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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.

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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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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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• How to Write Your Methods

Ensure understanding, reproducibility and replicability

What should you include in your methods section, and how much detail is appropriate?

Why Methods Matter

The methods section was once the most likely part of a paper to be unfairly abbreviated, overly summarized, or even relegated to hard-to-find sections of a publisher’s website. While some journals may responsibly include more detailed elements of methods in supplementary sections, the movement for increased reproducibility and rigor in science has reinstated the importance of the methods section. Methods are now viewed as a key element in establishing the credibility of the research being reported, alongside the open availability of data and results.

A clear methods section impacts editorial evaluation and readers’ understanding, and is also the backbone of transparency and replicability.

For example, the Reproducibility Project: Cancer Biology project set out in 2013 to replicate experiments from 50 high profile cancer papers, but revised their target to 18 papers once they understood how much methodological detail was not contained in the original papers.

What to include in your methods section

What you include in your methods sections depends on what field you are in and what experiments you are performing. However, the general principle in place at the majority of journals is summarized well by the guidelines at PLOS ONE : “The Materials and Methods section should provide enough detail to allow suitably skilled investigators to fully replicate your study. ” The emphases here are deliberate: the methods should enable readers to understand your paper, and replicate your study. However, there is no need to go into the level of detail that a lay-person would require—the focus is on the reader who is also trained in your field, with the suitable skills and knowledge to attempt a replication.

A constant principle of rigorous science

A methods section that enables other researchers to understand and replicate your results is a constant principle of rigorous, transparent, and Open Science. Aim to be thorough, even if a particular journal doesn’t require the same level of detail . Reproducibility is all of our responsibility. You cannot create any problems by exceeding a minimum standard of information. If a journal still has word-limits—either for the overall article or specific sections—and requires some methodological details to be in a supplemental section, that is OK as long as the extra details are searchable and findable .

Imagine replicating your own work, years in the future

As part of PLOS’ presentation on Reproducibility and Open Publishing (part of UCSF’s Reproducibility Series ) we recommend planning the level of detail in your methods section by imagining you are writing for your future self, replicating your own work. When you consider that you might be at a different institution, with different account logins, applications, resources, and access levels—you can help yourself imagine the level of specificity that you yourself would require to redo the exact experiment. Consider:

• Which details would you need to be reminded of? 
• Which cell line, or antibody, or software, or reagent did you use, and does it have a Research Resource ID (RRID) that you can cite?
• Which version of a questionnaire did you use in your survey? 
• Exactly which visual stimulus did you show participants, and is it publicly available? 
• What participants did you decide to exclude? 
• What process did you adjust, during your work? 

Tip: Be sure to capture any changes to your protocols

You yourself would want to know about any adjustments, if you ever replicate the work, so you can surmise that anyone else would want to as well. Even if a necessary adjustment you made was not ideal, transparency is the key to ensuring this is not regarded as an issue in the future. It is far better to transparently convey any non-optimal methods, or methodological constraints, than to conceal them, which could result in reproducibility or ethical issues downstream.

Visual aids for methods help when reading the whole paper

Consider whether a visual representation of your methods could be appropriate or aid understanding your process. A visual reference readers can easily return to, like a flow-diagram, decision-tree, or checklist, can help readers to better understand the complete article, not just the methods section.

Ethical Considerations

In addition to describing what you did, it is just as important to assure readers that you also followed all relevant ethical guidelines when conducting your research. While ethical standards and reporting guidelines are often presented in a separate section of a paper, ensure that your methods and protocols actually follow these guidelines. Read more about ethics .

Existing standards, checklists, guidelines, partners

While the level of detail contained in a methods section should be guided by the universal principles of rigorous science outlined above, various disciplines, fields, and projects have worked hard to design and develop consistent standards, guidelines, and tools to help with reporting all types of experiment. Below, you’ll find some of the key initiatives. Ensure you read the submission guidelines for the specific journal you are submitting to, in order to discover any further journal- or field-specific policies to follow, or initiatives/tools to utilize.

Tip: Keep your paper moving forward by providing the proper paperwork up front

Be sure to check the journal guidelines and provide the necessary documents with your manuscript submission. Collecting the necessary documentation can greatly slow the first round of peer review, or cause delays when you submit your revision.

Randomized Controlled Trials – CONSORT The Consolidated Standards of Reporting Trials (CONSORT) project covers various initiatives intended to prevent the problems of  inadequate reporting of randomized controlled trials. The primary initiative is an evidence-based minimum set of recommendations for reporting randomized trials known as the CONSORT Statement . 

Systematic Reviews and Meta-Analyses – PRISMA The Preferred Reporting Items for Systematic Reviews and Meta-Analyses ( PRISMA ) is an evidence-based minimum set of items focusing  on the reporting of  reviews evaluating randomized trials and other types of research.

Research using Animals – ARRIVE The Animal Research: Reporting of In Vivo Experiments ( ARRIVE ) guidelines encourage maximizing the information reported in research using animals thereby minimizing unnecessary studies. (Original study and proposal , and updated guidelines , in PLOS Biology .) 

Laboratory Protocols Protocols.io has developed a platform specifically for the sharing and updating of laboratory protocols , which are assigned their own DOI and can be linked from methods sections of papers to enhance reproducibility. Contextualize your protocol and improve discovery with an accompanying Lab Protocol article in PLOS ONE .

Consistent reporting of Materials, Design, and Analysis – the MDAR checklist A cross-publisher group of editors and experts have developed, tested, and rolled out a checklist to help establish and harmonize reporting standards in the Life Sciences . The checklist , which is available for use by authors to compile their methods, and editors/reviewers to check methods, establishes a minimum set of requirements in transparent reporting and is adaptable to any discipline within the Life Sciences, by covering a breadth of potentially relevant methodological items and considerations. If you are in the Life Sciences and writing up your methods section, try working through the MDAR checklist and see whether it helps you include all relevant details into your methods, and whether it reminded you of anything you might have missed otherwise.

Summary Writing tips

The main challenge you may find when writing your methods is keeping it readable AND covering all the details needed for reproducibility and replicability. While this is difficult, do not compromise on rigorous standards for credibility!

• Keep in mind future replicability, alongside understanding and readability.
• Follow checklists, and field- and journal-specific guidelines.
• Consider a commitment to rigorous and transparent science a personal responsibility, and not just adhering to journal guidelines.
• Establish whether there are persistent identifiers for any research resources you use that can be specifically cited in your methods section.
• Deposit your laboratory protocols in Protocols.io, establishing a permanent link to them. You can update your protocols later if you improve on them, as can future scientists who follow your protocols.
• Consider visual aids like flow-diagrams, lists, to help with reading other sections of the paper.
• Be specific about all decisions made during the experiments that someone reproducing your work would need to know.

Don’t

• Summarize or abbreviate methods without giving full details in a discoverable supplemental section.
• Presume you will always be able to remember how you performed the experiments, or have access to private or institutional notebooks and resources.
• Attempt to hide constraints or non-optimal decisions you had to make–transparency is the key to ensuring the credibility of your research.
• How to Write a Great Title
• How to Write an Abstract
• How to Report Statistics
• How to Write Discussions and Conclusions
• How to Edit Your Work

The contents of the Peer Review Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

The contents of the Writing Center are also available as a live, interactive training session, complete with slides, talking points, and activities. …

There’s a lot to consider when deciding where to submit your work. Learn how to choose a journal that will help your study reach its audience, while reflecting your values as a researcher…

• 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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How Do I Write the Methods Chapter?

