project research

Illustration by James Round

How to plan a research project

Whether for a paper or a thesis, define your question, review the work of others – and leave yourself open to discovery.

by Brooke Harrington   + BIO

is professor of sociology at Dartmouth College in New Hampshire. Her research has won international awards both for scholarly quality and impact on public life. She has published dozens of articles and three books, most recently the bestseller Capital without Borders (2016), now translated into five languages.

Edited by Sam Haselby

Need to know

‘When curiosity turns to serious matters, it’s called research.’ – From Aphorisms (1880-1905) by Marie von Ebner-Eschenbach

Planning research projects is a time-honoured intellectual exercise: one that requires both creativity and sharp analytical skills. The purpose of this Guide is to make the process systematic and easy to understand. While there is a great deal of freedom and discovery involved – from the topics you choose, to the data and methods you apply – there are also some norms and constraints that obtain, no matter what your academic level or field of study. For those in high school through to doctoral students, and from art history to archaeology, research planning involves broadly similar steps, including: formulating a question, developing an argument or predictions based on previous research, then selecting the information needed to answer your question.

Some of this might sound self-evident but, as you’ll find, research requires a different way of approaching and using information than most of us are accustomed to in everyday life. That is why I include orienting yourself to knowledge-creation as an initial step in the process. This is a crucial and underappreciated phase in education, akin to making the transition from salaried employment to entrepreneurship: suddenly, you’re on your own, and that requires a new way of thinking about your work.

What follows is a distillation of what I’ve learned about this process over 27 years as a professional social scientist. It reflects the skills that my own professors imparted in the sociology doctoral programme at Harvard, as well as what I learned later on as a research supervisor for Ivy League PhD and MA students, and then as the author of award-winning scholarly books and articles. It can be adapted to the demands of both short projects (such as course term papers) and long ones, such as a thesis.

At its simplest, research planning involves the four distinct steps outlined below: orienting yourself to knowledge-creation; defining your research question; reviewing previous research on your question; and then choosing relevant data to formulate your own answers. Because the focus of this Guide is on planning a research project, as opposed to conducting a research project, this section won’t delve into the details of data-collection or analysis; those steps happen after you plan the project. In addition, the topic is vast: year-long doctoral courses are devoted to data and analysis. Instead, the fourth part of this section will outline some basic strategies you could use in planning a data-selection and analysis process appropriate to your research question.

Step 1: Orient yourself

Planning and conducting research requires you to make a transition, from thinking like a consumer of information to thinking like a producer of information. That sounds simple, but it’s actually a complex task. As a practical matter, this means putting aside the mindset of a student, which treats knowledge as something created by other people. As students, we are often passive receivers of knowledge: asked to do a specified set of readings, then graded on how well we reproduce what we’ve read.

Researchers, however, must take on an active role as knowledge producers . Doing research requires more of you than reading and absorbing what other people have written: you have to engage in a dialogue with it. That includes arguing with previous knowledge and perhaps trying to show that ideas we have accepted as given are actually wrong or incomplete. For example, rather than simply taking in the claims of an author you read, you’ll need to draw out the implications of those claims: if what the author is saying is true, what else does that suggest must be true? What predictions could you make based on the author’s claims?

In other words, rather than treating a reading as a source of truth – even if it comes from a revered source, such as Plato or Marie Curie – this orientation step asks you to treat the claims you read as provisional and subject to interrogation. That is one of the great pieces of wisdom that science and philosophy can teach us: that the biggest advances in human understanding have been made not by being correct about trivial things, but by being wrong in an interesting way . For example, Albert Einstein was wrong about quantum mechanics, but his arguments about it with his fellow physicist Niels Bohr have led to some of the biggest breakthroughs in science, even a century later.

Step 2: Define your research question

Students often give this step cursory attention, but experienced researchers know that formulating a good question is sometimes the most difficult part of the research planning process. That is because the precise language of the question frames the rest of the project. It’s therefore important to pose the question carefully, in a way that’s both possible to answer and likely to yield interesting results. Of course, you must choose a question that interests you, but that’s only the beginning of what’s likely to be an iterative process: most researchers come back to this step repeatedly, modifying their questions in light of previous research, resource limitations and other considerations.

