research question in chapter 1

• Introduction to Problem Statements, Purpose Statements, and Research Questions

Worksheets and Guides

Chapter 1 playlist.

• Student Experience Feedback Buttons
• Narrowing Your Topic
• Problem Statement
• Purpose Statement
• Conceptual Framework
• Theoretical Framework
• Quantitative Research Questions This link opens in a new window
• Qualitative Research Questions This link opens in a new window
• Qualitative & Quantitative Research Support with the ASC This link opens in a new window
• Library Research Consultations This link opens in a new window

Jump to DSE Guide

Need help ask us.

Chapter 1 introduces the research problem and the evidence supporting the existence of the problem. It outlines an initial review of the literature on the study topic and articulates the purpose of the study. The definitions of any technical terms necessary for the reader to understand are essential. Chapter 1 also presents the research questions and theoretical foundation (Ph.D.) or conceptual framework (Applied Doctorate) and provides an overview of the research methods (qualitative or quantitative) being used in the study.  

• Research Feasibility Checklist Use this checklist to make sure your study will be feasible, reasonable, justifiable, and necessary.
• Alignment Worksheet Use this worksheet to make sure your problem statement, purpose, and research questions are aligned. Alignment indicates the degree to which the purpose of the study follows logically from the problem statement; and the degree to which the research questions help address the study’s purpose. Alignment is important because it helps ensure that the research study is well-designed and based on logical arguments.
• SOBE Research Design and Chapter 1 Checklist If you are in the School of Business and Economics (SOBE), use this checklist one week before the Communication and Research Design Checkpoint. Work with your Chair to determine if you need to complete this.

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• Last Updated: Apr 24, 2023 1:37 PM
• URL: https://resources.nu.edu/c.php?g=1006886

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 (for free)

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

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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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Scientific Writing for Health Research

Chapter 1 research question.

The first step in conducting a scientific study is to develop a research question; however, this can be a difficult process. Research questions organize and direct the study, communicate the research study’s goal to the readers, define the study’s boundaries and limitations, and inform researchers on how to conduct the study. A good research question can serve all of these purposes, but developing a “good” research question can be difficult and time-consuming. A good research question should address the clinical or population health problem under investigation. Furthermore, the significance of a study’s findings is determined by how well it addresses the research question; therefore, not asking the “right” research question can jeopardize the validity of the whole study.

Generally, the process of formulating a new research question begins with a public health or clinical problem that needs to be addressed. In health sciences research, the rationale for conducting a research study is typically to address at least one of three issues: the existing evidence is scarce, the current literature contains conflicting evidence, or the evidence base can be improved ( Fandino 2019 ) . As a result, conducting a thorough literature search on the topic of interest is frequently required in order to formulate a good research question. In addition, the answers to the research question should address an aspect of the specific problem that was identified, and be supportive of the study’s rationale. In many instances, this requires narrowing and specifying the research question from a broader, more general question. It has previously been suggested that using a PICOT (population, intervention, comparator, outcome and time frame) framework can help researchers formulate a good research question and can ensure higher quality reporting in studies ( Thabane et al. 2009 ; Rios, Ye, and Thabane 2010 ) . A well-structured research question will guide the implementation of the study as well as the reporting of the results. The FINER criteria may also be used to assess the quality of the research question and refine it as needed ( Thabane et al. 2009 ) . In this chapter, we discuss the PICOT framework and FINER criteria for developing a good research question in population and public health research.

1.1 Framing a research question using the PICOT framework

Formulating and refining the research question using the PICOT framework can inform which study design is most appropriate, what types of data should be collected and what types of analytical methods are most suitable to answer the research question. The framework has many different variations, but the general framework for studies in health research is as follows:

Table 1: Key elements and guiding questions for the PICOT framework

1.2 Evaluating research questions using FINER criteria

Once the research question is developed using the PICOT framework, the FINER criteria can be used to assess the quality of the research question and determine if the research is feasible.

Table 2: Key elements and guiding questions for the FINER criteria

1.3 Tips for formulating a good research question

A research question needs to be aligned with the data, methods and results. In addition, a good research question should have the following characteristics: clarity, specificity, empirical support, and relevance. Questions in population and public health research typically ask about phenomena related to health and may focus on comparisons, associations, relationships, or descriptions of variables ( Creswell and Creswell 2017 ) . Once you have a broad, general idea of the question you want to investigate, try to describe the goal of the research study as precisely as possible, for example, the gap in knowledge you want to fill or the new evidence you want to generate for a question previously considered in the literature ( Vandenbroucke and Pearce 2018 ) . Determining this objective can be helpful when deciding what types of results you need to present. Vandenbroucke and Pearce ( Vandenbroucke and Pearce 2018 ) advise describing what table or figure is required to achieve the goal. For example, what table or figure would be needed to fill the knowledge gap. Following this process, the questions will become clearer and guide what types of study design and methods are required to achieve the study objective and attain results.

The most common pitfalls when developing research questions are that the questions incorporate the methods or the study’s expected outcomes ( Mayo, Asano, and Pamela Barbic 2013 ) . Furthermore, the clarity of the research question can be impeded by the lack of a clear parameter to assess the relationship or association between exposure and outcome ( Mayo, Asano, and Pamela Barbic 2013 ) .

We propose the following overall roadmap for developing a good research question:

• Gain an understanding of the research context
• Experiment with a few different PICOT(S) combinations
• Choose the best set of combinations and narrow the research question
• Use the FINER criteria to evaluate the research question’s quality
• “Prune” the research question by removing any extraneous details ( Vandenbroucke and Pearce 2018 )

A good research question can inform the study objective, data collection, methodology and the relevance of the findings. Not having a good research question can create confusion for readers and reviewers, make the research aimless and the interpretation of the results may be difficult or pointless. Therefore, developing a clear, well-structured research question is a critical step in any scientific investigation.

1.4 Statistical analysis plans

Statistical analysis plans (SAP) are also known as data analysis plans (DAP) or reporting analysis plans (RAP). A statistical analysis plan describes the study variables and the plan for analyzing a data before conducting the analysis; this is essentially the strategy for connecting the study objective to the data analysis that will answer the research question. SAPs have been used in biomedical research and in clinical trials for many years; statistical analysis plans for clinical trials are registered and made publicly available in repositories such as ClinicalTrials.gov . In fact, the National Institutes of Health (NIH) in the United States established policies for reporting NIH-funded clinical trials in 2016, requiring researchers to report full protocol and statistical analysis plan, along with levels of specification for outcome measures, information about adverse events and collection method, and baseline information and characteristics associated with primary outcome measures ( Zarin et al. 2016 ) . Pre-registering SAPs can prevent “P-value hacking” , which can occur when researchers “shop around for a statistical test to give them the P-value that they love” ( Yuan et al. 2019 ) . By registering pre-specified SAPs, researchers can help improve the study reproducibility and reduce bias ( Kahan et al. 2020 ) .

In observational studies, SAPs are much less adopted compared to clinical trials ( Thor et al. 2020 ) ; however, the discussion around its use and value have been growing. In this chapter, we discuss the use of SAPs for observational studies, and propose some key components of SAP for observational studies.

1.4.1 The value of statistical analysis plans in observational studies

Many observational studies are based on large datasets, or “big data,” which is defined as heterogeneous datasets linked to a single dataset, with a large number of observations and variables, and that is either real-time or frequently updated ( Ehrenstein et al. 2017 ) . With these big data and powerful statistical software and methods, finding statistically significant associations without pre-established study objectives, research questions and hypotheses has become easier ( Yuan et al. 2019 ) . These types of analyses can produce statistically significant findings without implications to clinical relevance or justification. SAPs can be useful in ensuring that the analytical methods are planned ahead of time in relation to the research question and objectives, and that this procedure is transparent.

As the findings from observational studies may have an impact on public health policies, guidelines and decision-making, it is critical to ensure that these studies are of high standard, that analyses are pre-specified based on relevance to public health, and that they are replicable. When there is no pre-established SAP specifying the primary outcome variable, outcome reporting bias can occur ( Cafri and Paxton 2018 ) . Many efforts have been made to reduce reporting bias in observational studies, such as STROBE guidelines ( Von Elm et al. 2007 ) . The use of SAPs has also been suggested, and that only the variables that researchers pre-specified as variables of interest be made available to them to limit post hoc analyses ( Thomas and Peterson 2012 ; Williams et al. 2010 ) . Some even argue that SAPs should be required even before obtaining data, during the application stage of data access ( Trinh and Sun 2013 ; Hiemstra et al. 2019 ) . In fact, to obtain access to big data, it is often required to submit a data request form that contains some key elements of a SAP ( NHS Digital 2021 ; Population Data BC 2021 ) .

SAPs also have an important role in identifying potential biases, such as selection bias (based on the inclusion/exclusion criteria) or measurement bias, and can help researchers plan how to minimize and address these biases.