Methods, Participants, and Describing Data Analysis

• First Online: 19 October 2023

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• Sue Reeves   ORCID: orcid.org/0000-0002-3017-0559 3 &
• Bartek Buczkowski   ORCID: orcid.org/0000-0002-4146-3664 4  

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The methods chapter is where you describe what you did to collect and analyse your data. This book chapter will outline what the methods chapter should cover, potential differences in the styles between experiments, surveys, literature reviews, and audits. The different sections the methods chapter typically has including design, sample, measures, ethics and data analysis paragraphs, will be outlined, and there are also some general tips for writing your methods chapter in a scientific manner.

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Further Reading

For more general information on research methodologies:

Google Scholar  

Kumar R (2019) Research methodology–a step by step guide for beginners. Sage, Thousand Oaks, Ca

For qualitative methods in particular:

Durdella N (2018) Qualitative dissertation methodology–a guide for research design and methods. Sage, Thousand Oaks, Ca

For power calculations:

Jones SR, Carley S, Harrison M (2003) An introduction to power and sample size estimation. Emerg Med J 20:453–458

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For help with statistics:

Petrie A, Sabin C (2019) Medical statistics at a glance, 4th edn. Wiley Blackwell, Oxford

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How to Write a Methods Section for a Psychology Paper

Tips and Examples of an APA Methods Section

Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Emily is a board-certified science editor who has worked with top digital publishing brands like Voices for Biodiversity, Study.com, GoodTherapy, Vox, and Verywell.

Verywell / Brianna Gilmartin 

The methods section of an APA format psychology paper provides the methods and procedures used in a research study or experiment . This part of an APA paper is critical because it allows other researchers to see exactly how you conducted your research.

Method refers to the procedure that was used in a research study. It included a precise description of how the experiments were performed and why particular procedures were selected. While the APA technically refers to this section as the 'method section,' it is also often known as a 'methods section.'

The methods section ensures the experiment's reproducibility and the assessment of alternative methods that might produce different results. It also allows researchers to replicate the experiment and judge the study's validity.

This article discusses how to write a methods section for a psychology paper, including important elements to include and tips that can help.

What to Include in a Method Section

So what exactly do you need to include when writing your method section? You should provide detailed information on the following:

• Research design
• Participants
• Participant behavior

The method section should provide enough information to allow other researchers to replicate your experiment or study.

Components of a Method Section

The method section should utilize subheadings to divide up different subsections. These subsections typically include participants, materials, design, and procedure.

Participants 

In this part of the method section, you should describe the participants in your experiment, including who they were (and any unique features that set them apart from the general population), how many there were, and how they were selected. If you utilized random selection to choose your participants, it should be noted here.

For example: "We randomly selected 100 children from elementary schools near the University of Arizona."

At the very minimum, this part of your method section must convey:

• Basic demographic characteristics of your participants (such as sex, age, ethnicity, or religion)
• The population from which your participants were drawn
• Any restrictions on your pool of participants
• How many participants were assigned to each condition and how they were assigned to each group (i.e., randomly assignment , another selection method, etc.)
• Why participants took part in your research (i.e., the study was advertised at a college or hospital, they received some type of incentive, etc.)

Information about participants helps other researchers understand how your study was performed, how generalizable the result might be, and allows other researchers to replicate the experiment with other populations to see if they might obtain the same results.

In this part of the method section, you should describe the materials, measures, equipment, or stimuli used in the experiment. This may include:

• Testing instruments
• Technical equipment
• Any psychological assessments that were used
• Any special equipment that was used

For example: "Two stories from Sullivan et al.'s (1994) second-order false belief attribution tasks were used to assess children's understanding of second-order beliefs."

For standard equipment such as computers, televisions, and videos, you can simply name the device and not provide further explanation.

Specialized equipment should be given greater detail, especially if it is complex or created for a niche purpose. In some instances, such as if you created a special material or apparatus for your study, you might need to include an illustration of the item in the appendix of your paper.

In this part of your method section, describe the type of design used in the experiment. Specify the variables as well as the levels of these variables. Identify:

• The independent variables
• Dependent variables
• Control variables
• Any extraneous variables that might influence your results.

Also, explain whether your experiment uses a  within-groups  or between-groups design.

For example: "The experiment used a 3x2 between-subjects design. The independent variables were age and understanding of second-order beliefs."

The next part of your method section should detail the procedures used in your experiment. Your procedures should explain:

• What the participants did
• How data was collected
• The order in which steps occurred

For example: "An examiner interviewed children individually at their school in one session that lasted 20 minutes on average. The examiner explained to each child that he or she would be told two short stories and that some questions would be asked after each story. All sessions were videotaped so the data could later be coded."

Keep this subsection concise yet detailed. Explain what you did and how you did it, but do not overwhelm your readers with too much information.

Tips for How to Write a Methods Section

In addition to following the basic structure of an APA method section, there are also certain things you should remember when writing this section of your paper. Consider the following tips when writing this section:

• Use the past tense : Always write the method section in the past tense.
• Be descriptive : Provide enough detail that another researcher could replicate your experiment, but focus on brevity. Avoid unnecessary detail that is not relevant to the outcome of the experiment.
• Use an academic tone : Use formal language and avoid slang or colloquial expressions. Word choice is also important. Refer to the people in your experiment or study as "participants" rather than "subjects."
• Use APA format : Keep a style guide on hand as you write your method section. The Publication Manual of the American Psychological Association is the official source for APA style.
• Make connections : Read through each section of your paper for agreement with other sections. If you mention procedures in the method section, these elements should be discussed in the results and discussion sections.
• Proofread : Check your paper for grammar, spelling, and punctuation errors.. typos, grammar problems, and spelling errors. Although a spell checker is a handy tool, there are some errors only you can catch.

After writing a draft of your method section, be sure to get a second opinion. You can often become too close to your work to see errors or lack of clarity. Take a rough draft of your method section to your university's writing lab for additional assistance.

A Word From Verywell

The method section is one of the most important components of your APA format paper. The goal of your paper should be to clearly detail what you did in your experiment. Provide enough detail that another researcher could replicate your study if they wanted.

Finally, if you are writing your paper for a class or for a specific publication, be sure to keep in mind any specific instructions provided by your instructor or by the journal editor. Your instructor may have certain requirements that you need to follow while writing your method section.

Frequently Asked Questions

While the subsections can vary, the three components that should be included are sections on the participants, the materials, and the procedures.

• Describe who the participants were in the study and how they were selected.
• Define and describe the materials that were used including any equipment, tests, or assessments
• Describe how the data was collected

To write your methods section in APA format, describe your participants, materials, study design, and procedures. Keep this section succinct, and always write in the past tense. The main heading of this section should be labeled "Method" and it should be centered, bolded, and capitalized. Each subheading within this section should be bolded, left-aligned and in title case.

The purpose of the methods section is to describe what you did in your experiment. It should be brief, but include enough detail that someone could replicate your experiment based on this information. Your methods section should detail what you did to answer your research question. Describe how the study was conducted, the study design that was used and why it was chosen, and how you collected the data and analyzed the results.

Erdemir F. How to write a materials and methods section of a scientific article ? Turk J Urol . 2013;39(Suppl 1):10-5. doi:10.5152/tud.2013.047

Kallet RH. How to write the methods section of a research paper . Respir Care . 2004;49(10):1229-32. PMID: 15447808.

American Psychological Association.  Publication Manual of the American Psychological Association  (7th ed.). Washington DC: The American Psychological Association; 2019.

American Psychological Association. APA Style Journal Article Reporting Standards . Published 2020.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Research Voyage

Research Tips and Infromation

How to Write the Methodology Section of your Dissertation or Thesis?

Introduction

Role of research design in methodology section, how to represent participants or sample data in the methodology section, how to segregate data collection methods in the methodology section, representation of instruments and materials in the methodology section, how to represent data analysis in the methodology section, listing of ethical considerations in methodology section, how to list limitations and delimitations in the methodology section, validity and reliability aspects in methodology section, representation of timeframe and resources in methodology section, segregation of data management in methodology section.