Researchers face limits in terms of time and money. They, like everyone else, have to pose research questions that they can plausibly answer given the constraints they face. For example, it would be inadvisable to frame a project around the question ‘What are the roots of the Arab-Israeli conflict?’ if you have only a week to develop an answer and no background on that topic. That’s not to limit your imagination: you can come up with any question you’d like. But it typically does require some creativity to frame a question that you can answer well – that is, by investigating thoroughly and providing new insights – within the limits you face.

In addition to being interesting to you, and feasible within your resource constraints, the third and most important characteristic of a ‘good’ research topic is whether it allows you to create new knowledge. It might turn out that your question has already been asked and answered to your satisfaction: if so, you’ll find out in the next step of this process. On the other hand, you might come up with a research question that hasn’t been addressed previously. Before you get too excited about breaking uncharted ground, consider this: a lot of potentially researchable questions haven’t been studied for good reason ; they might have answers that are trivial or of very limited interest. This could include questions such as ‘Why does the area of a circle equal π r²?’ or ‘Did winter conditions affect Napoleon’s plans to invade Russia?’ Of course, you might be able to make the argument that a seemingly trivial question is actually vitally important, but you must be prepared to back that up with convincing evidence. The exercise in the ‘Learn More’ section below will help you think through some of these issues.

Finally, scholarly research questions must in some way lead to new and distinctive insights. For example, lots of people have studied gender roles in sports teams; what can you ask that hasn’t been asked before? Reinventing the wheel is the number-one no-no in this endeavour. That’s why the next step is so important: reviewing previous research on your topic. Depending on what you find in that step, you might need to revise your research question; iterating between your question and the existing literature is a normal process. But don’t worry: it doesn’t go on forever. In fact, the iterations taper off – and your research question stabilises – as you develop a firm grasp of the current state of knowledge on your topic.

Step 3: Review previous research

In academic research, from articles to books, it’s common to find a section called a ‘literature review’. The purpose of that section is to describe the state of the art in knowledge on the research question that a project has posed. It demonstrates that researchers have thoroughly and systematically reviewed the relevant findings of previous studies on their topic, and that they have something novel to contribute.

Your own research project should include something like this, even if it’s a high-school term paper. In the research planning process, you’ll want to list at least half a dozen bullet points stating the major findings on your topic by other people. In relation to those findings, you should be able to specify where your project could provide new and necessary insights. There are two basic rhetorical positions one can take in framing the novelty-plus-importance argument required of academic research:

  • Position 1 requires you to build on or extend a set of existing ideas; that means saying something like: ‘Person A has argued that X is true about gender; this implies Y, which has not yet been tested. My project will test Y, and if I find evidence to support it, that will change the way we understand gender.’
  • Position 2 is to argue that there is a gap in existing knowledge, either because previous research has reached conflicting conclusions or has failed to consider something important. For example, one could say that research on middle schoolers and gender has been limited by being conducted primarily in coeducational environments, and that findings might differ dramatically if research were conducted in more schools where the student body was all-male or all-female.

Your overall goal in this step of the process is to show that your research will be part of a larger conversation: that is, how your project flows from what’s already known, and how it advances, extends or challenges that existing body of knowledge. That will be the contribution of your project, and it constitutes the motivation for your research.

Two things are worth mentioning about your search for sources of relevant previous research. First, you needn’t look only at studies on your precise topic. For example, if you want to study gender-identity formation in schools, you shouldn’t restrict yourself to studies of schools; the empirical setting (schools) is secondary to the larger social process that interests you (how people form gender identity). That process occurs in many different settings, so cast a wide net. Second, be sure to use legitimate sources – meaning publications that have been through some sort of vetting process, whether that involves peer review (as with academic journal articles you might find via Google Scholar) or editorial review (as you’d find in well-known mass media publications, such as The Economist or The Washington Post ). What you’ll want to avoid is using unvetted sources such as personal blogs or Wikipedia. Why? Because anybody can write anything in those forums, and there is no way to know – unless you’re already an expert – if the claims you find there are accurate. Often, they’re not.

