research methodology study material for phd

Writing The Methodology Chapter

5 Time-Saving Tips & Tools

By: David Phair (PhD) and Amy Murdock (PhD) | July 2022

The methodology chapter is a crucial part of your dissertation or thesis – it’s where you provide context and justification for your study’s design. This in turn demonstrates your understanding of research theory, which is what earns you marks .

Over the years, we’ve helped thousands of students navigate this tricky section of the research process. In this post, we’ll share 5 time-saving tips to help you effectively write up your research methodology chapter .

Overview: Writing The Methodology Chapter

• Develop a (rough) outline before you start writing
• Draw inspiration from similar studies in your topic area
• Justify every research design choice that you make
• Err on the side of too much detail , rather than too little
• Back up every design choice by referencing literature

1. Develop an outline before you start writing 

The first thing to keep in mind when writing your methodology chapter (and the rest of your dissertation) is that it’s always a good idea to sketch out a rough outline of what you are going to write about before you start writing . This will ensure that you stay focused and have a clear structural logic – thereby making the writing process simpler and faster.

An easy method of finding a structure for this chapter is to use frameworks that already exist, such as Saunder’s “ research onion ” as an example. Alternatively, there are many free methodology chapter templates for you to use as a starting point, so don’t feel like you have to create a new one from scratch.

Next, you’ll want to consider what your research approach is , and how you can break it down from a top-down angle, i.e., from the philosophical down to the concrete/tactical level. For example, you’ll need to articulate the following:  

• Are you using a positivist , interpretivist , or pragmatist approach ?
• Are you using inductive or deductive reasoning?
• Are you using a qualitative , quantitative, or mixed methods study?

Keep these questions front of mind to ensure that you have a clear, well-aligned line of argument that will maintain your chapter’s internal and external consistency.

Remember, it’s okay if you feel overwhelmed when you first start the methodology chapter. Nobody is born with an innate knowledge of how to do this, so be prepared for the learning curve associated with new research projects. It’s no small task to write up a dissertation or thesis, so be kind to yourself!

2. Take inspiration from other studies 

Generally, there are plenty of existing journal articles that will share similar methodological approaches to your study. With any luck, there will also be existing dissertations and theses that adopt a similar methodological approach and topic. So, consider taking inspiration from these studies to help curate the contents of your methodology chapter.

Students often find it difficult to choose what content to include in the methodology chapter and what to leave for the appendix. By reviewing other studies with similar approaches, you will get a clearer sense of your discipline’s norms and characteristics . This will help you, especially in terms of deciding on the structure and depth of discussion.  

While you can draw inspiration from other studies, remember that it’s vital to pay close attention to your university’s specific guidelines, so you can anticipate departmental expectations of this section’s layout and content (and make it easier to work with your supervisor). Doing this is also a great way to figure out how in-depth your discussion should be. For example, word-count guidelines can help you decide whether to include or omit certain information.

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3. Justify every design choice you make

The golden rule of the methodology chapter is that you need to justify each and every design choice that you make, no matter how small or inconsequential it may seem. We often see that students merely state what they did instead of why they did what they did – and this costs them marks.

Keep in mind that you need to illustrate the strength of your study’s methodological foundation. By discussing the “what”, “why” and “how” of your choices, you demonstrate your understanding of research design and simultaneously justify the relevancy and efficacy of your methodology – both of which will earn you marks.

It’s never an easy task to conduct research. So, it’s seldom the case that you’ll be able to use the very best possible methodology for your research (e.g. due to time or budgetary constraints ). That’s okay – but make sure that you explain and justify your use of an alternate methodology to help justify your approach.

Ultimately, if you don’t justify and explain the logic behind each of your choices, your marker will have to assume that you simply didn’t know any better . So, make sure that you justify every choice, especially when it is a subpar choice (due to a practical constraint, for example). You can see an example of how this is done here.