The methodology section is a crucial component of a PhD or Post Graduate dissertation. It plays a fundamental role in demonstrating the rigor and validity of the research conducted. The methodology section outlines the methods used to conduct the research and provides a clear roadmap for the reader to understand how the study was executed.

The methodology section allows researchers to explain their approach and provide the necessary details for others to reproduce or build upon their work. It is essential for establishing the credibility and scientific integrity of the research.

For example, in a dissertation focused on developing a new machine learning algorithm for image classification, the methodology section would describe the specific steps followed to design, implement, and evaluate the algorithm. It would include details such as the choice of programming languages and libraries, the dataset used for training and testing, and the evaluation metrics employed. This information allows other researchers to understand how the algorithm was developed, assess its strengths and limitations, and potentially apply it to their own work.

Similarly, in a dissertation that involves conducting experiments to evaluate the performance of a networking protocol, the methodology section would describe the experimental setup, the hardware and software used, and the metrics measured. It would explain the steps taken to control variables, ensure reproducibility, and analyze the collected data. By documenting the methodology, researchers can provide a clear understanding of how the experiments were conducted, enabling others to validate the results or compare them with alternative approaches.

In both examples, the methodology section serves as a foundation for the research and establishes its scientific validity. It allows researchers to communicate the methods used, justify their choices, and provide the necessary details for others to assess and build upon their work.

By outlining the methodology, researchers can demonstrate their expertise, attention to detail, and adherence to scientific principles. This section also serves as a reference for future researchers who may want to replicate or extend the study. The methodology section is essential for ensuring the transparency, reproducibility, and credibility of research in computer science and contributes to the advancement of knowledge in the field.

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For any research domain, various research designs can be employed, depending on the nature of the study and the research goals. The choice of research design should align with the specific objectives of the research and the type of data being collected. Here are some examples of research designs commonly used:

• Quantitative Research Design: Quantitative research designs focus on collecting and analyzing numerical data to identify patterns, trends, and relationships. This can involve conducting experiments, surveys, or analyzing large datasets. For instance, a study aiming to evaluate the performance of different caching algorithms in a web server environment may use a quantitative design. The researcher could collect data on response times, cache hit rates, and system resource usage to compare the performance of the algorithms quantitatively.
• Qualitative Research Design: Qualitative research designs emphasize understanding and interpreting complex phenomena, often through in-depth interviews, observations, or case studies. Qualitative research can be employed to explore user experiences, perceptions, or challenges related to software systems or human-computer interaction. For example, a study investigating user satisfaction and feedback regarding a new mobile application could use qualitative research methods to collect and analyze user interviews or focus group discussions.
• Mixed Methods Research Design: Mixed methods research designs combine elements of both quantitative and qualitative approaches. This design allows researchers to gather a comprehensive understanding of a research problem by leveraging the strengths of both types of data. A mixed methods approach can be useful when seeking to explore user behavior (qualitative) and simultaneously collect and analyze usage data (quantitative). For instance, a study on the effectiveness of a learning management system might involve administering surveys to gather user perceptions (qualitative) while also tracking user interactions and performance within the system (quantitative).

When choosing a research design, researchers should consider the specific research goals and the type of data that will provide the most relevant insights. The rationale for selecting a particular design should be based on the strengths of that approach in addressing the research questions or objectives. It is important to justify the chosen design by explaining how it aligns with the research goals and allows for a comprehensive investigation of the phenomenon under study.

For example, in a Ph.D. dissertation focused on developing a new algorithm for sentiment analysis in social media data, a mixed methods research design might be appropriate. The qualitative component could involve analyzing a smaller subset of data manually to gain insights into the nuances and context of sentiment expressions. The quantitative component could involve applying the developed algorithm to a large dataset to measure its performance objectively. The rationale for choosing a mixed methods design would be to combine the benefits of qualitative analysis for understanding the complexities of sentiment expressions with the quantitative analysis for evaluating the algorithm’s accuracy and efficiency.

By selecting an appropriate research design and justifying its suitability, researchers can ensure that their study is well-aligned with their research goals and has the potential to yield valuable and valid findings.

In research, the participants or sample refers to the individuals, organizations, or data sources from which the researcher collects data. The characteristics of the study participants or sample are important to consider, as they can influence the generalizability and applicability of the research findings. Here are some examples of considerations for participants or samples in research:

• Characteristics of Participants: Describe the relevant characteristics of the participants in your study. In computer science, participants can include users of a software system, developers, IT professionals, or other stakeholders. For example, if you are conducting a study on the usability of a mobile application, you might describe the age range, technical expertise, or familiarity with similar applications of the participants.
• Sample Selection Process: Explain how you selected the participants or sample for your study. In computer science, the sample selection process can vary depending on the research goals and methodologies employed. For instance, if you are conducting a survey on user preferences for a specific software feature, you might recruit participants through online platforms or professional networks. Alternatively, if you are conducting interviews with software developers, you might use purposive sampling to select participants with specific expertise or experience relevant to your research.
• Inclusion/Exclusion Criteria: Discuss any inclusion or exclusion criteria used during the participant selection process. In computer science, certain criteria may be relevant for ensuring the sample represents the desired population or meets specific research requirements. For example, if you are studying the impact of a new programming language on software development, you might include participants who have experience with multiple programming languages but exclude those who are novices or have limited experience.
• Data Sources: In some computer science research, the sample may refer to data sources rather than human participants. For example, if you are analyzing large datasets, such as social media data or sensor data, you might describe the characteristics of the data sources, such as the volume, variety, or origin of the data. You could also explain the data collection process and any steps taken to ensure data quality and representativeness.

By describing the characteristics of the study participants or sample and explaining the selection process, researchers can provide insights into the population under study and the considerations taken to ensure its relevance to the research objectives. It is important to consider the representativeness of the sample or data sources and to address any potential biases that may arise from the selection process. Transparency in describing the sample characteristics and selection process contributes to the credibility and generalizability of the research findings.

In research, various data collection methods can be employed to gather the necessary data for analysis. The choice of data collection methods should align with the research questions, objectives, and the type of data needed to answer them. Here are some examples of data collection methods commonly used:

• Surveys: Surveys involve collecting data through structured questionnaires or online forms. Surveys can be administered to gather information about user preferences, opinions, or experiences related to software systems, user interfaces, or technological adoption. For example, a survey could be conducted to assess user satisfaction with a newly developed mobile application, collecting quantitative data on ratings, feedback, and user demographics.
• Interviews: Interviews involve conducting one-on-one or group discussions with participants to gather in-depth qualitative or quantitative data. In computer science, interviews can be used to understand user needs, gather requirements for software development, or explore experiences and perceptions. For instance, interviews could be conducted with software developers to understand their challenges and preferences when using specific programming frameworks or tools.
• Observations: Observations involve directly observing participants or systems in their natural environment or controlled settings. In computer science, observations can be used to study user behavior, system interactions, or software development processes. For example, researchers may observe users interacting with a website to gather data on usability or conduct ethnographic observations to understand how users integrate technology into their daily lives.
• Experiments: Experiments involve manipulating variables in a controlled environment to assess cause-effect relationships. In computer science, experiments can be used to evaluate the performance of algorithms, software systems, or user interfaces. For example, an experiment might involve comparing the effectiveness of two different algorithms for image recognition by measuring their accuracy, processing time, and resource usage under controlled conditions.
• Data Mining and Analysis: Data mining and analysis involve extracting meaningful patterns, insights, or correlations from large datasets. In computer science, data mining techniques can be used to identify trends, anomalies, or patterns in various domains such as social networks, cybersecurity, or recommendation systems. For instance, data mining algorithms could be applied to analyze social media data to identify sentiment trends or to detect patterns of malicious activities in network traffic data.