Step 4: Choose your data and methods

Whatever your research question is, eventually you’ll need to consider which data source and analytical strategy are most likely to provide the answers you’re seeking. One starting point is to consider whether your question would be best addressed by qualitative data (such as interviews, observations or historical records), quantitative data (such as surveys or census records) or some combination of both. Your ideas about data sources will, in turn, suggest options for analytical methods.

You might need to collect your own data, or you might find everything you need readily available in an existing dataset someone else has created. A great place to start is with a research librarian: university libraries always have them and, at public universities, those librarians can work with the public, including people who aren’t affiliated with the university. If you don’t happen to have a public university and its library close at hand, an ordinary public library can still be a good place to start: the librarians are often well versed in accessing data sources that might be relevant to your study, such as the census, or historical archives, or the Survey of Consumer Finances.

Because your task at this point is to plan research, rather than conduct it, the purpose of this step is not to commit you irrevocably to a course of action. Instead, your goal here is to think through a feasible approach to answering your research question. You’ll need to find out, for example, whether the data you want exist; if not, do you have a realistic chance of gathering the data yourself, or would it be better to modify your research question? In terms of analysis, would your strategy require you to apply statistical methods? If so, do you have those skills? If not, do you have time to learn them, or money to hire a research assistant to run the analysis for you?

Please be aware that qualitative methods in particular are not the casual undertaking they might appear to be. Many people make the mistake of thinking that only quantitative data and methods are scientific and systematic, while qualitative methods are just a fancy way of saying: ‘I talked to some people, read some old newspapers, and drew my own conclusions.’ Nothing could be further from the truth. In the final section of this guide, you’ll find some links to resources that will provide more insight on standards and procedures governing qualitative research, but suffice it to say: there are rules about what constitutes legitimate evidence and valid analytical procedure for qualitative data, just as there are for quantitative data.

Circle back and consider revising your initial plans

As you work through these four steps in planning your project, it’s perfectly normal to circle back and revise. Research planning is rarely a linear process. It’s also common for new and unexpected avenues to suggest themselves. As the sociologist Thorstein Veblen wrote in 1908 : ‘The outcome of any serious research can only be to make two questions grow where only one grew before.’ That’s as true of research planning as it is of a completed project. Try to enjoy the horizons that open up for you in this process, rather than becoming overwhelmed; the four steps, along with the two exercises that follow, will help you focus your plan and make it manageable.

Key points – How to plan a research project

  • Planning a research project is essential no matter your academic level or field of study. There is no one ‘best’ way to design research, but there are certain guidelines that can be helpfully applied across disciplines.
  • Orient yourself to knowledge-creation. Make the shift from being a consumer of information to being a producer of information.
  • Define your research question. Your question frames the rest of your project, sets the scope, and determines the kinds of answers you can find.
  • Review previous research on your question. Survey the existing body of relevant knowledge to ensure that your research will be part of a larger conversation.
  • Choose your data and methods. For instance, will you be collecting qualitative data, via interviews, or numerical data, via surveys?
  • Circle back and consider revising your initial plans. Expect your research question in particular to undergo multiple rounds of refinement as you learn more about your topic.

Good research questions tend to beget more questions. This can be frustrating for those who want to get down to business right away. Try to make room for the unexpected: this is usually how knowledge advances. Many of the most significant discoveries in human history have been made by people who were looking for something else entirely. There are ways to structure your research planning process without over-constraining yourself; the two exercises below are a start, and you can find further methods in the Links and Books section.

The following exercise provides a structured process for advancing your research project planning. After completing it, you’ll be able to do the following:

  • describe clearly and concisely the question you’ve chosen to study
  • summarise the state of the art in knowledge about the question, and where your project could contribute new insight
  • identify the best strategy for gathering and analysing relevant data

In other words, the following provides a systematic means to establish the building blocks of your research project.

Exercise 1: Definition of research question and sources

This exercise prompts you to select and clarify your general interest area, develop a research question, and investigate sources of information. The annotated bibliography will also help you refine your research question so that you can begin the second assignment, a description of the phenomenon you wish to study.

