to make efficient use of hardware. Another embeds the logic-programming language Prolog into ableC; yet another provides a form of nondeterministic parallelism useful in some algorithms that search for a solution in a structured, but very large, search space. The goal of his research is to make building language extensions such as these more practical for non-expert developers.  To this end he has made many significant contributions to the MELT group's Silver meta-language, making it easier for extension developers to correctly specify complex language features with minimal boilerplate. Kramer is the lead author of one journal and four conference papers on his work at the University of Minnesota, winning the distinguished paper award for his 2020 paper at the Software Language Engineering conference, "Strategic Tree Rewriting in Attribute Grammars".

Lin’s doctoral dissertation focuses on a timely, important topic of spatiotemporal prediction and forecasting using multimodal and multiscale data. Spatiotemporal prediction and forecasting are important scientific problems applicable to diverse phenomena, such as air quality, ambient noise, traffic conditions, and meteorology. Her work also couples the resulting prediction and forecasting with multimodal (e.g., satellite imagery, street-view photos, census records, and human mobility data) and multiscale geographic information (e.g., census records focusing on small tracts vs. neighborhood surveys) to characterize the natural and built environment, facilitating our understanding of the interactions between and within human social systems and the ecosystem. Her work has a wide-reaching impact across multiple domains such as smart cities, urban planning, policymaking, and public health.

Mingzhou Yang

Yang is developing a thesis in the broad area of spatial data mining for problems in transportation. His thesis has both societal and theoretical significance. Societally, climate change is a grand challenge due to the increasing severity and frequency of climate-related disasters such as wildfires, floods, droughts, etc. Thus, many nations are aiming at carbon neutrality (also called net zero) by mid-century to avert the worst impacts of global warming. Improving energy efficiency and reducing toxic emissions in transportation is important because transportation accounts for the vast majority of U.S. petroleum consumption as well as over a third of GHG emissions and over a hundred thousand U.S. deaths annually via air pollution. To accurately quantify the expected environmental cost of vehicles during real-world driving, Yang's thesis explores ways to incorporate physics in the neural network architecture complementing other methods of integration: feature incorporation, and regularization. This approach imposes stringent physical constraints on the neural network model, guaranteeing that its outputs are consistently in accordance with established physical laws for vehicles. Extensive experiments including ablation studies demonstrated the efficacy of incorporating physics into the model. 

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• Published: 15 May 2024

Arresting failure propagation in buildings through collapse isolation

• Nirvan Makoond   ORCID: orcid.org/0000-0002-5203-6318 1 ,
• Andri Setiawan   ORCID: orcid.org/0000-0003-2791-6118 1 ,
• Manuel Buitrago   ORCID: orcid.org/0000-0002-5561-5104 1 &
• Jose M. Adam   ORCID: orcid.org/0000-0002-9205-8458 1  

Nature volume  629 ,  pages 592–596 ( 2024 ) Cite this article

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• Civil engineering
• Mechanical engineering

Several catastrophic building collapses 1 , 2 , 3 , 4 , 5 occur because of the propagation of local-initial failures 6 , 7 . Current design methods attempt to completely prevent collapse after initial failures by improving connectivity between building components. These measures ensure that the loads supported by the failed components are redistributed to the rest of the structural system 8 , 9 . However, increased connectivity can contribute to collapsing elements pulling down parts of a building that would otherwise be unaffected 10 . This risk is particularly important when large initial failures occur, as tends to be the case in the most disastrous collapses 6 . Here we present an original design approach to arrest collapse propagation after major initial failures. When a collapse initiates, the approach ensures that specific elements fail before the failure of the most critical components for global stability. The structural system thus separates into different parts and isolates collapse when its propagation would otherwise be inevitable. The effectiveness of the approach is proved through unique experimental tests on a purposely built full-scale building. We also demonstrate that large initial failures would lead to total collapse of the test building if increased connectivity was implemented as recommended by present guidelines. Our proposed approach enables incorporating a last line of defence for more resilient buildings.

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Disasters recorded from 2000 to 2019 are estimated to have caused economic losses of US$2.97 trillion and claimed approximately 1.23 million lives 11 . Most of these losses can be attributed to building collapses 12 , which are often characterized by the propagation of local-initial failures 13 that can arise because of extreme or abnormal events such as earthquakes 13 , 14 , 15 , 16 , floods 17 , 18 , 19 , 20 , storms 21 , 22 , landslides 23 , 24 , explosions 25 , vehicle impacts 26 and even construction or design errors 6 , 26 . As the world faces increasing trends in the frequency and intensity of extreme events 27 , 28 , it is arguably now more important than ever to design robust structures that are insensitive to initial damage 13 , 29 , irrespective of the underlying threat causing it.

Most robustness design approaches used at present 8 , 9 , 30 , 31 aim to completely prevent collapse initiation after a local failure by providing extensive connectivity within a structural system. Although these measures can ensure that the load supported by a failed component is redistributed to the rest of the structure, they are neither viable nor sustainable when considering larger initial failures 13 , 25 , 32 . In these situations, the implementation of these approaches can even result in collapsing parts of the building pulling down the rest of the structure 10 . The fact that several major collapses have occurred because of large initial failures 6 raises serious concerns about the inadequacy of the current robustness measures.