When choosing specific data collection methods, researchers should consider the research questions or objectives and the type of data needed to answer them effectively. Each data collection method has its strengths and limitations, and the choice should be justified based on their relevance to the research goals. Researchers should also consider practical considerations such as time constraints, available resources, and ethical considerations when selecting data collection methods.

By selecting appropriate data collection methods and justifying their relevance, researchers can ensure the data collected is robust, aligned with the research objectives, and provides valuable insights into the research questions under investigation.

In research, the instruments and materials used for data collection play a crucial role in ensuring the reliability and validity of the findings. These instruments can include questionnaires, scales, interview protocols, software tools, or hardware devices. Here are some examples of instruments and materials commonly used:

• Questionnaires: Questionnaires are structured sets of questions used to collect data from participants. In computer science, questionnaires can be used to gather information about user preferences, opinions, or demographics. When developing questionnaires, researchers should pay attention to the clarity, relevance, and appropriateness of the questions. They should also consider the validity and reliability of the questionnaire, which can be established through pilot testing and statistical analysis.
• Scales: Scales are instruments used to measure attitudes, opinions, or perceptions of participants on a specific construct. In computer science, scales can be used to assess user satisfaction, system usability, or technology acceptance. Commonly used scales in computer science research include the System Usability Scale (SUS) for evaluating usability and the Technology Acceptance Model (TAM) for assessing users’ acceptance of technology. Researchers should ensure that the scales used have established validity and reliability through previous research studies.
• Interview Protocols: Interview protocols are guides or outlines used during interviews to ensure consistency and cover relevant topics. In computer science, interview protocols can be used to gather qualitative or quantitative data from participants. The development of interview protocols involves identifying the research objectives and research questions and designing open-ended or structured questions accordingly. Piloting the interview protocols and considering feedback from participants can help refine and improve their effectiveness.
• Software Tools: In computer science research, software tools are often used to collect, analyze, or process data. These tools can include programming languages, data collection platforms, data analysis software, or simulation environments. For example, researchers might use Python programming language and libraries such as TensorFlow or PyTorch for implementing machine learning algorithms. They might also use tools like Qualtrics or LimeSurvey for online survey data collection or tools like SPSS or R for statistical analysis.
• Hardware Devices: In certain computer science research, hardware devices are utilized for data collection purposes. For instance, in the field of human-computer interaction, eye-tracking devices or physiological sensors might be used to measure user attention or emotional responses. In such cases, researchers should describe the specific hardware devices used, their specifications, and any calibration or preprocessing steps undertaken to ensure accurate and reliable data collection.

When describing instruments and materials in the methodology section, researchers should provide details about their development, validity, and reliability. This can include information about the process of creating or adapting the instruments, any modifications made to suit the research context, and evidence of their psychometric properties, such as validity and reliability coefficients. Validity can be established through content validity, criterion-related validity, or construct validity, while reliability can be assessed through measures like internal consistency or test-retest reliability.

By providing a comprehensive overview of the instruments and materials used, their development process, and their validity and reliability, computer science researchers can ensure transparency and demonstrate the rigor of their data collection methods. This helps establish the credibility and trustworthiness of the research findings.

Data analysis is a critical step in research as it involves interpreting and deriving meaningful insights from the collected data. The chosen data analysis methods should align with the research objectives and the type of data collected. Here are some examples of data analysis techniques commonly used in research:

• Statistical Analysis: Statistical analysis involves applying various statistical tests and techniques to analyze quantitative data. In computer science, statistical analysis can be used to examine relationships, identify patterns, or test hypotheses. For example, researchers may use t-tests, chi-square tests, or ANOVA to compare means or proportions between different groups. Regression analysis can be employed to assess the relationship between variables, and correlation analysis can measure the strength and direction of associations.
• Machine Learning: Machine learning techniques are widely used in computer science to analyze and make predictions from large datasets. These techniques include supervised learning algorithms (e.g., decision trees, support vector machines, neural networks) and unsupervised learning algorithms (e.g., clustering, dimensionality reduction). Researchers can employ machine learning techniques for tasks such as classification, regression, clustering, or anomaly detection. Popular machine learning libraries in computer science include scikit-learn, TensorFlow, and PyTorch.
• Qualitative Analysis: Qualitative analysis involves interpreting and making sense of qualitative data such as interview transcripts, observation notes, or textual data. In computer science, qualitative analysis methods like thematic analysis, content analysis, or grounded theory can be used to derive themes, patterns, or categories from the data. Qualitative analysis often involves coding the data, categorizing information, and identifying emergent themes or concepts. Software tools such as NVivo or Atlas.ti can be employed to facilitate qualitative analysis.
• Text Mining and Natural Language Processing: Text mining and natural language processing (NLP) techniques are used to analyze textual data, such as social media posts, user reviews, or scientific articles. These techniques involve tasks like sentiment analysis, topic modeling, named entity recognition, or text classification. In computer science, researchers may employ libraries such as NLTK, spaCy, or gensim to preprocess and analyze text data and derive insights from it.

When justifying the chosen data analysis methods, researchers should explain how these methods align with the research objectives and research questions. The chosen analysis methods should allow researchers to address the research objectives effectively and extract meaningful insights from the data. Researchers should also consider the limitations and assumptions of the chosen methods and discuss any steps taken to address potential biases or limitations in the analysis process.

Additionally, it is important to mention the software packages or tools used for data analysis. This provides transparency and allows other researchers to replicate or validate the analysis. Researchers should provide information about the specific versions of software packages used, any preprocessing steps applied to the data, and the rationale behind choosing those particular tools.

Ethical considerations are of utmost importance in any research study. Researchers need to ensure that the rights, privacy, and well-being of participants are protected throughout the research process. Here are some examples of ethical considerations commonly addressed in research:

• Informed Consent: Informed consent is a fundamental ethical principle that requires researchers to obtain the voluntary and informed agreement of participants before their involvement in the study. In computer science research, participants should be provided with clear and understandable information about the study’s purpose, procedures, potential risks and benefits, confidentiality, and their rights as participants. For example, if conducting user studies for a software evaluation, participants should be informed about the purpose of the study, the tasks they will be asked to perform, and how their data will be collected and used.
• Privacy and Confidentiality: Privacy and confidentiality are essential considerations, particularly when dealing with sensitive data or personal information. In computer science research, researchers must take steps to protect the privacy of participants and ensure the confidentiality of their data. For instance, if collecting user data through online platforms or mobile applications, researchers should clearly communicate how the data will be handled, stored securely, and anonymized or pseudonymized when necessary. Researchers should also obtain necessary permissions if accessing or using datasets or third-party data sources.
• Risks and Benefits: Researchers should carefully consider and communicate any potential risks or benefits associated with participation in the study. In computer science research, risks might include breaches of data security, potential harm to participants’ privacy, or adverse effects resulting from the use of experimental technologies. Researchers should proactively mitigate and minimize risks and ensure that the benefits of the research outweigh the potential risks to participants and society.
• Ethics Committee Approval: Many institutions require researchers to obtain ethics committee or review board approval before conducting research involving human participants. In computer science research, this typically involves submitting a research proposal detailing the research objectives, methods, ethical considerations, and participant protections. Examples include Institutional Review Boards (IRBs) or Ethics Review Committees. Researchers should mention any approvals obtained and follow the ethical guidelines set forth by their institution or relevant regulatory bodies.

Researchers should also be aware of any specific ethical guidelines or standards in their field of study. For example, in areas like cybersecurity or data privacy, additional considerations such as vulnerability disclosure, data anonymization, or responsible data usage may be relevant.