1.4.2 Guide on writing an SAP for observational studies

Based on the guidelines for SAP for clinical trials ( Gamble et al. 2017 ) and literature suggesting its’ adaptation for observational studies ( Yuan et al. 2019 ; Thomas and Peterson 2012 ; Hiemstra et al. 2019 ) , we suggest the following four key components for writing SAP for observational studies in health sciences research:

Study objectives and hypotheses

• Broad research area, study background and rationale
• Research question (e.g. using PICOT framework and FINER criteria)

Study population

• Study design (e.g. cross-sectional, prospective cohort)
• Study sample and inclusion/exclusion criteria
• Study period (time points under consideration in the data source)

Study variables: definitions, types, how they are measured

• Outcome variables
• Explanatory/exposure variables
• Covariates (e.g. mediators, colliders, confounders)

Statistical analysis methods

• Defined level for statistical significance
• Plans for handling missing data, correlation, bias and confounding, and repetitive analyses
• Details on model building and variable selection
• Details on additional methods if model assumptions do not hold (e.g. normality, proportional hazards)
• Strategies for interaction or subgroup analysis and sensitivity analyses

Finally, SAPs can be useful in observational studies because they encourage detailed and rigorous planning of the study rather than disorganized and spontaneous data analysis. They can also optimize the resources to focus on the right methods for the research questions, and ensure methodological transparency and replicability of findings. We propose the following two broad questions that can be used to determine whether the SAP is appropriate:

• Does the SAP help in answering the research question or achieving the original study objective?
• Are the planned analyses appropriate in the context of the research question?

AP ® Research Handbook

Chapter 1 research question.

You can label chapter and section titles using {#label} after them, e.g., we can reference Chapter 1 . If you do not manually label them, there will be automatic labels anyway, e.g., Chapter 8 .

Figures and tables with captions will be placed in figure and table environments, respectively.

Exercises for ‘Introduction to The New Statistics’

Chapter 1 asking and answering research questions.

If you prefer to use for the exercises your phone or tablet, scan the associated QR code .

1.1 Interactive Video

1.1.1 research questions, 1.1.2 meta-analysis, 1.1.3 open science, 1.2 glossary, 1.2.1 accordion, 1.2.2 dialog cards, 1.2.3 drag words, 1.2.4 memory game, 1.2.5 fill in the blanks, 1.2.6 flash cards, 1.3 poll intuitions, 1.4 research process, 1.4.1 drag & drop, 1.4.2 form wizard, 1.4.3 interactive video, 1.4.4 order of steps, 1.4.4.1 research process (summary), 1.4.4.2 estimation plan (image sequencing).

Integrating this exercise into this books destroys the internal linking. It seems to me a bug of the H5P image sequenceing content type.

1.4.4.3 Estimation Plan (Summary)

1.4.4.4 research & estimation (learnr), 1.5 meta-analysis, 1.5.1 explore forest plot (image hotspots), 1.5.2 point estimates in forest plot (find multiple hotspots), 1.6 reporting (accordion), 1.7 quizzes and assessment, 1.7.1 quiz 1 (question set), 1.7.2 quiz 2 (question set), 1.7.3 take-home messages (summary), 1.7.4 assessment (question set).

Chapter 1: Getting started with research

1.6 Developing a research question

Sometimes your instructor may give you a very specific topic or research question to answer for your project. Other times, you may be allowed to decide what topic you’re researching. Whether you have been assigned a topic or not, developing a simple concept into a well-defined research question is an essential part of the research process. Your research question should inform the structure and contents of your project and everything you cite should be related to your research question in some way. Eventually, your research question will develop into your thesis , which is the central idea on which your project is based.

Turning your topic into a research question

There is no single approach to developing a research question that will work for every person and topic. You may start with a topic you’re somewhat familiar with and investigate a specific aspect of that topic that interests you. Or you may start by doing background research on a topic that’s new to you and then exploring the questions that arise as you learn more. A good research question cannot be answered with a yes or no. Creating a research question is not as simple as taking a topic you are interested in and making it into a question. Your research question should be clear, focused, manageable, and defensible (i.e. able to be supported by evidence). Let’s examine an example of this in more depth.

You are assigned to write a paper about the United States during the prohibition era. As you do some background research into the time period, you find that the illegal consumption of alcohol was prominent, especially among those with money. You come up with the following topic for your research: “illegal activity during prohibition in the United States.” How can we translate this into a clear, focused, manageable, and defensible research question?

Is it clear?

A research question should be stated clearly. Knowing what you want to research will help keep you from getting distracted by ideas that may be interesting, but are only loosely related to your topic. “Illegal activity during prohibition” could refer to a lot of things. Are you interested in mob activity, the prevalence of speakeasies, or another illegal activity at that time? Let’s say you’re specifically interested in the purchase and sale of alcohol. Your research question would be better phrased as: “How did the illegal use of alcohol persist when prohibition was in place?”

Is it focused?

Your new research question is fairly clear, but broad. There are a lot of resources about this topic and you may be overwhelmed with what you find. To make it more focused, you could refine your question by limiting it to a specific place (the American South) or timeframe (from 1920 to 1925). Revising your question for focus, it could read as: “How did the illegal use of alcohol persist in the American South when prohibition was in place?”

Is it manageable?

Perhaps even after narrowing your research topic you still find an overwhelming amount of resources. Or maybe you narrowed your topic too much, and you aren’t able to find enough information for your project. Based on what you learn along the way while searching, you may need to modify your research question or search strategy. You have to find balance between asking a really good, innovative research question and not overwhelming yourself by making it too big to conquer within the guidelines of your assignment, or too simple where it can be answered with a quick Google search. Looking at the research question posed above, “How did the illegal use of alcohol persist in the American South when prohibition was in place?” you wouldn’t need to make any revisions because this example is broad enough that you could find information about it easily, but it’s unlikely that you could find everything about your topic in a single search.

Is it defensible?

Whenever you do research, you bring your own biases and perspectives into your work, and these can influence the entire structure of your project. Avoid questions that have a moral stance “___ is not okay,” or an absolute stance “___ always results in ___.” Open-ended questions such as ones starting with “how,” “why,” or “what” make a great foundation for a research question. Be willing to change your research question if you can’t find resources that address your topic in a useful way. It could be that your topic is too new to have anything published about it, or it may be a topic that has been disproven by research over time. As you develop a research question, you should always think about whether your question can be supported by evidence. Our example, “How did the illegal use of alcohol persist in the American South when prohibition was in place?” is a good example of a defensible research question. You can find plenty of sources with relevant, reputable evidence about the economics, politics, and legal aspects of the illegal use of alcohol in this time and region to support your argument.

The next step is to begin searching for sources to support your research question. To find sources appropriate for your class projects, you’ll often need to search in specialized databases such as Academic Search in EBSCO or Compendex to find information. To efficiently search within these tools, you need to think carefully about the terms you’ll be using.

Library 160: Introduction to College-Level Research Copyright © 2021 by Iowa State University Library Instruction Services is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

Chapter 1. Introduction

“Science is in danger, and for that reason it is becoming dangerous” -Pierre Bourdieu, Science of Science and Reflexivity

Why an Open Access Textbook on Qualitative Research Methods?

I have been teaching qualitative research methods to both undergraduates and graduate students for many years.  Although there are some excellent textbooks out there, they are often costly, and none of them, to my mind, properly introduces qualitative research methods to the beginning student (whether undergraduate or graduate student).  In contrast, this open-access textbook is designed as a (free) true introduction to the subject, with helpful, practical pointers on how to conduct research and how to access more advanced instruction.  

Textbooks are typically arranged in one of two ways: (1) by technique (each chapter covers one method used in qualitative research); or (2) by process (chapters advance from research design through publication).  But both of these approaches are necessary for the beginner student.  This textbook will have sections dedicated to the process as well as the techniques of qualitative research.  This is a true “comprehensive” book for the beginning student.  In addition to covering techniques of data collection and data analysis, it provides a road map of how to get started and how to keep going and where to go for advanced instruction.  It covers aspects of research design and research communication as well as methods employed.  Along the way, it includes examples from many different disciplines in the social sciences.

The primary goal has been to create a useful, accessible, engaging textbook for use across many disciplines.  And, let’s face it.  Textbooks can be boring.  I hope readers find this to be a little different.  I have tried to write in a practical and forthright manner, with many lively examples and references to good and intellectually creative qualitative research.  Woven throughout the text are short textual asides (in colored textboxes) by professional (academic) qualitative researchers in various disciplines.  These short accounts by practitioners should help inspire students.  So, let’s begin!

What is Research?

When we use the word research , what exactly do we mean by that?  This is one of those words that everyone thinks they understand, but it is worth beginning this textbook with a short explanation.  We use the term to refer to “empirical research,” which is actually a historically specific approach to understanding the world around us.  Think about how you know things about the world. [1] You might know your mother loves you because she’s told you she does.  Or because that is what “mothers” do by tradition.  Or you might know because you’ve looked for evidence that she does, like taking care of you when you are sick or reading to you in bed or working two jobs so you can have the things you need to do OK in life.  Maybe it seems churlish to look for evidence; you just take it “on faith” that you are loved.