Traditionally, research in this area has focused on preventing collapse initiation after initial failures rather than on preventing collapse propagation. This trend dates back to the first impactful studies in the field of structural robustness, which were performed after a lack of connectivity enabled the progressive collapse of part of the Ronan Point tower in 1968 (ref.  33 ). Although completely preventing any collapse is certainly preferable to limiting the extent of a collapse, the occurrence of unforeseeable incidents is inevitable 34 and major building collapses keep occurring 1 , 2 , 3 .

Here we present an original approach for designing buildings to isolate the collapse triggered by a large initial failure. The approach, which is based on controlling the hierarchy of failures in a structural system, is inspired by how lizards shed their tails to escape predators 35 . The proposed hierarchy-based collapse isolation design ensures sufficient connectivity for operational conditions and after local-initial failures for which collapse initiation can be completely prevented through load redistribution. These local-initial failures can even be greater than those considered by building codes. Simultaneously, the structural system is also designed to separate into different parts and isolate a collapse when its propagation would otherwise be inevitable. As in the case of lizard tail autotomy 35 , this is achieved by promoting controlled fracture along predefined segment borders to limit failure propagation. In this work, hierarchy-based collapse isolation is applied to framed building structures. Developing this approach required a precise characterization of the collapse propagation mechanisms that need to be controlled. This was achieved using computational simulations that were validated through a specifically designed partial collapse test of a full-scale building. The obtained results demonstrate the viability of incorporating hierarchy-based collapse isolation in building design.

Hierarchy-based collapse isolation

Hierarchy-based collapse isolation design makes an important distinction between two types of initial failures. The first, referred to as small initial failures, includes all failures for which it is feasible to completely prevent the initiation of collapse by redistributing loads to the remaining structural system. The second type of initial failure, referred to as large initial failures, includes more severe failures that inevitably trigger at least a partial collapse.

The proposed design approach aims to (1) arrest unimpeded collapse propagation caused by large initial failures and (2) ensure the ability of a building to develop alternative load paths (ALPs) to prevent collapse initiation after small initial failures. This is achieved by prioritizing a specific hierarchy of failures among the components on the boundary of a moving collapse front.

Buildings are complex three-dimensional structural systems consisting of different components with very specific functions for transferring loads to the ground. Among these, vertical load-bearing components such as columns are the most important for ensuring global structural stability and integrity. Therefore, hierarchy-based collapse isolation design prevents the successive failure of columns, which would otherwise lead to catastrophic collapse. Although the exact magnitude of dynamic forces transmitted to columns during a collapse process is difficult to predict, these forces are eventually limited by the connections between columns and floor systems. In the proposed approach, partial-strength connections are designed to limit the magnitude of transmitted forces to values that are lower than the capacity of columns to resist unbalanced forces (see section ‘ Building design ’). This requirement guarantees a specific hierarchy of failures during collapse, whereby connection failures always occur before column failures. As a result, the collapse following a large initial failure is always restricted to components immediately adjacent to those directly involved in the initial failure. However, it is still necessary to ensure a lower bound on connection strengths to activate ALPs after small initial failures. Therefore, cost-effective implementation of hierarchy-based collapse isolation design requires finding an optimal balance between reducing the strength of connections and increasing the capacity of columns.

To test and verify the application of our proposed approach, we designed a real 15 m × 12 m precast reinforced concrete building with two 2.6-m-high floors. This basic geometry represents a building size that can be built and tested at full-scale while still being representative of current practices in the construction sector. The structural type was selected because of the increasing use of prefabricated construction for erecting high-occupancy buildings such as hospitals and malls because of several advantages in terms of quality, efficiency and sustainability 36 .

The collapse behaviour of possible design options (Extended Data Fig. 1 ) subjected to both small and large initial failures was investigated using high-fidelity collapse simulations (Fig. 1 ) based on the applied element method (AEM; see section ‘ Modelling strategy ’). The ability of these simulations to accurately represent collapse phenomena for the type of building being studied was later validated by comparing its predictions to the structural response observed during a purposely designed collapse test of a full-scale building (Extended Data Fig. 2 and Supplementary Video  7 ).

a , Partial-strength beam–column connection optimized for hierarchy-based collapse isolation. b , Partial collapse of a building designed for hierarchy-based collapse isolation (design H) after the loss of a corner column and two penultimate-edge columns. c , Total collapse of conventional building design (design C) after the same large initial failure scenario.

Following the preliminary design of a structure to resist loads suitable for office buildings, two building design options considering different robustness criteria were further investigated (see section ‘ Building design ’). The first option, design H (hierarchy-based), uses optimized partial-strength connections and enhanced columns (Fig. 1a ) to fulfil the requirements of hierarchy-based collapse isolation design. The second option, design C (conventional), is strictly based on code requirements and provides a benchmark comparison for evaluating the effectiveness of the proposed approach. It uses full-strength connections to improve robustness as recommended in current guidelines 37 and building codes 8 , 9 .