By addressing ethical considerations in the methodology section, researchers demonstrate their commitment to conducting responsible and ethical research. They show that they have taken appropriate measures to protect participants’ rights, privacy, and well-being. Clear communication and transparency regarding informed consent, privacy, confidentiality, potential risks and benefits, and any approvals obtained contribute to the ethical integrity and credibility of the research.

In any research study, it is important to acknowledge the limitations and delimitations that may have influenced the research process or findings. Researchers should identify the constraints, boundaries, and scope of their study. Here are some examples of limitations and delimitations commonly addressed in research:

• Sample Size and Selection: Limitations related to sample size and selection can arise in research. For example, if the study involved user testing of a software system, the sample size might have been limited due to time and resource constraints. Researchers should acknowledge that the findings may not be generalizable to the entire population and discuss the implications of the limited sample size on the validity and generalizability of the results.
• Data Collection Methods: Limitations can arise from the data collection methods employed in the study. For instance, if the study relied solely on self-reported data through surveys or interviews, there may be a risk of response bias or recall bias. Researchers should acknowledge such limitations and discuss the potential impact on the reliability and validity of the findings. They could suggest future research directions that employ complementary data collection methods to enhance the robustness of the study.
• Time and Resource Constraints: Time and resource constraints can affect the scope and depth of a research study. Researchers may have had limited time to collect data, implement complex algorithms, or conduct extensive experiments. It is important to acknowledge these constraints and discuss how they may have influenced the research outcomes or limited the extent of the study’s analysis. Researchers should be transparent about the trade-offs made due to such limitations.
• Technological Constraints: In research, technological constraints can arise due to hardware limitations, software limitations, or the availability of data. For example, a study involving real-time analysis of large-scale data may have been limited by the computational power or storage capacity of the available infrastructure. Researchers should discuss these technological constraints and their potential impact on the study’s results or the generalizability of the findings.
• Delimitations: Delimitations define the boundaries or scope of the study. For example, a study may focus on a specific programming language, a particular software framework, or a specific user group. Researchers should clearly define and communicate these delimitations, explaining why they were chosen and discussing how they may affect the applicability of the findings to other contexts or populations.

By acknowledging the limitations and delimitations of the study, researchers demonstrate a thoughtful and reflective approach to their research. They provide transparency and context for the readers, enabling them to interpret the findings appropriately. Furthermore, by discussing the implications of these limitations and delimitations, researchers can suggest potential avenues for future research that can overcome these constraints and expand upon the current study’s limitations.

Ensuring the validity and reliability of the research findings is crucial in research. Validity refers to the extent to which the research measures what it intends to measure, while reliability refers to the consistency and stability of the research results. Here are some examples of steps taken to ensure validity and reliability in computer science research:

• Implementing proper control groups and experimental design to establish cause-effect relationships.
• Randomizing the assignment of participants to different conditions or treatments to minimize biases.
• Conducting pilot studies or pre-tests to refine measurement instruments and identify potential issues.
• Considering and addressing threats to internal validity, such as confounding variables or selection bias.
• Ensuring the representativeness of the sample or participants to the target population.
• Employing diverse data sources or datasets to increase the breadth of the study.
• Conducting research in multiple settings or environments to assess the generalizability of the findings.
• Transparently reporting the study’s context, methodology, and limitations to facilitate external validity assessments by other researchers.
• Employing established and validated measurement instruments or tools.
• Conducting pilot studies or test-retest reliability analyses to assess the stability of the measurements over time.
• Ensuring inter-rater reliability in cases where multiple researchers are involved in data coding or analysis.
• Documenting the procedures and steps taken during data collection, preprocessing, and analysis to enable replication and validation.
• Implementing blinding or double-blinding procedures to minimize biases in data collection or analysis.
• Using standardized protocols or procedures to ensure consistency across participants or conditions.
• Employing objective measures or automated data collection techniques to reduce subjective biases.
• Conducting sensitivity analyses or exploring alternative explanations to address potential biases or alternative interpretations of the findings.

By discussing the steps taken to ensure validity and reliability, researchers demonstrate the rigor and credibility of their research. Addressing internal and external validity, as well as measures taken to minimize biases, helps establish the trustworthiness of the research findings. Additionally, providing transparency about the research methodology and limitations enables other researchers to assess and build upon the study’s validity and reliability in future work.

The timeframe and resources utilized in a research study are important considerations that help provide a clear understanding of the project’s scope, duration, and support. Here are some examples of how this can be elaborated upon in the methodology section:

• Planning and designing the research: This involves formulating research questions, conducting literature reviews, and developing the research methodology.
• Data collection: This includes the time required to collect data through surveys, experiments, interviews, or other methods, as well as any pilot testing or data preprocessing steps.
• Data analysis: This phase covers the time needed for data processing, statistical analysis, coding, or machine learning model training and evaluation.
• Results interpretation and report writing: This entails analyzing the findings, drawing conclusions, and documenting the research outcomes in the form of a dissertation or research paper.
• Revisions and finalization: This stage accounts for any revisions, incorporating feedback, and finalizing the research document.
• Funding: Researchers can mention any grants, scholarships, or funding sources that supported the research project. For instance, if the study received funding from a research grant or institution, the details of the funding organization, grant number, and duration can be provided.
• Equipment and Software: Researchers can outline any specialized equipment, hardware, or software used in the study. For example, if the research involved running simulations on high-performance computing clusters or using specific software tools or libraries, these details can be mentioned.
• Datasets: If the study utilized existing datasets, researchers can specify the sources and describe any preprocessing steps or data cleaning procedures undertaken to ensure data quality and integrity.
• Personnel: Researchers can acknowledge the contributions of any collaborators, research assistants, or support staff involved in the study. This can include their roles and responsibilities, as well as any specific expertise they brought to the project.

By providing an overview of the research timeframe and the resources utilized, researchers give readers a sense of the project’s timeline and the support available. This information helps to contextualize the research, understand the feasibility of the study, and evaluate the availability of necessary resources. It also enhances the transparency and reproducibility of the research, allowing other researchers to replicate or build upon the study’s findings.

Data management is a critical aspect, ensuring that data is organized, stored securely, and managed throughout the research process. Here are some examples of how data management can be elaborated upon in the methodology section:

• Data Organization: Researchers should explain how data was organized to facilitate efficient analysis and interpretation. This may involve creating a data structure or schema that captures relevant variables, metadata, and relationships between data elements. For example, in a machine learning study, researchers may organize the data into training, validation, and test sets, each with specific features and labels.
• Data Storage: Researchers should describe the storage infrastructure used to house the research data. This can include local servers, cloud-based storage platforms (e.g., Amazon S3, Google Cloud Storage), or institutional data repositories. It’s important to mention the capacity and scalability of the storage solution to accommodate the volume and variety of the collected data.
• Data Security: Data security measures are crucial to protect the privacy and integrity of research data. Researchers should discuss the protocols implemented to ensure data security throughout the research process. Examples may include encryption of sensitive information, access controls (e.g., user authentication, authorization levels), and network security measures (e.g., firewalls, intrusion detection systems). Compliance with relevant data protection regulations, such as GDPR (General Data Protection Regulation), should also be addressed if applicable.
• Backup and Retention: Researchers should outline the procedures and protocols in place for data backup and retention. This includes regular backup schedules to prevent data loss, as well as the storage location and redundancy mechanisms. Researchers may also discuss data retention policies, specifying the duration for which the data will be retained after the completion of the research project, and any anonymization or pseudonymization processes applied to protect participant identities.
• Data Sharing and Access: Researchers should indicate whether the research data will be shared with other researchers or made publicly available. If data sharing is planned, details such as the repository or platform where the data will be deposited and any associated access restrictions or licenses should be provided. Researchers should also address any ethical or legal considerations related to data sharing, such as obtaining informed consent from participants for data sharing purposes.