Only one of the above comes close to what we mean by research.  Empirical research is research (investigation) based on evidence.  Conclusions can then be drawn from observable data.  This observable data can also be “tested” or checked.  If the data cannot be tested, that is a good indication that we are not doing research.  Note that we can never “prove” conclusively, through observable data, that our mothers love us.  We might have some “disconfirming evidence” (that time she didn’t show up to your graduation, for example) that could push you to question an original hypothesis , but no amount of “confirming evidence” will ever allow us to say with 100% certainty, “my mother loves me.”  Faith and tradition and authority work differently.  Our knowledge can be 100% certain using each of those alternative methods of knowledge, but our certainty in those cases will not be based on facts or evidence.

For many periods of history, those in power have been nervous about “science” because it uses evidence and facts as the primary source of understanding the world, and facts can be at odds with what power or authority or tradition want you to believe.  That is why I say that scientific empirical research is a historically specific approach to understand the world.  You are in college or university now partly to learn how to engage in this historically specific approach.

In the sixteenth and seventeenth centuries in Europe, there was a newfound respect for empirical research, some of which was seriously challenging to the established church.  Using observations and testing them, scientists found that the earth was not at the center of the universe, for example, but rather that it was but one planet of many which circled the sun. [2]   For the next two centuries, the science of astronomy, physics, biology, and chemistry emerged and became disciplines taught in universities.  All used the scientific method of observation and testing to advance knowledge.  Knowledge about people , however, and social institutions, however, was still left to faith, tradition, and authority.  Historians and philosophers and poets wrote about the human condition, but none of them used research to do so. [3]

It was not until the nineteenth century that “social science” really emerged, using the scientific method (empirical observation) to understand people and social institutions.  New fields of sociology, economics, political science, and anthropology emerged.  The first sociologists, people like Auguste Comte and Karl Marx, sought specifically to apply the scientific method of research to understand society, Engels famously claiming that Marx had done for the social world what Darwin did for the natural world, tracings its laws of development.  Today we tend to take for granted the naturalness of science here, but it is actually a pretty recent and radical development.

To return to the question, “does your mother love you?”  Well, this is actually not really how a researcher would frame the question, as it is too specific to your case.  It doesn’t tell us much about the world at large, even if it does tell us something about you and your relationship with your mother.  A social science researcher might ask, “do mothers love their children?”  Or maybe they would be more interested in how this loving relationship might change over time (e.g., “do mothers love their children more now than they did in the 18th century when so many children died before reaching adulthood?”) or perhaps they might be interested in measuring quality of love across cultures or time periods, or even establishing “what love looks like” using the mother/child relationship as a site of exploration.  All of these make good research questions because we can use observable data to answer them.

What is Qualitative Research?

“All we know is how to learn. How to study, how to listen, how to talk, how to tell.  If we don’t tell the world, we don’t know the world.  We’re lost in it, we die.” -Ursula LeGuin, The Telling

At its simplest, qualitative research is research about the social world that does not use numbers in its analyses.  All those who fear statistics can breathe a sigh of relief – there are no mathematical formulae or regression models in this book! But this definition is less about what qualitative research can be and more about what it is not.  To be honest, any simple statement will fail to capture the power and depth of qualitative research.  One way of contrasting qualitative research to quantitative research is to note that the focus of qualitative research is less about explaining and predicting relationships between variables and more about understanding the social world.  To use our mother love example, the question about “what love looks like” is a good question for the qualitative researcher while all questions measuring love or comparing incidences of love (both of which require measurement) are good questions for quantitative researchers. Patton writes,

Qualitative data describe.  They take us, as readers, into the time and place of the observation so that we know what it was like to have been there.  They capture and communicate someone else’s experience of the world in his or her own words.  Qualitative data tell a story. ( Patton 2002:47 )

Qualitative researchers are asking different questions about the world than their quantitative colleagues.  Even when researchers are employed in “mixed methods” research ( both quantitative and qualitative), they are using different methods to address different questions of the study.  I do a lot of research about first-generation and working-college college students.  Where a quantitative researcher might ask, how many first-generation college students graduate from college within four years? Or does first-generation college status predict high student debt loads?  A qualitative researcher might ask, how does the college experience differ for first-generation college students?  What is it like to carry a lot of debt, and how does this impact the ability to complete college on time?  Both sets of questions are important, but they can only be answered using specific tools tailored to those questions.  For the former, you need large numbers to make adequate comparisons.  For the latter, you need to talk to people, find out what they are thinking and feeling, and try to inhabit their shoes for a little while so you can make sense of their experiences and beliefs.

Examples of Qualitative Research

You have probably seen examples of qualitative research before, but you might not have paid particular attention to how they were produced or realized that the accounts you were reading were the result of hours, months, even years of research “in the field.”  A good qualitative researcher will present the product of their hours of work in such a way that it seems natural, even obvious, to the reader.  Because we are trying to convey what it is like answers, qualitative research is often presented as stories – stories about how people live their lives, go to work, raise their children, interact with one another.  In some ways, this can seem like reading particularly insightful novels.  But, unlike novels, there are very specific rules and guidelines that qualitative researchers follow to ensure that the “story” they are telling is accurate , a truthful rendition of what life is like for the people being studied.  Most of this textbook will be spent conveying those rules and guidelines.  Let’s take a look, first, however, at three examples of what the end product looks like.  I have chosen these three examples to showcase very different approaches to qualitative research, and I will return to these five examples throughout the book.  They were all published as whole books (not chapters or articles), and they are worth the long read, if you have the time.  I will also provide some information on how these books came to be and the length of time it takes to get them into book version.  It is important you know about this process, and the rest of this textbook will help explain why it takes so long to conduct good qualitative research!

Example 1 : The End Game (ethnography + interviews)

Corey Abramson is a sociologist who teaches at the University of Arizona.   In 2015 he published The End Game: How Inequality Shapes our Final Years ( 2015 ). This book was based on the research he did for his dissertation at the University of California-Berkeley in 2012.  Actually, the dissertation was completed in 2012 but the work that was produced that took several years.  The dissertation was entitled, “This is How We Live, This is How We Die: Social Stratification, Aging, and Health in Urban America” ( 2012 ).  You can see how the book version, which was written for a more general audience, has a more engaging sound to it, but that the dissertation version, which is what academic faculty read and evaluate, has a more descriptive title.  You can read the title and know that this is a study about aging and health and that the focus is going to be inequality and that the context (place) is going to be “urban America.”  It’s a study about “how” people do something – in this case, how they deal with aging and death.  This is the very first sentence of the dissertation, “From our first breath in the hospital to the day we die, we live in a society characterized by unequal opportunities for maintaining health and taking care of ourselves when ill.  These disparities reflect persistent racial, socio-economic, and gender-based inequalities and contribute to their persistence over time” ( 1 ).  What follows is a truthful account of how that is so.

Cory Abramson spent three years conducting his research in four different urban neighborhoods.  We call the type of research he conducted “comparative ethnographic” because he designed his study to compare groups of seniors as they went about their everyday business.  It’s comparative because he is comparing different groups (based on race, class, gender) and ethnographic because he is studying the culture/way of life of a group. [4]   He had an educated guess, rooted in what previous research had shown and what social theory would suggest, that people’s experiences of aging differ by race, class, and gender.  So, he set up a research design that would allow him to observe differences.  He chose two primarily middle-class (one was racially diverse and the other was predominantly White) and two primarily poor neighborhoods (one was racially diverse and the other was predominantly African American).  He hung out in senior centers and other places seniors congregated, watched them as they took the bus to get prescriptions filled, sat in doctor’s offices with them, and listened to their conversations with each other.  He also conducted more formal conversations, what we call in-depth interviews, with sixty seniors from each of the four neighborhoods.  As with a lot of fieldwork , as he got closer to the people involved, he both expanded and deepened his reach –

By the end of the project, I expanded my pool of general observations to include various settings frequented by seniors: apartment building common rooms, doctors’ offices, emergency rooms, pharmacies, senior centers, bars, parks, corner stores, shopping centers, pool halls, hair salons, coffee shops, and discount stores. Over the course of the three years of fieldwork, I observed hundreds of elders, and developed close relationships with a number of them. ( 2012:10 )

When Abramson rewrote the dissertation for a general audience and published his book in 2015, it got a lot of attention.  It is a beautifully written book and it provided insight into a common human experience that we surprisingly know very little about.  It won the Outstanding Publication Award by the American Sociological Association Section on Aging and the Life Course and was featured in the New York Times .  The book was about aging, and specifically how inequality shapes the aging process, but it was also about much more than that.  It helped show how inequality affects people’s everyday lives.  For example, by observing the difficulties the poor had in setting up appointments and getting to them using public transportation and then being made to wait to see a doctor, sometimes in standing-room-only situations, when they are unwell, and then being treated dismissively by hospital staff, Abramson allowed readers to feel the material reality of being poor in the US.  Comparing these examples with seniors with adequate supplemental insurance who have the resources to hire car services or have others assist them in arranging care when they need it, jolts the reader to understand and appreciate the difference money makes in the lives and circumstances of us all, and in a way that is different than simply reading a statistic (“80% of the poor do not keep regular doctor’s appointments”) does.  Qualitative research can reach into spaces and places that often go unexamined and then reports back to the rest of us what it is like in those spaces and places.