Simulations predicted that both design H and design C could develop stable ALPs that are able to completely prevent the initiation of collapse after small initial failure scenarios that are more severe than those considered in building codes 8 , 9 (Extended Data Fig. 3 ).

When subjected to a larger initial failure, simulations predict that design H can isolate the collapse to only the region directly affected by the initial failure (Fig. 1b ). By contrast, design C, with increased connectivity, causes collapsing elements to pull down the rest of the structure, leading to total collapse (Fig. 1c ). These two distinct outcomes demonstrate that the prevention of unimpeded collapse propagation can only be ensured when hierarchy-based collapse isolation is implemented (Extended Data Fig. 4 and Supplementary Video  1 ).

Testing a full-scale precast building

To confirm the expected performance improvement that can be achieved with the hierarchy-based collapse isolation design, a full-scale building specimen corresponding to design H was purposely built and subjected to two phases of testing as part of this work (Fig. 2a and Supplementary Information  Sections 1 and 2 ). The precast structure was constructed with continuous columns cast together with corbels (Supplementary Video  4 ). The columns were cast with prepared dowel bars and sleeves for placing continuous top beam reinforcement bars through columns (Fig. 2b,c ). The bars used for these two types of reinforcing element (Fig. 1a ) were specifically selected to produce partial-strength connections. These connections are strong enough for the development of ALPs after small initial failures but weak enough to enable hierarchy-based collapse isolation after large initial failures.

a , Full-scale precast concrete structure and columns removed in different testing phases. The label used for each column is shown. The location of beams connecting the different columns is indicated by the dotted lines above the second-floor level. The expected collapse area in the second phase of testing is indicated. b , Typical first-floor connection before placement of beams during construction. c , Typical second-floor connection after placement of precast beams during construction. Both b and c show columns with two straight precast beams on either side (C2, C3, C6, C7, C10 and C11). d , Device used for quasi-static removal of two columns in the first phase of testing. e , Three-hinged mechanism used for dynamic removal of corner column in the second phase of testing.

After investigating different column-removal scenarios from different regions of the test building (see section ‘ Experiment and monitoring design ’, Extended Data Fig. 5 and Supplementary Video  2 ), two phases of testing were defined to capture relevant collapse-related phenomena and validate the effectiveness of hierarchy-based collapse isolation. Separating the test into two phases allowed two different aspects to be analysed: (1) the prevention of collapse initiation after small initial failures and (2) the isolation of collapse after large initial failures.

Phase 1 involved the quasi-static removal of two penultimate-edge columns using specifically designed removable supports (Fig. 2d and Extended Data Fig. 6 ). This testing phase corresponds to a small initial failure scenario for which design H was able to develop ALPs to prevent collapse initiation. Phase 2 reproduced a large initial failure through the dynamic removal of the corner column found between the two previously removed columns using a three-hinged collapsible column (Fig. 2e ).

During both testing phases, a distributed load (11.8 kN m −2 ) corresponding to almost twice the magnitude specified in Eurocodes 38 for accidental design situations (6 kN m −2 ) was imposed on bays expected to collapse in phase 2 (Fig. 2a and Supplementary Video  5 ). Predictive simulations indicated that the failure mode and overall collapse would be almost identical when comparing this partial loading configuration with that in which the entire building is loaded (Supplementary Video  3 ). However, the partial loading configuration turns out to be more demanding for the part of the structure expected to remain upright as evidenced by the greater drifts it produces during collapse (see section ‘ Experiment and monitoring design ’ and Extended Data Fig. 7 ). The structural response during all phases of testing was extensively monitored with an array of different sensors (see section ‘ Experiment and monitoring design ’ and Supplementary Information Section 3 ) that provided the information used as a basis for the analyses presented in the following sections.

Preventing collapse initiation

Collapse initiation was completely prevented after the removal of two penultimate-edge columns in phase 1 of testing (Fig. 3a ), demonstrating that design H complies with the robustness requirements included in current building standards 8 , 9 , 39 . As this initial failure scenario is more severe than those considered by standardized design methods 8 , 9 , 30 , it represents an extreme case for which ALPs are still effective. As such, the outcome of phase 1 demonstrates that implementing hierarchy-based collapse isolation design does not impair the ability of this structure to prevent collapse initiation.

a , Test building during phase 1 of testing after removal of columns C8 and C11. The beam depth ( h ) used to compute the ratio plotted in b is shown and the location of the strain measurement plotted in c is indicated. b , Evolution of beam deflection expressed as a ratio of beam depth at the location of removed column C11. The chord rotation of the beams bridging over this removed column is also indicated using a secondary vertical axis. c , Strain increase in continuity reinforcement in the second-floor beam between C12 and C11.

Source Data

Analysis of the structural response during phase 1 (Supplementary Information Section 4 ) shows that collapse was prevented because of the redistribution of loads through the beams (Fig. 3b,c ), columns (Extended Data Fig. 8 ) and slabs (Supplementary Report 4 ) adjacent to the removed columns. The beams bridging over the removed columns sustained loads through flexural action, as evidenced by the magnitude of the vertical displacement recorded at the removal locations (Fig. 3b ). These values were far too small to allow the development of catenary forces, which only begin to appear when displacements exceed the depth of the beam 40 .