4. Err on the side of too much detail

We often see a tendency in students to mistakenly give more of an overview of their methodology instead of a step-by-step breakdown . Since the methodology chapter needs to be detailed enough for another researcher to replicate your study, your chapter should be particularly granular in terms of detail. 

Whether you’re doing a qualitative or quantitative study, it’s crucial to convey rigor in your research. You can do this by being especially detailed when you discuss your data, so be absolutely clear about your:  

• Sampling strategy
• Data collection method(s)
• Data preparation
• Analysis technique(s)

As you will likely face an extensive period of editing at your supervisor/reviewer’s direction, you’ll make it much easier for yourself if you have more information than you’d need. Some supervisors expect extensive detail around a certain aspect of your dissertation (like your research philosophy), while others may not expect it at all.

Remember, it’s quicker and easier to remove/ trim down information than it is to add information after the fact, so take the time to show your supervisor that you know what you’re talking about (methodologically) and you’re doing your best to be rigorous in your research.

5. Provide citations to support each design choice

Related to the issue of poor justification (tip #3), it’s important include high-quality academic citations to support the justification of your design choices. In other words, it’s not enough to simply explain why you chose a specific approach – you need to support each justification with reference to academic material.  

Simply put, you should avoid thinking of your methodology chapter as a citation-less section in your dissertation. As with your literature review, your methods section must include citations for every decision you make, since you are building on prior research.  You must show that you are making decisions based on methods that are proven to be effective, and not just because you “feel” that they are effective.

When considering the source of your citations, you should stick to peer-reviewed academic papers and journals and avoid using websites or blog posts (like us, hehe). Doing this will demonstrate that you are familiar with the literature and that you are factoring in what credible academics have to say about your methodology.

As a final tip, it’s always a good idea to cite as you go . If you leave this for the end, then you’ll end up spending a lot of precious time retracing your steps to find your citations and risk losing track of them entirely. So, be proactive and drop in those citations as you write up . You’ll thank yourself later!

Let’s Recap…

In this post, we covered 5 time-saving tips for writing up the methodology chapter:

• Look at similar studies in your topic area
• Justify every design choice that you make
• Back up every design choice by referencing methodology literature

If you’ve got any questions relating to the methodology chapter, feel free to drop a comment below. Alternatively, if you’re interested in getting 1-on-1 help with your thesis or dissertation, be sure to check out our private coaching service .

Psst… there’s more (for free)

This post is part of our dissertation mini-course, which covers everything you need to get started with your dissertation, thesis or research project. 

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• What Is a Research Design | Types, Guide & Examples

What Is a Research Design | Types, Guide & Examples

Published on June 7, 2021 by Shona McCombes . Revised on November 20, 2023 by Pritha Bhandari.

A research design is a strategy for answering your   research question  using empirical data. Creating a research design means making decisions about:

• Your overall research objectives and approach
• Whether you’ll rely on primary research or secondary research
• Your sampling methods or criteria for selecting subjects
• Your data collection methods
• The procedures you’ll follow to collect data
• Your data analysis methods

A well-planned research design helps ensure that your methods match your research objectives and that you use the right kind of analysis for your data.

Table of contents

Step 1: consider your aims and approach, step 2: choose a type of research design, step 3: identify your population and sampling method, step 4: choose your data collection methods, step 5: plan your data collection procedures, step 6: decide on your data analysis strategies, other interesting articles, frequently asked questions about research design.

• Introduction

Before you can start designing your research, you should already have a clear idea of the research question you want to investigate.

There are many different ways you could go about answering this question. Your research design choices should be driven by your aims and priorities—start by thinking carefully about what you want to achieve.

The first choice you need to make is whether you’ll take a qualitative or quantitative approach.

Qualitative research designs tend to be more flexible and inductive , allowing you to adjust your approach based on what you find throughout the research process.

Quantitative research designs tend to be more fixed and deductive , with variables and hypotheses clearly defined in advance of data collection.