Jot down a few bullet points in response to these two questions, with the understanding that you’ll probably go back and modify your answers as you begin reading other studies relevant to your topic:

  • What will be the general topic of your paper?
  • What will be the specific topic of your paper?

b) Research question(s)

Use the following guidelines to frame a research question – or questions – that will drive your analysis. As with Part 1 above, you’ll probably find it necessary to change or refine your research question(s) as you complete future assignments.

  • Your question should be phrased so that it can’t be answered with a simple ‘yes’ or ‘no’.
  • Your question should have more than one plausible answer.
  • Your question should draw relationships between two or more concepts; framing the question in terms of How? or What? often works better than asking Why ?

c) Annotated bibliography

Most or all of your background information should come from two sources: scholarly books and journals, or reputable mass media sources. You might be able to access journal articles electronically through your library, using search engines such as JSTOR and Google Scholar. This can save you a great deal of time compared with going to the library in person to search periodicals. General news sources, such as those accessible through LexisNexis, are acceptable, but should be cited sparingly, since they don’t carry the same level of credibility as scholarly sources. As discussed above, unvetted sources such as blogs and Wikipedia should be avoided, because the quality of the information they provide is unreliable and often misleading.

To create an annotated bibliography, provide the following information for at least 10 sources relevant to your specific topic, using the format suggested below.

Name of author(s):
Publication date:
Title of book, chapter, or article:
If a chapter or article, title of journal or book where they appear:
Brief description of this work, including main findings and methods ( c 75 words):
Summary of how this work contributes to your project ( c 75 words):
Brief description of the implications of this work ( c 25 words):
Identify any gap or controversy in knowledge this work points up, and how your project could address those problems ( c 50 words):

Exercise 2: Towards an analysis

Develop a short statement ( c 250 words) about the kind of data that would be useful to address your research question, and how you’d analyse it. Some questions to consider in writing this statement include:

  • What are the central concepts or variables in your project? Offer a brief definition of each.
  • Do any data sources exist on those concepts or variables, or would you need to collect data?
  • Of the analytical strategies you could apply to that data, which would be the most appropriate to answer your question? Which would be the most feasible for you? Consider at least two methods, noting their advantages or disadvantages for your project.

Links & books

One of the best texts ever written about planning and executing research comes from a source that might be unexpected: a 60-year-old work on urban planning by a self-trained scholar. The classic book The Death and Life of Great American Cities (1961) by Jane Jacobs (available complete and free of charge via this link ) is worth reading in its entirety just for the pleasure of it. But the final 20 pages – a concluding chapter titled ‘The Kind of Problem a City Is’ – are really about the process of thinking through and investigating a problem. Highly recommended as a window into the craft of research.

Jacobs’s text references an essay on advancing human knowledge by the mathematician Warren Weaver. At the time, Weaver was director of the Rockefeller Foundation, in charge of funding basic research in the natural and medical sciences. Although the essay is titled ‘A Quarter Century in the Natural Sciences’ (1960) and appears at first blush to be merely a summation of one man’s career, it turns out to be something much bigger and more interesting: a meditation on the history of human beings seeking answers to big questions about the world. Weaver goes back to the 17th century to trace the origins of systematic research thinking, with enthusiasm and vivid anecdotes that make the process come alive. The essay is worth reading in its entirety, and is available free of charge via this link .

For those seeking a more in-depth, professional-level discussion of the logic of research design, the political scientist Harvey Starr provides insight in a compact format in the article ‘Cumulation from Proper Specification: Theory, Logic, Research Design, and “Nice” Laws’ (2005). Starr reviews the ‘research triad’, consisting of the interlinked considerations of formulating a question, selecting relevant theories and applying appropriate methods. The full text of the article, published in the scholarly journal Conflict Management and Peace Science , is available, free of charge, via this link .

Finally, the book Getting What You Came For (1992) by Robert Peters is not only an outstanding guide for anyone contemplating graduate school – from the application process onward – but it also includes several excellent chapters on planning and executing research, applicable across a wide variety of subject areas. It was an invaluable resource for me 25 years ago, and it remains in print with good reason; I recommend it to all my students, particularly Chapter 16 (‘The Thesis Topic: Finding It’), Chapter 17 (‘The Thesis Proposal’) and Chapter 18 (‘The Thesis: Writing It’).