The flexural response of the structure after the loss of two penultimate-edge columns was only able to develop because of the specific reinforcement detailing introduced in the design. This was verified by the increase in tensile strains recorded in the continuous beam reinforcement close to the removed column (Fig. 3c ) and in ties placed between the precast hollow-core planks in the floor system close to column C7 (Supplementary Information Section 4 ). The latter also proves that the slabs contributed notably to load redistribution after column removal.

In general, the structure experienced only small movements and suffered very little permanent damage during phase 1 (Supplementary Information Section 4 ), despite the high imposed loads used for testing. The only reinforcement bars showing some signs of yielding were the continuous reinforcement bars of beams close to the removed columns (Fig. 3c ).

Arresting collapse propagation

Following the removal of two penultimate-edge columns in phase 1, the sudden removal of the C12 corner column in phase 2 triggered a collapse that was arrested along the border delineated by columns C3, C7, C6 and C10 (Fig. 4a–d and Supplementary Video  6 ). Thus, the viability of hierarchy-based collapse isolation design is confirmed.

a , Collapse sequence during phase 2 of testing. b , Partial collapse of full-scale test building (design H) after the removal of three columns. The segment border in which collapse propagation was arrested is indicated. The axes shown at column C9 correspond to those used in f to indicate the changing direction of the resultant drift measured at this location. c , Failure of beam–column connections at collapse border. d , Debonding of reinforcement in the floor at collapse border. e , Change in average axial strains measured in column C7. A negative change represents an increase in compressive strains. f , Magnitude of resultant drift measured at C9. g , Change in direction of resultant drift measured at C9. The initial drift after phase 1 of testing and the residual drift after the upright part of the building stabilized are also shown in the plot.

During the initial stages following the removal of C12, the collapsing bays next to this column pulled up the columns on the opposite corner of the building (columns C1, C3 and C6). During this process, column C7 behaves like a pivot point, experiencing a significant increase in compressive forces (Fig. 4e and Supplementary Information Section 5 ). This phenomenon was enabled by the connectivity between collapsing parts and the rest of the structure. If allowed to continue, this could have led to successive column failures and unimpeded collapse propagation. However, during the test, the rupture of continuous reinforcement bars (Fig. 4c ) occurred as the connections failed and halted the transmission of forces to columns. These connection failures occurred before any column failures, as intended by the hierarchy-based collapse isolation design of the structural system. Specifically, this type of connection failure occurred at the junctions with the two columns (C7 and C10) immediately adjacent to the failure origin (around C8, C11 and C12), effectively segmenting the structure along the border shown in Fig. 4b . Segmentation along this border was completed by the total separation of the floor system, which was enabled by the debonding of slab reinforcements at the segment border (Fig. 4d and Supplementary Video  8 ).

Observing the building drift measured at the top of column C9 (Fig. 4f ) enabled us to better understand the nature of forces acting on the building further away from the collapsing region. The initial motion shows the direction of pulling forces generated by the collapsing elements (Fig. 4g ). This drift peaks very shortly after the point in time when separation of the collapsing parts occurs (Fig. 4f ). After this peak, the upright part of the structure recoiled backwards and experienced an attenuated oscillatory motion before finding a new stable equilibrium (Fig. 4g ). The magnitude of the measured peak drift is comparable to the drift limits considered in seismic regions when designing against earthquakes with a 2,500-year return period 41 (Supplementary Information Section 5 ). This indicates that the upright part of the structure was subjected to strong dynamic horizontal forces as it was effectively tugged by the collapsing elements falling to the ground. The building would have failed because of these unbalanced forces had hierarchy-based collapse isolation design not been implemented.

The upright building segment suffered permanent damages as evidenced by the residual drift recorded at the top of column C9 (Fig. 4g ). This is further corroborated by the fact that several reinforcement bars in this part of the structure yielded, particularly in areas close to the segment border (Supplementary Report 5 ). Despite the observed level of damage, safe evacuation and rescue of people from this building segment would still be possible after an extreme event, saving lives that would have been lost had a more conventional robustness design (design C) been used instead.

Discussion and future outlook

Our results demonstrate that the extensive connectivity adopted in conventional robustness design can lead to catastrophic collapse after large initial failures. To address this risk, we have developed and tested a collapse isolation design approach based on controlling the hierarchy of failures occurring during the collapse. Specifically, it is ensured that connection failures occur before column failures, mitigating the risk of collapse propagation throughout the rest of the structural system. The proposed approach has been validated through the partial collapse test of a full-scale precast building, showing that propagating collapses can be arrested at low cost without impairing the ability of the structure to completely prevent collapse initiation after small initial failures.

The reported findings show a last line of defence against major building collapses due to extreme events. This paves the way for the proposed solution to be developed, tested and implemented in different building types with different building elements. This discovery opens opportunities for robustness design that will lead to a new generation of solutions for avoiding catastrophic building collapses.

Building design

Our hierarchy-based collapse isolation approach ensures buildings have sufficient connectivity for operational conditions and small initial failures, yet separate into different parts and isolate a collapse after large initial failures. We chose a precast construction as our main structural system for our case study. A notable particularity of precast systems compared with cast-in-place buildings is that the required construction details can be implemented more precisely. We designed and systematically investigated two precast building designs: designs H and C.