It’s also possible to use a mixed-methods design that integrates aspects of both approaches. By combining qualitative and quantitative insights, you can gain a more complete picture of the problem you’re studying and strengthen the credibility of your conclusions.

Practical and ethical considerations when designing research

As well as scientific considerations, you need to think practically when designing your research. If your research involves people or animals, you also need to consider research ethics .

• How much time do you have to collect data and write up the research?
• Will you be able to gain access to the data you need (e.g., by travelling to a specific location or contacting specific people)?
• Do you have the necessary research skills (e.g., statistical analysis or interview techniques)?
• Will you need ethical approval ?

At each stage of the research design process, make sure that your choices are practically feasible.

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Within both qualitative and quantitative approaches, there are several types of research design to choose from. Each type provides a framework for the overall shape of your research.

Types of quantitative research designs

Quantitative designs can be split into four main types.

• Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships
• Descriptive and correlational designs allow you to measure variables and describe relationships between them.

With descriptive and correlational designs, you can get a clear picture of characteristics, trends and relationships as they exist in the real world. However, you can’t draw conclusions about cause and effect (because correlation doesn’t imply causation ).

Experiments are the strongest way to test cause-and-effect relationships without the risk of other variables influencing the results. However, their controlled conditions may not always reflect how things work in the real world. They’re often also more difficult and expensive to implement.

Types of qualitative research designs

Qualitative designs are less strictly defined. This approach is about gaining a rich, detailed understanding of a specific context or phenomenon, and you can often be more creative and flexible in designing your research.

The table below shows some common types of qualitative design. They often have similar approaches in terms of data collection, but focus on different aspects when analyzing the data.

Your research design should clearly define who or what your research will focus on, and how you’ll go about choosing your participants or subjects.

In research, a population is the entire group that you want to draw conclusions about, while a sample is the smaller group of individuals you’ll actually collect data from.

Defining the population

A population can be made up of anything you want to study—plants, animals, organizations, texts, countries, etc. In the social sciences, it most often refers to a group of people.

For example, will you focus on people from a specific demographic, region or background? Are you interested in people with a certain job or medical condition, or users of a particular product?

The more precisely you define your population, the easier it will be to gather a representative sample.

• Sampling methods

Even with a narrowly defined population, it’s rarely possible to collect data from every individual. Instead, you’ll collect data from a sample.

To select a sample, there are two main approaches: probability sampling and non-probability sampling . The sampling method you use affects how confidently you can generalize your results to the population as a whole.

Probability sampling is the most statistically valid option, but it’s often difficult to achieve unless you’re dealing with a very small and accessible population.

For practical reasons, many studies use non-probability sampling, but it’s important to be aware of the limitations and carefully consider potential biases. You should always make an effort to gather a sample that’s as representative as possible of the population.

Case selection in qualitative research

In some types of qualitative designs, sampling may not be relevant.

For example, in an ethnography or a case study , your aim is to deeply understand a specific context, not to generalize to a population. Instead of sampling, you may simply aim to collect as much data as possible about the context you are studying.

In these types of design, you still have to carefully consider your choice of case or community. You should have a clear rationale for why this particular case is suitable for answering your research question .

For example, you might choose a case study that reveals an unusual or neglected aspect of your research problem, or you might choose several very similar or very different cases in order to compare them.

Data collection methods are ways of directly measuring variables and gathering information. They allow you to gain first-hand knowledge and original insights into your research problem.

You can choose just one data collection method, or use several methods in the same study.

Survey methods

Surveys allow you to collect data about opinions, behaviors, experiences, and characteristics by asking people directly. There are two main survey methods to choose from: questionnaires and interviews .

Observation methods

Observational studies allow you to collect data unobtrusively, observing characteristics, behaviors or social interactions without relying on self-reporting.

Observations may be conducted in real time, taking notes as you observe, or you might make audiovisual recordings for later analysis. They can be qualitative or quantitative.