By explaining the data management procedures, researchers demonstrate their commitment to maintaining data integrity, privacy, and security. Transparently documenting data organization, storage, security, backup, and retention protocols enhances the reproducibility and credibility of the research. It also ensures compliance with ethical guidelines and data protection regulations, while facilitating data sharing and future collaborations.

The methodology section of a dissertation plays a crucial role in providing a clear and comprehensive understanding of how the research was conducted. It serves as a roadmap that outlines the methods, procedures, and techniques employed to address the research questions or objectives.

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What is the Methods Chapter?

This chapter provides information on what you did and how you did it over the course of your research. Essentially, this chapter will list the steps you followed to help you answer your research questions and determine the accuracy of your hypotheses. A goal to have in mind when you are writing this chapter is to be detailed enough so that a colleague reading through the steps of your study could replicate your research without needing additional information. It is important that as you write your methods section, you ensure alignment with other sections of your dissertation.

(Important note: Remember that in this chapter, you are not getting into your findings or the results from your study. This is only to explain the process you used to obtain these results)

Before you Begin

What tense should i use in this chapter.

By the time you are writing this chapter of your dissertation, you should have completed your research. Thus, you will write the methods chapter in past tense .

Organization

Consider organizing this chapter in the following manner: 1. Introductory paragraph including general research design and organization of chapter 2. Data collection methods (how did you gather your data?) 3. Data analysis methods (how did you analyze your data?)

1. What do I Include in my Introductory Paragraph?

As is the intent of any introduction paragraphs, this paragraph will provide your readers with context for the research you conducted and provide them with an understanding of what will follow it. Consider incorporating the following information:

Reference to the Aim: Consider starting this paragraph by referencing the overall aim/purpose of your research. Be careful not to go into too much detail about why this was your aim or why this purpose matters. This information will be added to other chapters. Here stick to one sentence.

Research Design Statement: In one to two sentences, describe the research design you used for this study. There are a variety of research design approaches; for additional support on this topic, see here. If you are using a specific type of quantitative or qualitative design (ex: quasi experimental, case study), consider also stating this in your introduction.

Quantitative

Study Information: Emailed a survey to 200 undergraduate educators who just finished teaching their first classes to determine how effective their program was at preparing them for the role itself.

Statement: This study used a cross-sectional survey design to assess how prepared first-time undergraduate educators felt after teaching their initial courses.

Qualitative

Study Information: Interviewed 35 students who participated in a study incorporating the wise intervention strategy to their feedback to determine perception of bias.

Statement: This study used a narrative research design to identify how the wise intervention strategy influenced the perception of bias in freshman students at the university level.

Organization of the Chapter: Add a statement or two describing what information the reader will find in this chapter and how it is organized.

2. What do I Include in the Data Collections Section?

This section will be dedicated to explaining to your readers how you collected the data that you needed in order to answer your research questions and verify the accuracy of your hypotheses (if applicable). The way you organize this information may vary, but ensure you have the following information available.

When explaining your sample, ensure you identify who the target population was, the size and demographics of your sample, the location of sample participants, and the sampling design you used to obtain your sample. Pay attention to justifying the rationale for the decisions you made in this section, and provide relevant citations to support these decisions.

(Note: For advice on how to avoid bias when referring to people or groups in this section, see this tutorial , for advice on selecting your sample, please see here ).

Instruments/Collection Method

In this section, you are both indicating the measures you used to answer your research questions and how they will measure the focus of your research (variables, cause-effect relationship, etc.). Data collection methods can include interviews, surveys, archival data, focus groups, ethnography, and much more. If you are using assessments or other instruments (ex: standardized interview protocols) as part of your data collection methods, information should be provided about the instruments themselves (reliability and validity in your population and in measuring your variables) and the relevancy for use in your study. For additional information on methods, please see here .

For qualitative research: Explain the appropriateness of the measure you chose (how did you ensure you were selecting the ‘best’ option?), the measurement characteristics of the instrument(s), and the administration and scoring of the measures. (See here for further information).

For qualitative research: Explain the training and practice of the observer, indicate instrument type (structured or unstructured), and include opening questions as well as examples of some sub-questions for your research. (Include the full set of questions used as an appendix). (See here for further information)

In this section, you will explain how you implemented your methods. Consider aspects such as what steps you took to contact your sample (or access your data), to gain their participation, to protect their anonymity/ensure confidentiality or any other ethical considerations you made, and how you administered the instruments.

(Note: If you provided participants with any documentation (recruitment letter, survey, etc., copies of these should be added as appendixes).

Example of a research project:

Study was conducted with undergraduate students to test the effectiveness of the wise interventional strategy approach in feedback on the perception of positive bias., some examples of what i would consider writing in this section include:.

Note: By the time you finish writing this section, your reader should be able to know when, where, and how you collected the data.

Step: Pre-contact

Information Included: How I chose the educator(s) I worked with, selected the classes (and when they ran), identified the assignment to use, created a benefit for student participant (extra credit/mandatory participation/etc.), information I needed to collect from the students, if the instructor would see the feedback provided to students, if I needed the school’s approval and the instructors or just the instructor, and more

Step: Contact

Information Included: How much information the educator provided to the students before the study (protect the validity of the results), how the students opted into the study

Step: Process

Information Included: How I set up the study so that the reviews of the assignments were blind reviews, how I protected student anonymity when providing feedback, how I stored the data, the timeline of providing feedback, the timeline of when students could submit revised versions for grading, the rubric used to assess grading, and how I collected revisions from the instructor.

3. What do I Include in My Data Analysis Section?

In this section, you will explain how you analyzed your data. Ensure that you are not getting into the results of what your analysis determined. You are only explaining how you analyzed the data in this section.

For quantitative research: Explain what you did prior to the analysis (did you have to sift through to remove any outliers, did you have to ensure you were not missing data, etc.), how you conducted the analysis (what software or tool did you use), what test did you use (T-test, linear regression, etc.), and what equation did you use within the test construct. Indicate what information that analysis provided you (ex: determining relationships, causal links).

For qualitative research: Explain what you did after collecting the responses from your participants. It is important that you outline the process you will use to analyze the data (ex: inductive analysis, discourse analysis), any coding methods, or tools that will be used to classify the data. Typically, people will transcribe their responses, identify a type of analysis (thematic, content, discourse), and code the information to determine patterns and relationships. It is also important to outline how the researcher will avoid bias in their analysis of the data.

Did I Include All of the Information I Need?

To double-check if you have added all of the information you need, please see this checklist as a guide. (Note: this is to help you self-assess in general but is not meant to be an exhaustive list – download to check off the boxes as you go). It is also a good idea to do one last check for alignment with your other chapters!

Please see the following tutorials created by methodologists to support you in the curation of this chapter. • How to Write the Methodology Section • Quantitative Studies: Methodology Considerations • Qualitative Studies: Methodology Considerations

Dissertation Structure & Layout 101: How to structure your dissertation, thesis or research project.

By: Derek Jansen (MBA) Reviewed By: David Phair (PhD) | July 2019

So, you’ve got a decent understanding of what a dissertation is , you’ve chosen your topic and hopefully you’ve received approval for your research proposal . Awesome! Now its time to start the actual dissertation or thesis writing journey.

To craft a high-quality document, the very first thing you need to understand is dissertation structure . In this post, we’ll walk you through the generic dissertation structure and layout, step by step. We’ll start with the big picture, and then zoom into each chapter to briefly discuss the core contents. If you’re just starting out on your research journey, you should start with this post, which covers the big-picture process of how to write a dissertation or thesis .