Design H is our building design in which the hierarchy-based collapse isolation approach is applied. Design H was achieved after several preliminary iterations by evaluating various connections and construction details commonly adopted in precast structures. The final design comprises precast columns with corbels connected to a floor system (partially precast beams and hollow-core slabs) through partial-strength beam–column connections (Extended Data Fig. 1 and Supplementary Information Section 1 ). This partial-strength connection was achieved by (1) connecting the bottom part of the beam (precast) to optimally designed dowel bars anchored to the column corbels and (2) passing continuous top beam bars through the columns. With this partial-strength connection, we have more direct control over the magnitude of forces being transferred from the floor system to the columns, which is a key aspect for achieving hierarchy-based collapse isolation. The hierarchy of failures was initially implemented through the beam–column connections (local level) and later verified at the system (global) level.

At the local level, three main components are designed according to the hierarchy-based concept: (1) top continuity bars of the beams; (2) dowel bars connecting beams to corbels; and (3) columns.

Top continuity bars of beams: To allow the structural system to redistribute the loads after small initial failures, top reinforcement bars in all beams were specifically designed to fulfil structural robustness requirements (Extended Data Fig. 3 ). Particularly, we adopted the prescriptive tying rules (referred to as Tie Forces) of UFC 4-023-03 (ref.  9 ) to perform the design of the ties. The required tie strength F i in both the longitudinal and transverse directions for the internal beams is expressed as

For the peripheral beams, the required tie strength F P is expressed as

where  w F  = floor load (in kN m −2 );  D  = dead load (in kN m −2 );  L  = live load (in kN m −2 );  L 1  = greater of the distances between the centres of the columns, frames or walls supporting any two adjacent floor spaces in the direction under consideration (in m);  L P  = 1.0 m; and  W C  = 1.2 times dead load of cladding (neglected in this design).

These required tie strengths are fulfilled with three bars (20 mm diameter) for the peripheral beams and three bars (25 mm diameter) for the internal beams. These required reinforcement dimensions were implemented through the top bars of the beam and installed continuously (lap-spliced, internally, and anchored with couplers at the ends) throughout the building (Extended Data Fig. 1 ).

Dowel bars connecting the beam and corbel of the column: The design of the dowel bars is one of the key aspects in achieving partial-strength connections that fail at a specific threshold to enable segmentation. These dowel bars would control the magnitude of the internal forces between the floor system and column while allowing for some degree of rotational movement. The dowels were designed to resist possible failure modes using expressions proposed in the fib guidelines 37 . Several possible failure modes were checked: splitting of concrete around the dowel bars, shear failure of the dowel bars and forming a plastic hinge in the dowel. The shear capacity of a dowel bar loaded in pure shear can be determined according to the Von Mises yield criterion:

where f yd is the design yield strength of the dowel bar and A s is the cross-sectional area of the dowel bar. In case of concrete splitting failure, the highly concentrated reaction transferred from the dowel bar shall be designed to be safely spread to the surrounding concrete. The strut and tie method is recommended to perform such a design 42 . If shear failure and splitting of concrete do not occur prematurely, the dowel bar will normally yield in bending, indicated by the formation of a plastic hinge. This failure mode is associated with a significant tensile strain at the plastic hinge location of the dowel bar and the crushing of concrete around the compression part of the dowel. The shear resistance achieved at this state for dowel (ribbed) bars across a joint of a certain width (that is, the neoprene bearing) can be expressed as

where α 0 is a coefficient that considers the bearing strength of concrete and can be taken as 1.0 for design purposes, α e is a coefficient that considers the eccentricity, e is the load eccentricity and shall be computed as the half of the joint width (half of the neoprene bearing thickness), Φ and A s are the diameter and the cross-sectional area of the dowel bar, respectively, f cd,max is the design concrete compressive strength at the stronger side, σ sn is the local axial stress of the dowel bar at the interface location, \({f}_{{\rm{yd}},{\rm{red}}}={f}_{{\rm{yd}}}-{\sigma }_{{\rm{sn}}}\) is the design yield strength available for dowel action, f yd is the yield strength of the dowel bar and μ is the coefficient of friction between the concrete and neoprene bearing. By performing the checks on these three possible failure modes, we selected the final (optimum) design with a two dowel bars (20 mm diameter) configuration.