Other methods of data collection

There are many other ways you might collect data depending on your field and topic.

If you’re not sure which methods will work best for your research design, try reading some papers in your field to see what kinds of data collection methods they used.

Secondary data

If you don’t have the time or resources to collect data from the population you’re interested in, you can also choose to use secondary data that other researchers already collected—for example, datasets from government surveys or previous studies on your topic.

With this raw data, you can do your own analysis to answer new research questions that weren’t addressed by the original study.

Using secondary data can expand the scope of your research, as you may be able to access much larger and more varied samples than you could collect yourself.

However, it also means you don’t have any control over which variables to measure or how to measure them, so the conclusions you can draw may be limited.

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As well as deciding on your methods, you need to plan exactly how you’ll use these methods to collect data that’s consistent, accurate, and unbiased.

Planning systematic procedures is especially important in quantitative research, where you need to precisely define your variables and ensure your measurements are high in reliability and validity.

Operationalization

Some variables, like height or age, are easily measured. But often you’ll be dealing with more abstract concepts, like satisfaction, anxiety, or competence. Operationalization means turning these fuzzy ideas into measurable indicators.

If you’re using observations , which events or actions will you count?

If you’re using surveys , which questions will you ask and what range of responses will be offered?

You may also choose to use or adapt existing materials designed to measure the concept you’re interested in—for example, questionnaires or inventories whose reliability and validity has already been established.

Reliability and validity

Reliability means your results can be consistently reproduced, while validity means that you’re actually measuring the concept you’re interested in.

For valid and reliable results, your measurement materials should be thoroughly researched and carefully designed. Plan your procedures to make sure you carry out the same steps in the same way for each participant.

If you’re developing a new questionnaire or other instrument to measure a specific concept, running a pilot study allows you to check its validity and reliability in advance.

Sampling procedures

As well as choosing an appropriate sampling method , you need a concrete plan for how you’ll actually contact and recruit your selected sample.

That means making decisions about things like:

• How many participants do you need for an adequate sample size?
• What inclusion and exclusion criteria will you use to identify eligible participants?
• How will you contact your sample—by mail, online, by phone, or in person?

If you’re using a probability sampling method , it’s important that everyone who is randomly selected actually participates in the study. How will you ensure a high response rate?

If you’re using a non-probability method , how will you avoid research bias and ensure a representative sample?

Data management

It’s also important to create a data management plan for organizing and storing your data.

Will you need to transcribe interviews or perform data entry for observations? You should anonymize and safeguard any sensitive data, and make sure it’s backed up regularly.

Keeping your data well-organized will save time when it comes to analyzing it. It can also help other researchers validate and add to your findings (high replicability ).

On its own, raw data can’t answer your research question. The last step of designing your research is planning how you’ll analyze the data.

Quantitative data analysis

In quantitative research, you’ll most likely use some form of statistical analysis . With statistics, you can summarize your sample data, make estimates, and test hypotheses.

Using descriptive statistics , you can summarize your sample data in terms of:

• The distribution of the data (e.g., the frequency of each score on a test)
• The central tendency of the data (e.g., the mean to describe the average score)
• The variability of the data (e.g., the standard deviation to describe how spread out the scores are)

The specific calculations you can do depend on the level of measurement of your variables.

Using inferential statistics , you can:

• Make estimates about the population based on your sample data.
• Test hypotheses about a relationship between variables.

Regression and correlation tests look for associations between two or more variables, while comparison tests (such as t tests and ANOVAs ) look for differences in the outcomes of different groups.

Your choice of statistical test depends on various aspects of your research design, including the types of variables you’re dealing with and the distribution of your data.

Qualitative data analysis

In qualitative research, your data will usually be very dense with information and ideas. Instead of summing it up in numbers, you’ll need to comb through the data in detail, interpret its meanings, identify patterns, and extract the parts that are most relevant to your research question.