Example 2: Racing for Innocence (Interviews + Content Analysis + Fictional Stories)

Jennifer Pierce is a Professor of American Studies at the University of Minnesota.  Trained as a sociologist, she has written a number of books about gender, race, and power.  Her very first book, Gender Trials: Emotional Lives in Contemporary Law Firms, published in 1995, is a brilliant look at gender dynamics within two law firms.  Pierce was a participant observer, working as a paralegal, and she observed how female lawyers and female paralegals struggled to obtain parity with their male colleagues.

Fifteen years later, she reexamined the context of the law firm to include an examination of racial dynamics, particularly how elite white men working in these spaces created and maintained a culture that made it difficult for both female attorneys and attorneys of color to thrive. Her book, Racing for Innocence: Whiteness, Gender, and the Backlash Against Affirmative Action , published in 2012, is an interesting and creative blending of interviews with attorneys, content analyses of popular films during this period, and fictional accounts of racial discrimination and sexual harassment.  The law firm she chose to study had come under an affirmative action order and was in the process of implementing equitable policies and programs.  She wanted to understand how recipients of white privilege (the elite white male attorneys) come to deny the role they play in reproducing inequality.  Through interviews with attorneys who were present both before and during the affirmative action order, she creates a historical record of the “bad behavior” that necessitated new policies and procedures, but also, and more importantly , probed the participants ’ understanding of this behavior.  It should come as no surprise that most (but not all) of the white male attorneys saw little need for change, and that almost everyone else had accounts that were different if not sometimes downright harrowing.

I’ve used Pierce’s book in my qualitative research methods courses as an example of an interesting blend of techniques and presentation styles.  My students often have a very difficult time with the fictional accounts she includes.  But they serve an important communicative purpose here.  They are her attempts at presenting “both sides” to an objective reality – something happens (Pierce writes this something so it is very clear what it is), and the two participants to the thing that happened have very different understandings of what this means.  By including these stories, Pierce presents one of her key findings – people remember things differently and these different memories tend to support their own ideological positions.  I wonder what Pierce would have written had she studied the murder of George Floyd or the storming of the US Capitol on January 6 or any number of other historic events whose observers and participants record very different happenings.

This is not to say that qualitative researchers write fictional accounts.  In fact, the use of fiction in our work remains controversial.  When used, it must be clearly identified as a presentation device, as Pierce did.  I include Racing for Innocence here as an example of the multiple uses of methods and techniques and the way that these work together to produce better understandings by us, the readers, of what Pierce studied.  We readers come away with a better grasp of how and why advantaged people understate their own involvement in situations and structures that advantage them.  This is normal human behavior , in other words.  This case may have been about elite white men in law firms, but the general insights here can be transposed to other settings.  Indeed, Pierce argues that more research needs to be done about the role elites play in the reproduction of inequality in the workplace in general.

Example 3: Amplified Advantage (Mixed Methods: Survey Interviews + Focus Groups + Archives)

The final example comes from my own work with college students, particularly the ways in which class background affects the experience of college and outcomes for graduates.  I include it here as an example of mixed methods, and for the use of supplementary archival research.  I’ve done a lot of research over the years on first-generation, low-income, and working-class college students.  I am curious (and skeptical) about the possibility of social mobility today, particularly with the rising cost of college and growing inequality in general.  As one of the few people in my family to go to college, I didn’t grow up with a lot of examples of what college was like or how to make the most of it.  And when I entered graduate school, I realized with dismay that there were very few people like me there.  I worried about becoming too different from my family and friends back home.  And I wasn’t at all sure that I would ever be able to pay back the huge load of debt I was taking on.  And so I wrote my dissertation and first two books about working-class college students.  These books focused on experiences in college and the difficulties of navigating between family and school ( Hurst 2010a, 2012 ).  But even after all that research, I kept coming back to wondering if working-class students who made it through college had an equal chance at finding good jobs and happy lives,

What happens to students after college?  Do working-class students fare as well as their peers?  I knew from my own experience that barriers continued through graduate school and beyond, and that my debtload was higher than that of my peers, constraining some of the choices I made when I graduated.  To answer these questions, I designed a study of students attending small liberal arts colleges, the type of college that tried to equalize the experience of students by requiring all students to live on campus and offering small classes with lots of interaction with faculty.  These private colleges tend to have more money and resources so they can provide financial aid to low-income students.  They also attract some very wealthy students.  Because they enroll students across the class spectrum, I would be able to draw comparisons.  I ended up spending about four years collecting data, both a survey of more than 2000 students (which formed the basis for quantitative analyses) and qualitative data collection (interviews, focus groups, archival research, and participant observation).  This is what we call a “mixed methods” approach because we use both quantitative and qualitative data.  The survey gave me a large enough number of students that I could make comparisons of the how many kind, and to be able to say with some authority that there were in fact significant differences in experience and outcome by class (e.g., wealthier students earned more money and had little debt; working-class students often found jobs that were not in their chosen careers and were very affected by debt, upper-middle-class students were more likely to go to graduate school).  But the survey analyses could not explain why these differences existed.  For that, I needed to talk to people and ask them about their motivations and aspirations.  I needed to understand their perceptions of the world, and it is very hard to do this through a survey.

By interviewing students and recent graduates, I was able to discern particular patterns and pathways through college and beyond.  Specifically, I identified three versions of gameplay.  Upper-middle-class students, whose parents were themselves professionals (academics, lawyers, managers of non-profits), saw college as the first stage of their education and took classes and declared majors that would prepare them for graduate school.  They also spent a lot of time building their resumes, taking advantage of opportunities to help professors with their research, or study abroad.  This helped them gain admission to highly-ranked graduate schools and interesting jobs in the public sector.  In contrast, upper-class students, whose parents were wealthy and more likely to be engaged in business (as CEOs or other high-level directors), prioritized building social capital.  They did this by joining fraternities and sororities and playing club sports.  This helped them when they graduated as they called on friends and parents of friends to find them well-paying jobs.  Finally, low-income, first-generation, and working-class students were often adrift.  They took the classes that were recommended to them but without the knowledge of how to connect them to life beyond college.  They spent time working and studying rather than partying or building their resumes.  All three sets of students thought they were “doing college” the right way, the way that one was supposed to do college.   But these three versions of gameplay led to distinct outcomes that advantaged some students over others.  I titled my work “Amplified Advantage” to highlight this process.

These three examples, Cory Abramson’s The End Game , Jennifer Peirce’s Racing for Innocence, and my own Amplified Advantage, demonstrate the range of approaches and tools available to the qualitative researcher.  They also help explain why qualitative research is so important.  Numbers can tell us some things about the world, but they cannot get at the hearts and minds, motivations and beliefs of the people who make up the social worlds we inhabit.  For that, we need tools that allow us to listen and make sense of what people tell us and show us.  That is what good qualitative research offers us.

How Is This Book Organized?

This textbook is organized as a comprehensive introduction to the use of qualitative research methods.  The first half covers general topics (e.g., approaches to qualitative research, ethics) and research design (necessary steps for building a successful qualitative research study).  The second half reviews various data collection and data analysis techniques.  Of course, building a successful qualitative research study requires some knowledge of data collection and data analysis so the chapters in the first half and the chapters in the second half should be read in conversation with each other.  That said, each chapter can be read on its own for assistance with a particular narrow topic.  In addition to the chapters, a helpful glossary can be found in the back of the book.  Rummage around in the text as needed.

Chapter Descriptions

Chapter 2 provides an overview of the Research Design Process.  How does one begin a study? What is an appropriate research question?  How is the study to be done – with what methods ?  Involving what people and sites?  Although qualitative research studies can and often do change and develop over the course of data collection, it is important to have a good idea of what the aims and goals of your study are at the outset and a good plan of how to achieve those aims and goals.  Chapter 2 provides a road map of the process.

Chapter 3 describes and explains various ways of knowing the (social) world.  What is it possible for us to know about how other people think or why they behave the way they do?  What does it mean to say something is a “fact” or that it is “well-known” and understood?  Qualitative researchers are particularly interested in these questions because of the types of research questions we are interested in answering (the how questions rather than the how many questions of quantitative research).  Qualitative researchers have adopted various epistemological approaches.  Chapter 3 will explore these approaches, highlighting interpretivist approaches that acknowledge the subjective aspect of reality – in other words, reality and knowledge are not objective but rather influenced by (interpreted through) people.

Chapter 4 focuses on the practical matter of developing a research question and finding the right approach to data collection.  In any given study (think of Cory Abramson’s study of aging, for example), there may be years of collected data, thousands of observations , hundreds of pages of notes to read and review and make sense of.  If all you had was a general interest area (“aging”), it would be very difficult, nearly impossible, to make sense of all of that data.  The research question provides a helpful lens to refine and clarify (and simplify) everything you find and collect.  For that reason, it is important to pull out that lens (articulate the research question) before you get started.  In the case of the aging study, Cory Abramson was interested in how inequalities affected understandings and responses to aging.  It is for this reason he designed a study that would allow him to compare different groups of seniors (some middle-class, some poor).  Inevitably, he saw much more in the three years in the field than what made it into his book (or dissertation), but he was able to narrow down the complexity of the social world to provide us with this rich account linked to the original research question.  Developing a good research question is thus crucial to effective design and a successful outcome.  Chapter 4 will provide pointers on how to do this.  Chapter 4 also provides an overview of general approaches taken to doing qualitative research and various “traditions of inquiry.”