Columns: The proposed hierarchy-based approach requires columns to have adequate capacity to resist the internal forces transmitted by the floor system during a collapse. By fulfilling this strength hierarchy, we can ensure and control that failure happens at the connections first before the columns fail, thus preventing collapse propagation. The columns were initially designed according to the general procedure prescribed by building standards. Then, the resulting capacity was verified using the modified compression field theory (MCFT) 43 to ensure that it was higher than the maximum expected forces transmitted by the connection to the floor system. MCFT was derived to consistently fulfil three main aspects: equilibrium of forces, compatibility and rational stress–strain relationships of cracked concrete expressed as average stresses and strains. The principal compressive stress in the concrete f c 2 is expressed not only as a function of the principal compressive strain ε 2 but also of the co-existing principal tensile strain ε 1 , known as the compression softening effect:

where f c 2max is the peak concrete compressive strength considering the perpendicular tensile strain, \({f}_{c}^{{\prime} }\) is the uniaxial compressive strength, and \({\varepsilon }_{{c}^{{\prime} }}\) is the peak uniaxial concrete compressive strain and can be taken as −0.002. In tension, concrete is assumed to behave linearly until the tensile strength is achieved, followed by a specific decaying function 43 . Regarding aggregate interlock, the shear stress that can be transmitted across cracks v ci is expressed as a function of the crack width w , and the required compressive stress on the crack f ci (ref.  44 ):

where a refers to the maximum aggregate size in mm and the stresses are expressed in MPa. The MCFT analytical model was implemented to solve the sectional and full-member response of beams and columns subjected to axial, bending and shear in Response 2000 software (open access) 45 , 46 . In Response 2000, we input key information, including the geometries of the columns, reinforcement configuration and the material definition for the concrete and the reinforcing bars. Based on this information, we computed the M – V (moment and shear interaction envelope) and M – N (moment and axial interaction envelope) diagrams that represent the capacity of the columns. The results shown in Extended Data Fig. 4 about the verification of the demand and capacity envelopes were obtained using the analytical procedure described here.

At the global level, the initially collapsing regions of the building generate a significant magnitude of dynamic unbalanced forces. The rest of the building system must collectively resist these unbalanced forces to achieve a new equilibrium state. Depending on the design of the structure, this phenomenon can lead to two possible scenarios: (1) major collapse due to failure propagation or (2) partial collapse only of the initially affected regions. The complex interaction between the three-dimensional structural system and its components must be accounted for to evaluate the structural response during collapse accurately. Advanced computational simulations, described in the ‘ Modelling strategy ’ section, were adopted to analyse the global building to verify that major collapse can be prevented. The final design obtained from the local-level analysis (top continuity bars, dowel bars and columns) was used as an input for performing the global computational simulations. Certain large initial failures deemed suitable for evaluating the performance of this building were simulated. In case failure propagation occurs, the original hierarchy-based design must be further adapted. An iterative process is typically required involving several simulations with various building designs to achieve an optimum result that balances the cost and desired collapse performance. The final iteration of design H, which fulfils both the local and global hierarchy checks, is provided in Extended Data Fig. 1 .

Design C is a conventional building design that complies with current robustness standards but does not explicitly fulfil our hierarchy-based approach. The same continuity bars used in design H were used in design C. We adopted a full-strength connection as recommended by the fib guideline 37 . The guideline promotes full connectivity to enhance the development of alternative load paths for preventing collapse initiation. In design C, we used a two dowel bars (32 mm diameter) configuration to ensure full connectivity when the beams are working at their maximum flexural capacity. Another main difference was that the columns in design C were designed according to codes and current practice (optimal solution) without explicitly checking that hierarchy-based collapse isolation criteria are fulfilled. The final design of the columns and connections adopted in design C is provided in Extended Data Fig. 1 .

Modelling strategy

We used the AEM implemented in the Extreme Loading for Structures software to perform all the computational simulations presented in this study 47 (Extended Data Figs. 2 – 5 and 7 and Supplementary Videos  1 , 2 , 3 and 7 ). We chose the AEM for its ability to represent all phases of a structural collapse efficiently and accurately, including element separation (fracture), contact and collision 47 . The method discretizes a continuum into small, finite-size elements (rigid bodies) connected using multiple normal and shear springs distributed across each element face. Each element has six degrees of freedom, three translational and three rotational, at its centre, whereas the behaviour of the springs represents all material constitutive models, contact and collision response. Despite the simplifying assumptions in its formulation 48 , its ability to accurately account for large displacements 49 , cyclic loading 50 , as well as the effects of element separation, contact and collision 51 has been demonstrated through many comparisons with experimental and theoretical results 47 .

Geometric and physical representations

We modelled each of the main structural components of the building separately, including the columns, beams, corbels and hollow-core slabs. We adopted a consistent mesh size with an average (representative) size of 150 mm. Adopting this mesh configuration resulted in a total number of 98,611 elements. We defined a specialized interface with no tensile or shear strength between the precast and cast-in-situ parts to allow for localized deformations that occur at these locations. The behaviour of the interface was mainly governed by a friction coefficient of 0.6, which was defined according to concrete design guidelines 52 , 53 , 54 . The normal stiffness of these interfaces corresponded to the stiffness of the concrete cast-in-situ topping. The elastomeric bearing pads supporting the precast beams on top of the corbels were also modelled with a similar interface having a coefficient of friction of 0.5 (ref.  55 ).