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How to Get Started With a Research Project

Last Updated: October 3, 2023 Fact Checked

This article was co-authored by Chris Hadley, PhD . Chris Hadley, PhD is part of the wikiHow team and works on content strategy and data and analytics. Chris Hadley earned his PhD in Cognitive Psychology from UCLA in 2006. Chris' academic research has been published in numerous scientific journals. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 311,473 times.

You'll be required to undertake and complete research projects throughout your academic career and even, in many cases, as a member of the workforce. Don't worry if you feel stuck or intimidated by the idea of a research project, with care and dedication, you can get the project done well before the deadline!

Development and Foundation

Step 1 Brainstorm an idea or identify a problem or question.

  • Don't hesitate while writing down ideas. You'll end up with some mental noise on the paper – silly or nonsensical phrases that your brain just pushes out. That's fine. Think of it as sweeping the cobwebs out of your attic. After a minute or two, better ideas will begin to form (and you might have a nice little laugh at your own expense in the meantime).

Step 2 Use the tools you've already been given.

  • Some instructors will even provide samples of previously successful topics if you ask for them. Just be careful that you don't end up stuck with an idea you want to do, but are afraid to do because you know someone else did it before.

Step 4 Think from all angles.

  • For example, if your research topic is “urban poverty,” you could look at that topic across ethnic or sexual lines, but you could also look into corporate wages, minimum wage laws, the cost of medical benefits, the loss of unskilled jobs in the urban core, and on and on. You could also try comparing and contrasting urban poverty with suburban or rural poverty, and examine things that might be different about both areas, such as diet and exercise levels, or air pollution.

Step 5 Synthesize specific topics.

  • Think in terms of questions you want answered. A good research project should collect information for the purpose of answering (or at least attempting to answer) a question. As you review and interconnect topics, you'll think of questions that don't seem to have clear answers yet. These questions are your research topics.

Step 7 Brush across information you have access to.

  • Don't limit yourself to libraries and online databases. Think in terms of outside resources as well: primary sources, government agencies, even educational TV programs. If you want to know about differences in animal population between public land and an Indian reservation, call the reservation and see if you can speak to their department of fish and wildlife.
  • If you're planning to go ahead with original research, that's great – but those techniques aren't covered in this article. Instead, speak with qualified advisors and work with them to set up a thorough, controlled, repeatable process for gathering information.

Step 8 Clearly define your project.

  • If your plan comes down to “researching the topic,” and there aren't any more specific things you can say about it, write down the types of sources you plan to use instead: books (library or private?), magazines (which ones?), interviews, and so on. Your preliminary research should have given you a solid idea of where to begin.

Expanding Your Idea with Research

Step 1 Start with the basics.

  • It's generally considered more convincing to source one item from three different authors who all agree on it than it is to rely too heavily on one book. Go for quantity at least as much as quality. Be sure to check citations, endnotes, and bibliographies to get more potential sources (and see whether or not all your authors are just quoting the same, older author).
  • Writing down your sources and any other relevant details (such as context) around your pieces of information right now will save you lots of trouble in the future.

Step 2 Move outward.

  • Use many different queries to get the database results you want. If one phrasing or a particular set of words doesn't yield useful results, try rephrasing it or using synonymous terms. Online academic databases tend to be dumber than the sum of their parts, so you'll have to use tangentially related terms and inventive language to get all the results you want.

Step 3 Gather unusual sources.

  • If it's sensible, consider heading out into the field and speaking to ordinary people for their opinions. This isn't always appropriate (or welcomed) in a research project, but in some cases, it can provide you with some excellent perspective for your research.
  • Review cultural artifacts as well. In many areas of study, there's useful information on attitudes, hopes, and/or concerns of people in a particular time and place contained within the art, music, and writing they produced. One has only to look at the woodblock prints of the later German Expressionists, for example, to understand that they lived in a world they felt was often dark, grotesque, and hopeless. Song lyrics and poetry can likewise express strong popular attitudes.