Chapter 5 explores sampling .  After you have developed a research question and have a general idea of how you will collect data (Observations?  Interviews?), how do you go about actually finding people and sites to study?  Although there is no “correct number” of people to interview , the sample should follow the research question and research design.  Unlike quantitative research, qualitative research involves nonprobability sampling.  Chapter 5 explains why this is so and what qualities instead make a good sample for qualitative research.

Chapter 6 addresses the importance of reflexivity in qualitative research.  Related to epistemological issues of how we know anything about the social world, qualitative researchers understand that we the researchers can never be truly neutral or outside the study we are conducting.  As observers, we see things that make sense to us and may entirely miss what is either too obvious to note or too different to comprehend.  As interviewers, as much as we would like to ask questions neutrally and remain in the background, interviews are a form of conversation, and the persons we interview are responding to us .  Therefore, it is important to reflect upon our social positions and the knowledges and expectations we bring to our work and to work through any blind spots that we may have.  Chapter 6 provides some examples of reflexivity in practice and exercises for thinking through one’s own biases.

Chapter 7 is a very important chapter and should not be overlooked.  As a practical matter, it should also be read closely with chapters 6 and 8.  Because qualitative researchers deal with people and the social world, it is imperative they develop and adhere to a strong ethical code for conducting research in a way that does not harm.  There are legal requirements and guidelines for doing so (see chapter 8), but these requirements should not be considered synonymous with the ethical code required of us.   Each researcher must constantly interrogate every aspect of their research, from research question to design to sample through analysis and presentation, to ensure that a minimum of harm (ideally, zero harm) is caused.  Because each research project is unique, the standards of care for each study are unique.  Part of being a professional researcher is carrying this code in one’s heart, being constantly attentive to what is required under particular circumstances.  Chapter 7 provides various research scenarios and asks readers to weigh in on the suitability and appropriateness of the research.  If done in a class setting, it will become obvious fairly quickly that there are often no absolutely correct answers, as different people find different aspects of the scenarios of greatest importance.  Minimizing the harm in one area may require possible harm in another.  Being attentive to all the ethical aspects of one’s research and making the best judgments one can, clearly and consciously, is an integral part of being a good researcher.

Chapter 8 , best to be read in conjunction with chapter 7, explains the role and importance of Institutional Review Boards (IRBs) .  Under federal guidelines, an IRB is an appropriately constituted group that has been formally designated to review and monitor research involving human subjects .  Every institution that receives funding from the federal government has an IRB.  IRBs have the authority to approve, require modifications to (to secure approval), or disapprove research.  This group review serves an important role in the protection of the rights and welfare of human research subjects.  Chapter 8 reviews the history of IRBs and the work they do but also argues that IRBs’ review of qualitative research is often both over-inclusive and under-inclusive.  Some aspects of qualitative research are not well understood by IRBs, given that they were developed to prevent abuses in biomedical research.  Thus, it is important not to rely on IRBs to identify all the potential ethical issues that emerge in our research (see chapter 7).

Chapter 9 provides help for getting started on formulating a research question based on gaps in the pre-existing literature.  Research is conducted as part of a community, even if particular studies are done by single individuals (or small teams).  What any of us finds and reports back becomes part of a much larger body of knowledge.  Thus, it is important that we look at the larger body of knowledge before we actually start our bit to see how we can best contribute.  When I first began interviewing working-class college students, there was only one other similar study I could find, and it hadn’t been published (it was a dissertation of students from poor backgrounds).  But there had been a lot published by professors who had grown up working class and made it through college despite the odds.  These accounts by “working-class academics” became an important inspiration for my study and helped me frame the questions I asked the students I interviewed.  Chapter 9 will provide some pointers on how to search for relevant literature and how to use this to refine your research question.

Chapter 10 serves as a bridge between the two parts of the textbook, by introducing techniques of data collection.  Qualitative research is often characterized by the form of data collection – for example, an ethnographic study is one that employs primarily observational data collection for the purpose of documenting and presenting a particular culture or ethnos.  Techniques can be effectively combined, depending on the research question and the aims and goals of the study.   Chapter 10 provides a general overview of all the various techniques and how they can be combined.

The second part of the textbook moves into the doing part of qualitative research once the research question has been articulated and the study designed.  Chapters 11 through 17 cover various data collection techniques and approaches.  Chapters 18 and 19 provide a very simple overview of basic data analysis.  Chapter 20 covers communication of the data to various audiences, and in various formats.

Chapter 11 begins our overview of data collection techniques with a focus on interviewing , the true heart of qualitative research.  This technique can serve as the primary and exclusive form of data collection, or it can be used to supplement other forms (observation, archival).  An interview is distinct from a survey, where questions are asked in a specific order and often with a range of predetermined responses available.  Interviews can be conversational and unstructured or, more conventionally, semistructured , where a general set of interview questions “guides” the conversation.  Chapter 11 covers the basics of interviews: how to create interview guides, how many people to interview, where to conduct the interview, what to watch out for (how to prepare against things going wrong), and how to get the most out of your interviews.

Chapter 12 covers an important variant of interviewing, the focus group.  Focus groups are semistructured interviews with a group of people moderated by a facilitator (the researcher or researcher’s assistant).  Focus groups explicitly use group interaction to assist in the data collection.  They are best used to collect data on a specific topic that is non-personal and shared among the group.  For example, asking a group of college students about a common experience such as taking classes by remote delivery during the pandemic year of 2020.  Chapter 12 covers the basics of focus groups: when to use them, how to create interview guides for them, and how to run them effectively.

Chapter 13 moves away from interviewing to the second major form of data collection unique to qualitative researchers – observation .  Qualitative research that employs observation can best be understood as falling on a continuum of “fly on the wall” observation (e.g., observing how strangers interact in a doctor’s waiting room) to “participant” observation, where the researcher is also an active participant of the activity being observed.  For example, an activist in the Black Lives Matter movement might want to study the movement, using her inside position to gain access to observe key meetings and interactions.  Chapter  13 covers the basics of participant observation studies: advantages and disadvantages, gaining access, ethical concerns related to insider/outsider status and entanglement, and recording techniques.

Chapter 14 takes a closer look at “deep ethnography” – immersion in the field of a particularly long duration for the purpose of gaining a deeper understanding and appreciation of a particular culture or social world.  Clifford Geertz called this “deep hanging out.”  Whereas participant observation is often combined with semistructured interview techniques, deep ethnography’s commitment to “living the life” or experiencing the situation as it really is demands more conversational and natural interactions with people.  These interactions and conversations may take place over months or even years.  As can be expected, there are some costs to this technique, as well as some very large rewards when done competently.  Chapter 14 provides some examples of deep ethnographies that will inspire some beginning researchers and intimidate others.

Chapter 15 moves in the opposite direction of deep ethnography, a technique that is the least positivist of all those discussed here, to mixed methods , a set of techniques that is arguably the most positivist .  A mixed methods approach combines both qualitative data collection and quantitative data collection, commonly by combining a survey that is analyzed statistically (e.g., cross-tabs or regression analyses of large number probability samples) with semi-structured interviews.  Although it is somewhat unconventional to discuss mixed methods in textbooks on qualitative research, I think it is important to recognize this often-employed approach here.  There are several advantages and some disadvantages to taking this route.  Chapter 16 will describe those advantages and disadvantages and provide some particular guidance on how to design a mixed methods study for maximum effectiveness.

Chapter 16 covers data collection that does not involve live human subjects at all – archival and historical research (chapter 17 will also cover data that does not involve interacting with human subjects).  Sometimes people are unavailable to us, either because they do not wish to be interviewed or observed (as is the case with many “elites”) or because they are too far away, in both place and time.  Fortunately, humans leave many traces and we can often answer questions we have by examining those traces.  Special collections and archives can be goldmines for social science research.  This chapter will explain how to access these places, for what purposes, and how to begin to make sense of what you find.

Chapter 17 covers another data collection area that does not involve face-to-face interaction with humans: content analysis .  Although content analysis may be understood more properly as a data analysis technique, the term is often used for the entire approach, which will be the case here.  Content analysis involves interpreting meaning from a body of text.  This body of text might be something found in historical records (see chapter 16) or something collected by the researcher, as in the case of comment posts on a popular blog post.  I once used the stories told by student loan debtors on the website studentloanjustice.org as the content I analyzed.  Content analysis is particularly useful when attempting to define and understand prevalent stories or communication about a topic of interest.  In other words, when we are less interested in what particular people (our defined sample) are doing or believing and more interested in what general narratives exist about a particular topic or issue.  This chapter will explore different approaches to content analysis and provide helpful tips on how to collect data, how to turn that data into codes for analysis, and how to go about presenting what is found through analysis.

Where chapter 17 has pushed us towards data analysis, chapters 18 and 19 are all about what to do with the data collected, whether that data be in the form of interview transcripts or fieldnotes from observations.  Chapter 18 introduces the basics of coding , the iterative process of assigning meaning to the data in order to both simplify and identify patterns.  What is a code and how does it work?  What are the different ways of coding data, and when should you use them?  What is a codebook, and why do you need one?  What does the process of data analysis look like?