*The Caveat *

In this post, we’ll be discussing a traditional dissertation/thesis structure and layout, which is generally used for social science research across universities, whether in the US, UK, Europe or Australia. However, some universities may have small variations on this structure (extra chapters, merged chapters, slightly different ordering, etc).

So, always check with your university if they have a prescribed structure or layout that they expect you to work with. If not, it’s safe to assume the structure we’ll discuss here is suitable. And even if they do have a prescribed structure, you’ll still get value from this post as we’ll explain the core contents of each section.  

Overview: S tructuring a dissertation or thesis

• Acknowledgements page
• Abstract (or executive summary)
• Table of contents , list of figures and tables
• Chapter 1: Introduction
• Chapter 2: Literature review
• Chapter 3: Methodology
• Chapter 4: Results
• Chapter 5: Discussion
• Chapter 6: Conclusion
• Reference list

As I mentioned, some universities will have slight variations on this structure. For example, they want an additional “personal reflection chapter”, or they might prefer the results and discussion chapter to be merged into one. Regardless, the overarching flow will always be the same, as this flow reflects the research process , which we discussed here – i.e.:

• The introduction chapter presents the core research question and aims .
• The literature review chapter assesses what the current research says about this question.
• The methodology, results and discussion chapters go about undertaking new research about this question.
• The conclusion chapter (attempts to) answer the core research question .

In other words, the dissertation structure and layout reflect the research process of asking a well-defined question(s), investigating, and then answering the question – see below.

To restate that – the structure and layout of a dissertation reflect the flow of the overall research process . This is essential to understand, as each chapter will make a lot more sense if you “get” this concept. If you’re not familiar with the research process, read this post before going further.

Right. Now that we’ve covered the big picture, let’s dive a little deeper into the details of each section and chapter. Oh and by the way, you can also grab our free dissertation/thesis template here to help speed things up.

The title page of your dissertation is the very first impression the marker will get of your work, so it pays to invest some time thinking about your title. But what makes for a good title? A strong title needs to be 3 things:

• Succinct (not overly lengthy or verbose)
• Specific (not vague or ambiguous)
• Representative of the research you’re undertaking (clearly linked to your research questions)

Typically, a good title includes mention of the following:

• The broader area of the research (i.e. the overarching topic)
• The specific focus of your research (i.e. your specific context)
• Indication of research design (e.g. quantitative , qualitative , or  mixed methods ).

For example:

A quantitative investigation [research design] into the antecedents of organisational trust [broader area] in the UK retail forex trading market [specific context/area of focus].

Again, some universities may have specific requirements regarding the format and structure of the title, so it’s worth double-checking expectations with your institution (if there’s no mention in the brief or study material).

Acknowledgements

This page provides you with an opportunity to say thank you to those who helped you along your research journey. Generally, it’s optional (and won’t count towards your marks), but it is academic best practice to include this.

So, who do you say thanks to? Well, there’s no prescribed requirements, but it’s common to mention the following people:

• Your dissertation supervisor or committee.
• Any professors, lecturers or academics that helped you understand the topic or methodologies.
• Any tutors, mentors or advisors.
• Your family and friends, especially spouse (for adult learners studying part-time).

There’s no need for lengthy rambling. Just state who you’re thankful to and for what (e.g. thank you to my supervisor, John Doe, for his endless patience and attentiveness) – be sincere. In terms of length, you should keep this to a page or less.

Abstract or executive summary

The dissertation abstract (or executive summary for some degrees) serves to provide the first-time reader (and marker or moderator) with a big-picture view of your research project. It should give them an understanding of the key insights and findings from the research, without them needing to read the rest of the report – in other words, it should be able to stand alone .

For it to stand alone, your abstract should cover the following key points (at a minimum):

• Your research questions and aims – what key question(s) did your research aim to answer?
• Your methodology – how did you go about investigating the topic and finding answers to your research question(s)?
• Your findings – following your own research, what did do you discover?
• Your conclusions – based on your findings, what conclusions did you draw? What answers did you find to your research question(s)?

So, in much the same way the dissertation structure mimics the research process, your abstract or executive summary should reflect the research process, from the initial stage of asking the original question to the final stage of answering that question.

In practical terms, it’s a good idea to write this section up last , once all your core chapters are complete. Otherwise, you’ll end up writing and rewriting this section multiple times (just wasting time). For a step by step guide on how to write a strong executive summary, check out this post .

Need a helping hand?

Table of contents

This section is straightforward. You’ll typically present your table of contents (TOC) first, followed by the two lists – figures and tables. I recommend that you use Microsoft Word’s automatic table of contents generator to generate your TOC. If you’re not familiar with this functionality, the video below explains it simply:

If you find that your table of contents is overly lengthy, consider removing one level of depth. Oftentimes, this can be done without detracting from the usefulness of the TOC.

Right, now that the “admin” sections are out of the way, its time to move on to your core chapters. These chapters are the heart of your dissertation and are where you’ll earn the marks. The first chapter is the introduction chapter – as you would expect, this is the time to introduce your research…

It’s important to understand that even though you’ve provided an overview of your research in your abstract, your introduction needs to be written as if the reader has not read that (remember, the abstract is essentially a standalone document). So, your introduction chapter needs to start from the very beginning, and should address the following questions:

• What will you be investigating (in plain-language, big picture-level)?
• Why is that worth investigating? How is it important to academia or business? How is it sufficiently original?
• What are your research aims and research question(s)? Note that the research questions can sometimes be presented at the end of the literature review (next chapter).
• What is the scope of your study? In other words, what will and won’t you cover ?
• How will you approach your research? In other words, what methodology will you adopt?
• How will you structure your dissertation? What are the core chapters and what will you do in each of them?

These are just the bare basic requirements for your intro chapter. Some universities will want additional bells and whistles in the intro chapter, so be sure to carefully read your brief or consult your research supervisor.

If done right, your introduction chapter will set a clear direction for the rest of your dissertation. Specifically, it will make it clear to the reader (and marker) exactly what you’ll be investigating, why that’s important, and how you’ll be going about the investigation. Conversely, if your introduction chapter leaves a first-time reader wondering what exactly you’ll be researching, you’ve still got some work to do.

Now that you’ve set a clear direction with your introduction chapter, the next step is the literature review . In this section, you will analyse the existing research (typically academic journal articles and high-quality industry publications), with a view to understanding the following questions:

• What does the literature currently say about the topic you’re investigating?
• Is the literature lacking or well established? Is it divided or in disagreement?
• How does your research fit into the bigger picture?
• How does your research contribute something original?
• How does the methodology of previous studies help you develop your own?

Depending on the nature of your study, you may also present a conceptual framework towards the end of your literature review, which you will then test in your actual research.

Again, some universities will want you to focus on some of these areas more than others, some will have additional or fewer requirements, and so on. Therefore, as always, its important to review your brief and/or discuss with your supervisor, so that you know exactly what’s expected of your literature review chapter.

Now that you’ve investigated the current state of knowledge in your literature review chapter and are familiar with the existing key theories, models and frameworks, its time to design your own research. Enter the methodology chapter – the most “science-ey” of the chapters…

In this chapter, you need to address two critical questions:

• Exactly HOW will you carry out your research (i.e. what is your intended research design)?
• Exactly WHY have you chosen to do things this way (i.e. how do you justify your design)?

Remember, the dissertation part of your degree is first and foremost about developing and demonstrating research skills . Therefore, the markers want to see that you know which methods to use, can clearly articulate why you’ve chosen then, and know how to deploy them effectively.

Importantly, this chapter requires detail – don’t hold back on the specifics. State exactly what you’ll be doing, with who, when, for how long, etc. Moreover, for every design choice you make, make sure you justify it.