Element type and constitutive models

We adopted an eight-node hexahedron (cube) element with the so-called matrix-springs connecting adjacent cubes to model the concrete parts. We adopted the compression model in refs.  56 , 57 to simulate the behaviour of concrete under compression. Three specific parameters are required to define the response envelope: the initial elastic modulus, the fracture parameter and the compressive plastic strain. For the behaviour in tension, the spring stiffness is assumed to be linear (with the initial elastic modulus) until reaching the cracking point. The shear behaviour is considered to remain linear up to the cracking of the concrete. The interaction between normal compressive and shear stress follows the Mohr–Coulomb failure criterion. After reaching the peak, the shear stress is assumed to drop to a certain residual value affected by the aggregate interlock and friction at the cracked surface. By contrast, under tension, both normal and shear stresses drop to zero after the cracking point. The steel reinforcement bars were simulated as a discrete spring element with three force components: the normal spring takes the principal/normal forces parallel to the rebar, and two other springs represent the reinforcement bar in shear (dowelling). Three distinct stages are considered: elastic, yield plateau and strain hardening. A perfect bond behaviour between the concrete and the reinforcement bars was adopted. We assigned the material properties based on the results of the laboratory tests performed on reinforcement bars and concrete cylinders (Supplementary Information Section 2 ).

Boundary conditions and loading protocol

We assumed that all the ground floor columns are fully restrained in all six degrees of freedom at the base location. This assumption is reasonable, as we expected that the footing would provide sufficient rigidity to constrain any significant deformations. We assigned the reflecting domain boundaries to allow a realistic representation of the collapsing elements (debris) that might fall and rebound after hitting the ground. The ground level was assumed to be at the same elevation at which the column bases are restrained. We applied the additional imposed uniform distributed load as an extra volume of mass assigned to the slabs. To perform the column removal, we used the element removal feature that allows some specific designated elements to be immediately removed at the beginning of the loading stage. This represents a dynamic (sudden) removal, as we expected from the actual test.

Extended Data Tables 1 and 2 summarize all key parameters and assumptions adopted in the modelling process. To validate these assumptions for simulating the precast building designs described previously, it was ensured that the full-scale test performed as part of this work captured all relevant phenomena influencing collapse (large displacements, fracture, contact and collision).

Experiment and monitoring design

We used computational simulations of design H subjected to different initial failure scenarios to define a suitable testing sequence and protocol. The geometry, reinforcement configurations, connection system and construction details of the purpose-built specimen representing design H are provided in Supplementary Information Section 1 and Supplementary Video  4 .

Initial failure scenarios

Initial failure scenarios occurring in edge and corner regions of the building were prioritized for this study because they are usually exposed to a wider range of external threats 58 , 59 , 60 , 61 . After performing a systematic sensitivity study, we identified three critical scenarios (Extended Data Fig. 5 and Supplementary Video  2 ):

Scenario 1: a scenario involving a two-column failure—a corner column and the adjacent edge column. We determined that the required gravity loads to induce collapse equal 11.5 kN m −2 and that partial collapse would occur locally.

Scenario 2: a scenario involving a three-column failure—two corner columns and the edge column in between the two corner columns. We determined that the required gravity loads to induce collapse equal 8.5 kN m −2 and that segmentation (partially collapsing two bays) would take place only across one principal axis of the building.

Scenario 3: a scenario involving a three-column failure: one corner column and two edge columns on both sides of the corner column. We determined that the required gravity loads to induce collapse equal 7.0 kN m −2 and that segmentation (partially collapsing three bays) would take place across both principal axes of the building.

Scenario 3 was ultimately chosen after considering three main aspects: (1) it requires the lowest gravity loads to trigger partial collapse; (2) the failure mode involves activating segmentation mechanisms in two principal axes of the building (more realistic collapse pattern); and (3) the ratio of the area of the intact part and the collapsed part was predicted to be 50:50, leading to the largest collapse area among the three scenarios.

Testing phases

To allow us to investigate the behaviour of the building specimen under small and large initial failures in only one building specimen, we decided to perform two separate testing phases. Phase 1 involved the quasi-static (gradual) removal of two edge columns (C8 and C11), whereas phase 2 involved the sudden removal of the corner column (C12) found between the columns removed in phase 1. A uniformly distributed load of 11.8  kN m −2 was applied only on the bays directly adjacent to these three columns without loading the remaining bays (Supplementary Video  5 ). This was achieved by placing more than 8,000 sandbags in the designated bays on the two floors (the first- and second-floor slabs). We performed additional computational simulations to compare this partial loading configuration and loading of the entire building. The simulations indicated that both would have resulted in almost identical final collapse states (Extended Data Fig. 7 and Supplementary Video  3 ). However, the partial loading configuration introduced a higher magnitude of unbalanced moment to surrounding columns, which induces more demanding bending and shear in columns. Simulations confirmed that the lateral drift of the remaining part of the building would be higher when only three bays are loaded, indicating that its stability would be tested to a greater extent with this loading configuration (Extended Data Fig. 7 ).

Specially designed elements to trigger initial failures

We designed special devices to perform the column removal (Extended Data Fig. 6 ). For phase 1, we constructed two hanging concrete columns (C8 and C11) supported only on a vertical hydraulic jack. The pressure in the jack could be gradually released from a safe distance to remove the vertical reaction supporting the column. In phase 2, a three-steel-hinged column was used as the corner column. The middle part of the column represents a central hinge that was able to rotate if unlocked. During the second testing phase, we unlocked the hinge by pulling the column from outside the building using a forklift to induce a slight destabilization. This resulted in a sudden removal of the corner column C12 and the initiation of the collapse.