Chapter 19 goes further into detail on codes and how to use them, particularly the later stages of coding in which our codes are refined, simplified, combined, and organized.  These later rounds of coding are essential to getting the most out of the data we’ve collected.  As students are often overwhelmed with the amount of data (a corpus of interview transcripts typically runs into the hundreds of pages; fieldnotes can easily top that), this chapter will also address time management and provide suggestions for dealing with chaos and reminders that feeling overwhelmed at the analysis stage is part of the process.  By the end of the chapter, you should understand how “findings” are actually found.

The book concludes with a chapter dedicated to the effective presentation of data results.  Chapter 20 covers the many ways that researchers communicate their studies to various audiences (academic, personal, political), what elements must be included in these various publications, and the hallmarks of excellent qualitative research that various audiences will be expecting.  Because qualitative researchers are motivated by understanding and conveying meaning , effective communication is not only an essential skill but a fundamental facet of the entire research project.  Ethnographers must be able to convey a certain sense of verisimilitude , the appearance of true reality.  Those employing interviews must faithfully depict the key meanings of the people they interviewed in a way that rings true to those people, even if the end result surprises them.  And all researchers must strive for clarity in their publications so that various audiences can understand what was found and why it is important.

The book concludes with a short chapter ( chapter 21 ) discussing the value of qualitative research. At the very end of this book, you will find a glossary of terms. I recommend you make frequent use of the glossary and add to each entry as you find examples. Although the entries are meant to be simple and clear, you may also want to paraphrase the definition—make it “make sense” to you, in other words. In addition to the standard reference list (all works cited here), you will find various recommendations for further reading at the end of many chapters. Some of these recommendations will be examples of excellent qualitative research, indicated with an asterisk (*) at the end of the entry. As they say, a picture is worth a thousand words. A good example of qualitative research can teach you more about conducting research than any textbook can (this one included). I highly recommend you select one to three examples from these lists and read them along with the textbook.

A final note on the choice of examples – you will note that many of the examples used in the text come from research on college students.  This is for two reasons.  First, as most of my research falls in this area, I am most familiar with this literature and have contacts with those who do research here and can call upon them to share their stories with you.  Second, and more importantly, my hope is that this textbook reaches a wide audience of beginning researchers who study widely and deeply across the range of what can be known about the social world (from marine resources management to public policy to nursing to political science to sexuality studies and beyond).  It is sometimes difficult to find examples that speak to all those research interests, however. A focus on college students is something that all readers can understand and, hopefully, appreciate, as we are all now or have been at some point a college student.

Recommended Reading: Other Qualitative Research Textbooks

I’ve included a brief list of some of my favorite qualitative research textbooks and guidebooks if you need more than what you will find in this introductory text.  For each, I’ve also indicated if these are for “beginning” or “advanced” (graduate-level) readers.  Many of these books have several editions that do not significantly vary; the edition recommended is merely the edition I have used in teaching and to whose page numbers any specific references made in the text agree.

Barbour, Rosaline. 2014. Introducing Qualitative Research: A Student’s Guide. Thousand Oaks, CA: SAGE.  A good introduction to qualitative research, with abundant examples (often from the discipline of health care) and clear definitions.  Includes quick summaries at the ends of each chapter.  However, some US students might find the British context distracting and can be a bit advanced in some places.  Beginning .

Bloomberg, Linda Dale, and Marie F. Volpe. 2012. Completing Your Qualitative Dissertation . 2nd ed. Thousand Oaks, CA: SAGE.  Specifically designed to guide graduate students through the research process. Advanced .

Creswell, John W., and Cheryl Poth. 2018 Qualitative Inquiry and Research Design: Choosing among Five Traditions .  4th ed. Thousand Oaks, CA: SAGE.  This is a classic and one of the go-to books I used myself as a graduate student.  One of the best things about this text is its clear presentation of five distinct traditions in qualitative research.  Despite the title, this reasonably sized book is about more than research design, including both data analysis and how to write about qualitative research.  Advanced .

Lareau, Annette. 2021. Listening to People: A Practical Guide to Interviewing, Participant Observation, Data Analysis, and Writing It All Up .  Chicago: University of Chicago Press. A readable and personal account of conducting qualitative research by an eminent sociologist, with a heavy emphasis on the kinds of participant-observation research conducted by the author.  Despite its reader-friendliness, this is really a book targeted to graduate students learning the craft.  Advanced .

Lune, Howard, and Bruce L. Berg. 2018. 9th edition.  Qualitative Research Methods for the Social Sciences.  Pearson . Although a good introduction to qualitative methods, the authors favor symbolic interactionist and dramaturgical approaches, which limits the appeal primarily to sociologists.  Beginning .

Marshall, Catherine, and Gretchen B. Rossman. 2016. 6th edition. Designing Qualitative Research. Thousand Oaks, CA: SAGE.  Very readable and accessible guide to research design by two educational scholars.  Although the presentation is sometimes fairly dry, personal vignettes and illustrations enliven the text.  Beginning .

Maxwell, Joseph A. 2013. Qualitative Research Design: An Interactive Approach .  3rd ed. Thousand Oaks, CA: SAGE. A short and accessible introduction to qualitative research design, particularly helpful for graduate students contemplating theses and dissertations. This has been a standard textbook in my graduate-level courses for years.  Advanced .

Patton, Michael Quinn. 2002. Qualitative Research and Evaluation Methods . Thousand Oaks, CA: SAGE.  This is a comprehensive text that served as my “go-to” reference when I was a graduate student.  It is particularly helpful for those involved in program evaluation and other forms of evaluation studies and uses examples from a wide range of disciplines.  Advanced .

Rubin, Ashley T. 2021. Rocking Qualitative Social Science: An Irreverent Guide to Rigorous Research. Stanford : Stanford University Press.  A delightful and personal read.  Rubin uses rock climbing as an extended metaphor for learning how to conduct qualitative research.  A bit slanted toward ethnographic and archival methods of data collection, with frequent examples from her own studies in criminology. Beginning .

Weis, Lois, and Michelle Fine. 2000. Speed Bumps: A Student-Friendly Guide to Qualitative Research . New York: Teachers College Press.  Readable and accessibly written in a quasi-conversational style.  Particularly strong in its discussion of ethical issues throughout the qualitative research process.  Not comprehensive, however, and very much tied to ethnographic research.  Although designed for graduate students, this is a recommended read for students of all levels.  Beginning .

Patton’s Ten Suggestions for Doing Qualitative Research

The following ten suggestions were made by Michael Quinn Patton in his massive textbooks Qualitative Research and Evaluations Methods . This book is highly recommended for those of you who want more than an introduction to qualitative methods. It is the book I relied on heavily when I was a graduate student, although it is much easier to “dip into” when necessary than to read through as a whole. Patton is asked for “just one bit of advice” for a graduate student considering using qualitative research methods for their dissertation.  Here are his top ten responses, in short form, heavily paraphrased, and with additional comments and emphases from me:

• Make sure that a qualitative approach fits the research question. The following are the kinds of questions that call out for qualitative methods or where qualitative methods are particularly appropriate: questions about people’s experiences or how they make sense of those experiences; studying a person in their natural environment; researching a phenomenon so unknown that it would be impossible to study it with standardized instruments or other forms of quantitative data collection.
• Study qualitative research by going to the original sources for the design and analysis appropriate to the particular approach you want to take (e.g., read Glaser and Straus if you are using grounded theory )
• Find a dissertation adviser who understands or at least who will support your use of qualitative research methods. You are asking for trouble if your entire committee is populated by quantitative researchers, even if they are all very knowledgeable about the subject or focus of your study (maybe even more so if they are!)
• Really work on design. Doing qualitative research effectively takes a lot of planning.  Even if things are more flexible than in quantitative research, a good design is absolutely essential when starting out.
• Practice data collection techniques, particularly interviewing and observing. There is definitely a set of learned skills here!  Do not expect your first interview to be perfect.  You will continue to grow as a researcher the more interviews you conduct, and you will probably come to understand yourself a bit more in the process, too.  This is not easy, despite what others who don’t work with qualitative methods may assume (and tell you!)
• Have a plan for analysis before you begin data collection. This is often a requirement in IRB protocols , although you can get away with writing something fairly simple.  And even if you are taking an approach, such as grounded theory, that pushes you to remain fairly open-minded during the data collection process, you still want to know what you will be doing with all the data collected – creating a codebook? Writing analytical memos? Comparing cases?  Having a plan in hand will also help prevent you from collecting too much extraneous data.
• Be prepared to confront controversies both within the qualitative research community and between qualitative research and quantitative research. Don’t be naïve about this – qualitative research, particularly some approaches, will be derided by many more “positivist” researchers and audiences.  For example, is an “n” of 1 really sufficient?  Yes!  But not everyone will agree.
• Do not make the mistake of using qualitative research methods because someone told you it was easier, or because you are intimidated by the math required of statistical analyses. Qualitative research is difficult in its own way (and many would claim much more time-consuming than quantitative research).  Do it because you are convinced it is right for your goals, aims, and research questions.
• Find a good support network. This could be a research mentor, or it could be a group of friends or colleagues who are also using qualitative research, or it could be just someone who will listen to you work through all of the issues you will confront out in the field and during the writing process.  Even though qualitative research often involves human subjects, it can be pretty lonely.  A lot of times you will feel like you are working without a net.  You have to create one for yourself.  Take care of yourself.
• And, finally, in the words of Patton, “Prepare to be changed. Looking deeply at other people’s lives will force you to look deeply at yourself.”
• We will actually spend an entire chapter ( chapter 3 ) looking at this question in much more detail! ↵
• Note that this might have been news to Europeans at the time, but many other societies around the world had also come to this conclusion through observation.  There is often a tendency to equate “the scientific revolution” with the European world in which it took place, but this is somewhat misleading. ↵
• Historians are a special case here.  Historians have scrupulously and rigorously investigated the social world, but not for the purpose of understanding general laws about how things work, which is the point of scientific empirical research.  History is often referred to as an idiographic field of study, meaning that it studies things that happened or are happening in themselves and not for general observations or conclusions. ↵
• Don’t worry, we’ll spend more time later in this book unpacking the meaning of ethnography and other terms that are important here.  Note the available glossary ↵