In practice, you will likely end up coming back to this chapter once you’ve undertaken all your data collection and analysis, and revise it based on changes you made during the analysis phase. This is perfectly fine. Its natural for you to add an additional analysis technique, scrap an old one, etc based on where your data lead you. Of course, I’m talking about small changes here – not a fundamental switch from qualitative to quantitative, which will likely send your supervisor in a spin!

You’ve now collected your data and undertaken your analysis, whether qualitative, quantitative or mixed methods. In this chapter, you’ll present the raw results of your analysis . For example, in the case of a quant study, you’ll present the demographic data, descriptive statistics, inferential statistics , etc.

Typically, Chapter 4 is simply a presentation and description of the data, not a discussion of the meaning of the data. In other words, it’s descriptive, rather than analytical – the meaning is discussed in Chapter 5. However, some universities will want you to combine chapters 4 and 5, so that you both present and interpret the meaning of the data at the same time. Check with your institution what their preference is.

Now that you’ve presented the data analysis results, its time to interpret and analyse them. In other words, its time to discuss what they mean, especially in relation to your research question(s).

What you discuss here will depend largely on your chosen methodology. For example, if you’ve gone the quantitative route, you might discuss the relationships between variables . If you’ve gone the qualitative route, you might discuss key themes and the meanings thereof. It all depends on what your research design choices were.

Most importantly, you need to discuss your results in relation to your research questions and aims, as well as the existing literature. What do the results tell you about your research questions? Are they aligned with the existing research or at odds? If so, why might this be? Dig deep into your findings and explain what the findings suggest, in plain English.

The final chapter – you’ve made it! Now that you’ve discussed your interpretation of the results, its time to bring it back to the beginning with the conclusion chapter . In other words, its time to (attempt to) answer your original research question s (from way back in chapter 1). Clearly state what your conclusions are in terms of your research questions. This might feel a bit repetitive, as you would have touched on this in the previous chapter, but its important to bring the discussion full circle and explicitly state your answer(s) to the research question(s).

Next, you’ll typically discuss the implications of your findings? In other words, you’ve answered your research questions – but what does this mean for the real world (or even for academia)? What should now be done differently, given the new insight you’ve generated?

Lastly, you should discuss the limitations of your research, as well as what this means for future research in the area. No study is perfect, especially not a Masters-level. Discuss the shortcomings of your research. Perhaps your methodology was limited, perhaps your sample size was small or not representative, etc, etc. Don’t be afraid to critique your work – the markers want to see that you can identify the limitations of your work. This is a strength, not a weakness. Be brutal!

This marks the end of your core chapters – woohoo! From here on out, it’s pretty smooth sailing.

The reference list is straightforward. It should contain a list of all resources cited in your dissertation, in the required format, e.g. APA , Harvard, etc.

It’s essential that you use reference management software for your dissertation. Do NOT try handle your referencing manually – its far too error prone. On a reference list of multiple pages, you’re going to make mistake. To this end, I suggest considering either Mendeley or Zotero. Both are free and provide a very straightforward interface to ensure that your referencing is 100% on point. I’ve included a simple how-to video for the Mendeley software (my personal favourite) below:

Some universities may ask you to include a bibliography, as opposed to a reference list. These two things are not the same . A bibliography is similar to a reference list, except that it also includes resources which informed your thinking but were not directly cited in your dissertation. So, double-check your brief and make sure you use the right one.

The very last piece of the puzzle is the appendix or set of appendices. This is where you’ll include any supporting data and evidence. Importantly, supporting is the keyword here.

Your appendices should provide additional “nice to know”, depth-adding information, which is not critical to the core analysis. Appendices should not be used as a way to cut down word count (see this post which covers how to reduce word count ). In other words, don’t place content that is critical to the core analysis here, just to save word count. You will not earn marks on any content in the appendices, so don’t try to play the system!

Time to recap…

And there you have it – the traditional dissertation structure and layout, from A-Z. To recap, the core structure for a dissertation or thesis is (typically) as follows:

• Acknowledgments page

Most importantly, the core chapters should reflect the research process (asking, investigating and answering your research question). Moreover, the research question(s) should form the golden thread throughout your dissertation structure. Everything should revolve around the research questions, and as you’ve seen, they should form both the start point (i.e. introduction chapter) and the endpoint (i.e. conclusion chapter).

I hope this post has provided you with clarity about the traditional dissertation/thesis structure and layout. If you have any questions or comments, please leave a comment below, or feel free to get in touch with us. Also, be sure to check out the rest of the  Grad Coach Blog .

Psst... there’s more!

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

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36 Comments

many thanks i found it very useful

Glad to hear that, Arun. Good luck writing your dissertation.

Such clear practical logical advice. I very much needed to read this to keep me focused in stead of fretting.. Perfect now ready to start my research!

what about scientific fields like computer or engineering thesis what is the difference in the structure? thank you very much

Thanks so much this helped me a lot!

Very helpful and accessible. What I like most is how practical the advice is along with helpful tools/ links.

Thanks Ade!

Thank you so much sir.. It was really helpful..

You’re welcome!

Hi! How many words maximum should contain the abstract?

Thank you so much 😊 Find this at the right moment

You’re most welcome. Good luck with your dissertation.

best ever benefit i got on right time thank you

Many times Clarity and vision of destination of dissertation is what makes the difference between good ,average and great researchers the same way a great automobile driver is fast with clarity of address and Clear weather conditions .

I guess Great researcher = great ideas + knowledge + great and fast data collection and modeling + great writing + high clarity on all these

You have given immense clarity from start to end.

Morning. Where will I write the definitions of what I’m referring to in my report?

Thank you so much Derek, I was almost lost! Thanks a tonnnn! Have a great day!

Thanks ! so concise and valuable

This was very helpful. Clear and concise. I know exactly what to do now.

Thank you for allowing me to go through briefly. I hope to find time to continue.

Really useful to me. Thanks a thousand times

Very interesting! It will definitely set me and many more for success. highly recommended.

Thank you soo much sir, for the opportunity to express my skills

Usefull, thanks a lot. Really clear

Very nice and easy to understand. Thank you .

That was incredibly useful. Thanks Grad Coach Crew!

My stress level just dropped at least 15 points after watching this. Just starting my thesis for my grad program and I feel a lot more capable now! Thanks for such a clear and helpful video, Emma and the GradCoach team!

Do we need to mention the number of words the dissertation contains in the main document?

It depends on your university’s requirements, so it would be best to check with them 🙂

Such a helpful post to help me get started with structuring my masters dissertation, thank you!

Great video; I appreciate that helpful information

It is so necessary or avital course

This blog is very informative for my research. Thank you

Doctoral students are required to fill out the National Research Council’s Survey of Earned Doctorates

wow this is an amazing gain in my life

This is so good

How can i arrange my specific objectives in my dissertation?

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Library Guides

Dissertations 4: methodology: structure.

• Introduction & Philosophy
• Methodology

Indicative Chapter Structure

If your department have given you guidance as to the structure of your methodology chapter, make sure you adhere to it.  

If not, a typical structure might look something like this (but not necessarily including all these elements, and in this order!): 

Introduction  

Research philosophy 

Methods:  

Primary and/or secondary sources? 

Quantitative or/and qualitative method(s)? 

Procedural method 

Ethics 

Reflection on the methods 

Justification 

Limitations and delimitations 

Conclusion 

Each section is addressed in the tabs of this guide.  

Always  check with your supervisor or consult the assignment guidelines posted on Blackboard if you are unsure about which sections you will need to include in your dissertation.   

Alternative Structures

The links below also suggest alternative structures: 

How to write Research Methodology 

How to Write Methodology for Dissertation 

The Method Chapter 

Writing the Methodology Chapter of a Qualitative Study 

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

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