Step 4 Review and trim.

Expert Q&A

Chris Hadley, PhD

  • Start early. The foundation of a great research project is the research, which takes time and patience to gather even if you aren't performing any original research of your own. Set aside time for it whenever you can, at least until your initial gathering phase is complete. Past that point, the project should practically come together on its own. Thanks Helpful 1 Not Helpful 0
  • When in doubt, write more, rather than less. It's easier to pare down and reorganize an overabundance of information than it is to puff up a flimsy core of facts and anecdotes. Thanks Helpful 1 Not Helpful 0

project research

  • Respect the wishes of others. Unless you're a research journalist, it's vital that you yield to the wishes and requests of others before engaging in original research, even if it's technically ethical. Many older American Indians, for instance, harbor a great deal of cultural resentment towards social scientists who visit reservations for research, even those invited by tribal governments for important reasons such as language revitalization. Always tread softly whenever you're out of your element, and only work with those who want to work with you. Thanks Helpful 8 Not Helpful 2
  • Be mindful of ethical concerns. Especially if you plan to use original research, there are very stringent ethical guidelines that must be followed for any credible academic body to accept it. Speak to an advisor (such as a professor) about what you plan to do and what steps you should take to verify that it will be ethical. Thanks Helpful 6 Not Helpful 2

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  • ↑ http://www.butte.edu/departments/cas/tipsheets/research/research_paper.html
  • ↑ https://www.nhcc.edu/academics/library/doing-library-research/basic-steps-research-process
  • ↑ https://library.sacredheart.edu/c.php?g=29803&p=185905
  • ↑ https://owl.purdue.edu/owl/general_writing/common_writing_assignments/research_papers/choosing_a_topic.html
  • ↑ https://www.unr.edu/writing-speaking-center/student-resources/writing-speaking-resources/using-an-interview-in-a-research-paper
  • ↑ https://www.science.org/content/article/how-review-paper

About This Article

Chris Hadley, PhD

The easiest way to get started with a research project is to use your notes and other materials to come up with topics that interest you. Research your favorite topic to see if it can be developed, and then refine it into a research question. Begin thoroughly researching, and collect notes and sources. To learn more about finding reliable and helpful sources while you're researching, continue reading! Did this summary help you? Yes No

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Research Design | Step-by-Step Guide with Examples

Published on 5 May 2022 by Shona McCombes . Revised on 20 March 2023.

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

  • Your overall aims and approach
  • The type of research design you’ll use
  • Your sampling methods or criteria for selecting subjects
  • Your data collection methods
  • The procedures you’ll follow to collect data
  • Your data analysis methods

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

Table of contents

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

  • Introduction

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

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

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

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

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

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

Practical and ethical considerations when designing research

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

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

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

Prevent plagiarism, run a free check.

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

Types of quantitative research designs

Quantitative designs can be split into four main types. Experimental and   quasi-experimental designs allow you to test cause-and-effect relationships, while descriptive and correlational designs allow you to measure variables and describe relationships between them.

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

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

Types of qualitative research designs

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

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

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

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

Defining the population

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

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

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

Sampling methods

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

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

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

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

Case selection in qualitative research

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

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

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

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

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

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

Survey methods

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

Observation methods

Observations allow you to collect data unobtrusively, observing characteristics, behaviours, or social interactions without relying on self-reporting.

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

Other methods of data collection

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

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

Secondary data

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

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

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

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

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

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

Operationalisation

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

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

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

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

Reliability and validity

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

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

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

Sampling procedures

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

That means making decisions about things like:

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

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

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

Data management

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

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

Keeping your data well organised will save time when it comes to analysing them. It can also help other researchers validate and add to your findings.

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

Quantitative data analysis

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

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

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

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

Using inferential statistics , you can:

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

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

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

Qualitative data analysis

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

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

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

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.

Operationalisation means turning abstract conceptual ideas into measurable observations.

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

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

The research methods you use depend on the type of data you need to answer your research question .

  • If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
  • If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
  • If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

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Shona McCombes

Shona McCombes