Two of the most common approaches to doing this are thematic analysis and discourse analysis .

There are many other ways of analyzing qualitative data depending on the aims of your research. To get a sense of potential approaches, try reading some qualitative research papers in your field.

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

• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

A research design is a strategy for answering your   research question . It defines your overall approach and determines how you will collect and analyze data.

A well-planned research design helps ensure that your methods match your research aims, that you collect high-quality data, and that you use the right kind of analysis to answer your questions, utilizing credible sources . This allows you to draw valid , trustworthy conclusions.

Quantitative research designs can be divided into two main categories:

• Correlational and descriptive designs are used to investigate characteristics, averages, trends, and associations between variables.
• Experimental and quasi-experimental designs are used to test causal relationships .

Qualitative research designs tend to be more flexible. Common types of qualitative design include case study , ethnography , and grounded theory designs.

The priorities of a research design can vary depending on the field, but you usually have to specify:

• Your research questions and/or hypotheses
• Your overall approach (e.g., qualitative or quantitative )
• The type of design you’re using (e.g., a survey , experiment , or case study )
• Your data collection methods (e.g., questionnaires , observations)
• Your data collection procedures (e.g., operationalization , timing and data management)
• Your data analysis methods (e.g., statistical tests  or thematic analysis )

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.

In statistics, sampling allows you to test a hypothesis about the characteristics of a population.

Operationalization means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioral avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalize the variables that you want to measure.

A research project is an academic, scientific, or professional undertaking to answer a research question . Research projects can take many forms, such as qualitative or quantitative , descriptive , longitudinal , experimental , or correlational . What kind of research approach you choose will depend on your topic.

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You will develop expertise in evaluation, statistics, and measurement, and recognize when research findings are being misrepresented or data misused. Our expert faculty will train you in both qualitative and quantitative methodology, including applied statistics and psychometrics. You'll also learn how numbers relate to action, policy, and advocacy.

You will be able to critically evaluate bodies of knowledge from a variety of methodological traditions, use a variety of software programs to implement analyses, and conduct all stages of a research study in applied settings. Plus, you'll participate in a required consulting experience, where you'll conduct a research study and then provide consulting advice to a researcher or organization.

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• For  application  related questions,  contact Graduate Enrollment Management . 
• For  program structure and academics  related questions, contact:  Ken Fujimoto , Program Chair

Tuition, Financial Aid and Scholarships

The School of Education and Loyola's Financial Aid Office are committed to helping students secure the necessary financial resources to make their education at Loyola affordable. You can learn more on the  Financial Assistance  page.

How long will it take to finish the program?

Five years is about the average length of time, especially if the student is not full-time. However a full-time student who transfers the maximum 30 credit hours from another university could complete the PhD in as few as three years. Please note that a maximum of six years is allowed to complete your coursework and dissertation.

Much will depend upon how many courses a student is able to take during any given term. Since the minimum is 20 courses, one should count on two or three years of coursework, another year for taking and passing comprehensive exams and developing a proposal, and at least one more year for the dissertation research. 

What can I do with a degree in research methodology?

This degree offers many professional opportunities. Recent graduates work at research firms, testing companies, professional associations or accrediting agencies, nonprofits, and in higher education, including institutional research.

How is the consulting experience structured?

The consulting experience is fulfilled by providing research or statistical consulting. Students, in consultation with their advisor, will determine the form of the consulting. For example, some students have provided statistical analysis assistance to faculty members or other doctoral students at the university, working on a research team with a faculty member in the School of Education. Others have completed a project associated with the student's full-time employment.

Research Methodology

Note: This exam date is subjected to change based on seat availability. You can check final exam date on your hall ticket.

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Prof. Soumitro Banerjee

Course certificate.

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MLIE-102 Research Methodology Community home page

Collections in this community, block-1 introduction to research methodology, block-2 tools for research, block-3 research methods, block-4 research process.