An approach to research that is “multimethod in focus, involving an interpretative, naturalistic approach to its subject matter.  This means that qualitative researchers study things in their natural settings, attempting to make sense of, or interpret, phenomena in terms of the meanings people bring to them.  Qualitative research involves the studied use and collection of a variety of empirical materials – case study, personal experience, introspective, life story, interview, observational, historical, interactional, and visual texts – that describe routine and problematic moments and meanings in individuals’ lives." ( Denzin and Lincoln 2005:2 ). Contrast with quantitative research .

In contrast to methodology, methods are more simply the practices and tools used to collect and analyze data.  Examples of common methods in qualitative research are interviews , observations , and documentary analysis .  One’s methodology should connect to one’s choice of methods, of course, but they are distinguishable terms.  See also methodology .

A proposed explanation for an observation, phenomenon, or scientific problem that can be tested by further investigation.  The positing of a hypothesis is often the first step in quantitative research but not in qualitative research.  Even when qualitative researchers offer possible explanations in advance of conducting research, they will tend to not use the word “hypothesis” as it conjures up the kind of positivist research they are not conducting.

The foundational question to be addressed by the research study.  This will form the anchor of the research design, collection, and analysis.  Note that in qualitative research, the research question may, and probably will, alter or develop during the course of the research.

An approach to research that collects and analyzes numerical data for the purpose of finding patterns and averages, making predictions, testing causal relationships, and generalizing results to wider populations.  Contrast with qualitative research .

Data collection that takes place in real-world settings, referred to as “the field;” a key component of much Grounded Theory and ethnographic research.  Patton ( 2002 ) calls fieldwork “the central activity of qualitative inquiry” where “‘going into the field’ means having direct and personal contact with people under study in their own environments – getting close to people and situations being studied to personally understand the realities of minutiae of daily life” (48).

The people who are the subjects of a qualitative study.  In interview-based studies, they may be the respondents to the interviewer; for purposes of IRBs, they are often referred to as the human subjects of the research.

The branch of philosophy concerned with knowledge.  For researchers, it is important to recognize and adopt one of the many distinguishing epistemological perspectives as part of our understanding of what questions research can address or fully answer.  See, e.g., constructivism , subjectivism, and  objectivism .

An approach that refutes the possibility of neutrality in social science research.  All research is “guided by a set of beliefs and feelings about the world and how it should be understood and studied” (Denzin and Lincoln 2005: 13).  In contrast to positivism , interpretivism recognizes the social constructedness of reality, and researchers adopting this approach focus on capturing interpretations and understandings people have about the world rather than “the world” as it is (which is a chimera).

The cluster of data-collection tools and techniques that involve observing interactions between people, the behaviors, and practices of individuals (sometimes in contrast to what they say about how they act and behave), and cultures in context.  Observational methods are the key tools employed by ethnographers and Grounded Theory .

Research based on data collected and analyzed by the research (in contrast to secondary “library” research).

The process of selecting people or other units of analysis to represent a larger population. In quantitative research, this representation is taken quite literally, as statistically representative.  In qualitative research, in contrast, sample selection is often made based on potential to generate insight about a particular topic or phenomenon.

A method of data collection in which the researcher asks the participant questions; the answers to these questions are often recorded and transcribed verbatim. There are many different kinds of interviews - see also semistructured interview , structured interview , and unstructured interview .

The specific group of individuals that you will collect data from.  Contrast population.

The practice of being conscious of and reflective upon one’s own social location and presence when conducting research.  Because qualitative research often requires interaction with live humans, failing to take into account how one’s presence and prior expectations and social location affect the data collected and how analyzed may limit the reliability of the findings.  This remains true even when dealing with historical archives and other content.  Who we are matters when asking questions about how people experience the world because we, too, are a part of that world.

The science and practice of right conduct; in research, it is also the delineation of moral obligations towards research participants, communities to which we belong, and communities in which we conduct our research.

An administrative body established to protect the rights and welfare of human research subjects recruited to participate in research activities conducted under the auspices of the institution with which it is affiliated. The IRB is charged with the responsibility of reviewing all research involving human participants. The IRB is concerned with protecting the welfare, rights, and privacy of human subjects. The IRB has the authority to approve, disapprove, monitor, and require modifications in all research activities that fall within its jurisdiction as specified by both the federal regulations and institutional policy.

Research, according to US federal guidelines, that involves “a living individual about whom an investigator (whether professional or student) conducting research:  (1) Obtains information or biospecimens through intervention or interaction with the individual, and uses, studies, or analyzes the information or biospecimens; or  (2) Obtains, uses, studies, analyzes, or generates identifiable private information or identifiable biospecimens.”

One of the primary methodological traditions of inquiry in qualitative research, ethnography is the study of a group or group culture, largely through observational fieldwork supplemented by interviews. It is a form of fieldwork that may include participant-observation data collection. See chapter 14 for a discussion of deep ethnography. 

A form of interview that follows a standard guide of questions asked, although the order of the questions may change to match the particular needs of each individual interview subject, and probing “follow-up” questions are often added during the course of the interview.  The semi-structured interview is the primary form of interviewing used by qualitative researchers in the social sciences.  It is sometimes referred to as an “in-depth” interview.  See also interview and  interview guide .

A method of observational data collection taking place in a natural setting; a form of fieldwork .  The term encompasses a continuum of relative participation by the researcher (from full participant to “fly-on-the-wall” observer).  This is also sometimes referred to as ethnography , although the latter is characterized by a greater focus on the culture under observation.

A research design that employs both quantitative and qualitative methods, as in the case of a survey supplemented by interviews.

An epistemological perspective that posits the existence of reality through sensory experience similar to empiricism but goes further in denying any non-sensory basis of thought or consciousness.  In the social sciences, the term has roots in the proto-sociologist August Comte, who believed he could discern “laws” of society similar to the laws of natural science (e.g., gravity).  The term has come to mean the kinds of measurable and verifiable science conducted by quantitative researchers and is thus used pejoratively by some qualitative researchers interested in interpretation, consciousness, and human understanding.  Calling someone a “positivist” is often intended as an insult.  See also empiricism and objectivism.

A place or collection containing records, documents, or other materials of historical interest; most universities have an archive of material related to the university’s history, as well as other “special collections” that may be of interest to members of the community.

A method of both data collection and data analysis in which a given content (textual, visual, graphic) is examined systematically and rigorously to identify meanings, themes, patterns and assumptions.  Qualitative content analysis (QCA) is concerned with gathering and interpreting an existing body of material.    

A word or short phrase that symbolically assigns a summative, salient, essence-capturing, and/or evocative attribute for a portion of language-based or visual data (Saldaña 2021:5).

Usually a verbatim written record of an interview or focus group discussion.

The primary form of data for fieldwork , participant observation , and ethnography .  These notes, taken by the researcher either during the course of fieldwork or at day’s end, should include as many details as possible on what was observed and what was said.  They should include clear identifiers of date, time, setting, and names (or identifying characteristics) of participants.

The process of labeling and organizing qualitative data to identify different themes and the relationships between them; a way of simplifying data to allow better management and retrieval of key themes and illustrative passages.  See coding frame and  codebook.

A methodological tradition of inquiry and approach to analyzing qualitative data in which theories emerge from a rigorous and systematic process of induction.  This approach was pioneered by the sociologists Glaser and Strauss (1967).  The elements of theory generated from comparative analysis of data are, first, conceptual categories and their properties and, second, hypotheses or generalized relations among the categories and their properties – “The constant comparing of many groups draws the [researcher’s] attention to their many similarities and differences.  Considering these leads [the researcher] to generate abstract categories and their properties, which, since they emerge from the data, will clearly be important to a theory explaining the kind of behavior under observation.” (36).

A detailed description of any proposed research that involves human subjects for review by IRB.  The protocol serves as the recipe for the conduct of the research activity.  It includes the scientific rationale to justify the conduct of the study, the information necessary to conduct the study, the plan for managing and analyzing the data, and a discussion of the research ethical issues relevant to the research.  Protocols for qualitative research often include interview guides, all documents related to recruitment, informed consent forms, very clear guidelines on the safekeeping of materials collected, and plans for de-identifying transcripts or other data that include personal identifying information.