Monitoring plan

To monitor the structural behaviour, we heavily instrumented the building specimen with multiple sensors. A total of 57 embedded strain gauges, 17 displacement transducers and 5 accelerometers were placed at key locations in different parts of the structure (Extended Data Fig. 8 and Supplementary Information Section 3 ) during all phases of testing. The data from these sensors (Supplementary Information Sections 4 and 5 ) were complemented by the pictures and videos of the structural response captured by five high-resolution cameras and two drones (Supplementary Videos  6 and 8 ).

Data availability

All experimental data recorded during testing of the full-scale building are available from Zenodo ( https://doi.org/10.5281/zenodo.10698030 ) 62 . Source data are provided with this paper.

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Acknowledgements

This article is part of a project (Endure) that has received funding from the European Research Council (ERC) under the Horizon 2020 research and innovation programme of the European Union (grant agreement no. 101000396). We acknowledge the assistance of the following colleagues from the ICITECH-UPV institute in preparing and executing the full-scale building tests: J. J. Moragues, P. Calderón, D. Tasquer, G. Caredda, D. Cetina, M. L. Gerbaudo, L. Marín, M. Oliver and G. Sempértegui. We are also grateful to the Levantina, Ingeniería y Construcción S.L. (LIC) company for providing human resources and access to their facilities for testing. Finally, we thank A. Elfouly and Applied Science International for their support in performing simulations.

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Contributions

N.M. prepared the main text, performed the computational simulations and validated the test results. A.S. analysed the experimental data, performed data curation and prepared the Methods section. M.B. contributed to the design of the building specimen, the design of the test and data curation. J.M.A. contributed to the design of the research methodology, supervised the research and was responsible for funding acquisition. N.M., A.S. and M.B. contributed to the execution of the experimental test and to preparing figures, extended data and supplementary information. All authors interpreted the test and simulation results and edited the paper.

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Correspondence to Jose M. Adam .

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Extended data figures and tables

Extended data fig. 1 summary of building designs..

General building layout, connection details, and reinforcement configurations of Design H (“Hierarchy-based”) and Design C (“Conventional”).

Extended Data Fig. 2 Comparison of measured experimental data and simulation predictions.

a, Location of shown comparisons. All data shown in panels b to d refer to the change in structural response following the sudden removal of column C12 (after having removed columns C8 and C11 in a previous phase). b, Change in axial load in lower part of column C7. c, Change in axial load in lower part of column C9. d , Change in drift measured in both directions parallel to each building side.

Extended Data Fig. 3 Computational simulations of Design H and Design C subjected to small initial failures.

Principal strains and relative vertical displacement at the location of column C11 after removal of columns C8 and C11 from Design H ( a ) and Design C ( b ).

Extended Data Fig. 4 Demand and capacity envelopes of internal forces in Designs H and C subjected to large initial failures.

Evolution of axial loads, bending moments, and shear forces in column C7 compared to lower and upper bounds of its capacity after the removal of columns C8, C11, and C12 from Design H ( a ) and Design C ( b ).

Extended Data Fig. 5 Initial failure scenarios considered for testing.

Simulation of three different initial failure scenarios that were considered for testing. Scenario 3 was selected for the experimental test.

Extended Data Fig. 6 Specially designed removable supports to perform column removals.

Removable supports designed for quasi-static column removals in phase 1 and sudden column removal in phase 2.

Extended Data Fig. 7 Comparison of simulations of fully loaded and partially loaded building specimen.

a, Loaded bays, deformed shape, and principal normal strains following the sudden removal of column C12 (after having removed columns C8 and C11 in a previous phase). b, Horizontal displacement in the east-west and north-south directions at the top of columns C1 and C9 (2nd floor).

Extended Data Fig. 8 Measured redistribution of column axial forces during phase 1.

Maximum change in axial load of columns during phase 1 of testing based on recorded strain measurements.

Supplementary information

Supplementary information.

This file contains a supplementary test report that covers as-built building design, material properties, monitoring plan, structural response in phase 1 of testing and structural response in phase 2 of testing.

Peer Review File

Supplementary video 1.

Structural response of designs H and C.

Supplementary Video 2

Initial failure scenarios.

Supplementary Video 3

Comparison of partial and full loading.

Supplementary Video 4

Construction of the building.

Supplementary Video 5

An aerial view of the building before the test.

Supplementary Video 6

Multiple perspectives of the partial collapse of the building specimen in testing phase 2.

Supplementary Video 7

Experimental and simulation comparison of the partial collapse in testing phase 2.

Supplementary Video 8

Post-collapse inspection drone video.

Source data

Source data fig. 3, source data fig. 4, source data extended data fig. 2, source data extended data fig. 3, source data extended data fig. 4, rights and permissions.

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Makoond, N., Setiawan, A., Buitrago, M. et al. Arresting failure propagation in buildings through collapse isolation. Nature 629 , 592–596 (2024). https://doi.org/10.1038/s41586-024-07268-5

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Received : 07 December 2023

Accepted : 05 March 2024

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Issue Date : 16 May 2024

DOI : https://doi.org/10.1038/s41586-024-07268-5

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