Introduction to Qualitative Research Methods Copyright © 2023 by Allison Hurst is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License , except where otherwise noted.

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Module 3 Chapter 1: From Research Questions to Research Approaches

The approaches that social work investigators adopt in their research studies are directly related to the nature of the research questions being addressed.In Module 2 you learned about exploratory, descriptive, and explanatory research questions. Let’s consider different approaches to finding answers to each type of question.

In this chapter we build on what was learned in Module 2 about research questions, examining how investigators’ approaches to research are determined by the nature of those questions. The approaches we explore are all systematic, scientific approaches, and when properly conducted and reported, they all contribute empirical evidence to build knowledge.  In this chapter you will read about:

• qualitative research approaches for understanding diverse populations, social problems, and social phenomena,
• quantitative research approaches for understanding diverse populations, social problems, and social phenomena,
• mixed methods research approaches for understanding diverse populations, social problems, and social phenomena.

Overview of Qualitative Approaches

Questions of a descriptive or exploratory nature are often asked and addressed through  qualitative research . The specific aim in these studies is to understand diverse populations, social work problems, or social phenomena as they naturally occur, situated in their natural environments, providing rich, in-depth, participant-centered descriptions of the phenomena being studied. Qualitative research approaches have been described as “humanistic” in aiming to study the world from the perspective of those who are experiencing it themselves; this also contributes to a social justice commitment in that the approaches give “voice” to the individuals who are experiencing the phenomena of interest (Denzen & Lincoln, 2011).  As such, qualitative research approaches are also credited with being sensitive and responsive to diversity—embracing feminist, ethnic, class, critical race, queer, and ability/disability theory and lenses.

In qualitative research, the investigator is engaged as an observer and interpreter, being acutely aware of the subjectivity of the resulting observations and interpretations.

“At this level, qualitative research involves an interpretive, naturalistic approach to the world” (Denzin & Lincoln, 2011, p. 3)

Because the data are rich and deep, a lot of information is collected by involving relatively few participants; otherwise, the investigator would be overwhelmed by a tremendous volume of information to collect, sift through, process, interpret, and analyze. Thus, a single qualitative study has a relatively low level of generalizability  to the population as a whole because of its methodology, but that is not the aim or goal of this approach.

In addition, because the aim is to develop understanding of the participating individuals’ lived experiences, the investigator in a qualitative study seldom imposes structure with standardized measurement tools. The investigator may not even start with preconceived theory and hypotheses. Instead, the methodologies involve a great deal of open-ended triggers, questions, or stimuli to be interpreted by the persons providing insight:

“Qualitative research’s express purpose is to produce descriptive data in an individual’s own written or spoken words and/or observable behavior” (Holosko, 2006, p. 12).

Furthermore, investigators often become a part of the qualitative research process: they maintain awareness of their own influences on the data being collected and on the impact of their own experiences and processes in interpreting the data provided by participants. In some qualitative methodologies, the investigator actually enters into/becomes immersed in the events or phenomena being studied, to both live and observe the experiences first-hand.

Qualitative data and interpretations are recognized as being subjective in nature—that is the purpose—rather than assuming objectivity. Qualitative research is based on experientially derived data and is interpretive, meaning it is “concerned with understanding the meaning of human experience from the subject’s own frame of reference” (Holosko, 2006, p. 13). In this approach, conclusions about the nature of reality are specific to each individual study participant, following his or her own interpretation of that reality. These approaches are considered to flow from an inductive reasoning process where specific themes or patterns are derived from general data (Creswell & Poth, 2018).

Several purposes of qualitative approaches in social work include:

• describing and exploring the nature of phenomena, events, or relationships at any system level (individual to global)
• generating theory
• initially test ideas or assumptions (in theory or about practices)
• evaluate participants’ lived experiences with practices, programs, policies, or participation in a research study, particularly with diverse participants
• explore “fit” of quantitative research conclusions with participants’ lived experiences, particularly with diverse participants
• inform the development of clinical or research assessment/measurement tools, particularly with diverse participants.

Overview of Quantitative Approaches

Questions of the exploratory, descriptive, or explanatory type are often asked and addressed through quantitative research  approaches, particularly questions that have a numeric component. Exploratory and descriptive quantitative studies rely on objective measures for data collection which is a major difference from qualitative studies which are aimed at understanding subjective perspectives and experiences. Explanatory quantitative studies often begin with theory and hypotheses, and proceed to empirically test the hypotheses that investigators generated. By their quantitative (numeric) nature, statistical hypothesis testing is possible in many types of quantitative studies.

Quantitative research studies utilize methodologies that enhance generalizability of results to the greatest extent possible—individual differences are de-emphasized, similarities across individuals are emphasized. These studies can be quite large in terms of participant numbers, and the study samples need to be developed in such a manner as to support generalization to the larger populations of interest.

The process is generally described as following a deductive logical system where specific data points are combined to lead to developing a generalizable conclusion. The philosophical roots (epistemology) underlying quantitative approaches is positivism, involving the seeking of empirical “facts or causes of social phenomena based on experimentallyderived evidence and/or valid observations” (Holosko, 2006, p. 13). The empirical orientation is objective in that investigators attempt to be detached from the collection and interpretation of data in order to minimize their own influences and biases. Furthermore, investigators utilize objective measurement tools to the greatest extent possible in the process of collecting quantitative study data.

Several purposes of quantitative approaches in social work include:

• describing and exploring the dimensions of diverse populations, phenomena, events, or relationships at any system level (individual to global)—how much, how many, how large, how often, etc. (including epidemiology questions and methods)
• testing theory (including etiology questions)
• experimentally determining the existence of relationships between factors that might influence phenomena or relationships at any system level (including epidemiology and etiology questions)
• testing causal pathways between factors that might influence phenomena or relationships at any system level (including etiology questions)
• evaluate quantifiable outcomes of practices, programs, or policies
• assess the reliability and validity of clinical or research assessment/measurement tools.

Overview of Mixed-Method Approaches

Important dimensions distinguish between qualitative and quantitative approaches. First, qualitative approaches rely on “insider” perspectives, whereas quantitative approaches are directed by “outsiders” in the role of investigator (Padgett, 2008). Second, qualitative results are presented holistically, whereas quantitative approaches present results in terms of specific variables dissected from the whole for close examination; qualitative studies emphasize the context of individuals’ experiences, whereas quantitative studies tend to decontextualize the phenomena under study (Padgett, 2008). Third, quantitative research approaches tend to follow a positivist philosophy, seeking objectivity and representation of what actually exists; qualitative research approaches follow from a post-positivist philosophy, recognizing that observation is always shaped by the observer, therefore is always subjective in nature and this should be acknowledged and embraced. In post-positivist qualitative research traditions, realities are perceived as being socially constructed, whereas in positivist quantitative research, a single reality exists, waiting to be discovered or understood. The quantitative perspective on reality has a long tradition in the physical and natural sciences (physics, chemistry, anatomy, physiology, astronomy, and others). The social construction perspective has a strong hold in social science and understanding social phenomena. But what if an investigator’s questions are relevant to both qualitative and quantitative approaches?

Given the fundamental philosophical and practical differences, some scholars argue that there can be no mixing of the approaches, that the underlying paradigms are too different. However, mixed-methods research  has also been described as a new paradigm (since the 1980s) for social science:

“Like the mythology of the phoenix, mixed methods research has arisen out of the ashes of the paradigm wars to become the third methodological movement. The fields of applied social science and evaluation are among those which have shown the greatest popularity and uptake of mixed methods research designs” (Cameron & Miller, 2007, p. 3). 

Mixed-methods research approaches are used to address in a single study the acknowledged limitations of both quantitative and qualitative approaches. Mixed methods research combines elements of both qualitative and quantitative approaches for the purpose of achieving both depth and breadth of understanding, along with corroboration of results (Johnson, Onwuegbuzie, & Turner, 2007, p. 123). One mixed-methods strategy is related to the concept of  triangulation : understanding an event or phenomenon from the use of varied data sources and methods all applied to understanding the same phenomenon (Denzin & Lincoln, 2011; see Figure 1-1).

Figure 1-1. Depiction of triangulation as synthesis of different data sources

For example, in a survey research study of student debt load experienced by social work doctoral students, the investigators gathered quantitative data concerning demographics, dollar amounts of debt and resources, and other numeric data from students and programs (Begun & Carter, 2017). In addition, they collected qualitative data about the experience of incurring and managing debt load, how debt shaped students’ career path decisions, practices around mentoring doctoral students about student debt load, and ideas for addressing the problem. Triangulation came into play in two ways: first, collecting data from students and programs about the topics, and second, a sub-sample of the original surveyed participants engaged in qualitative interviews concerning the “fit” or validity of conclusions drawn from the prior qualitative and quantitative data.

Three different types of mixed methods approaches are used:

• Convergent designs involve the simultaneous collection of both qualitative and quantitative data, followed by analysis of both data sets, and merging the two sets of results in a comparative manner.
• Explanatory sequential designs use quantitative methods first, and then apply qualitative methods to help explain and further interpret the quantitative results.
• Exploratory sequential designs first explore a problem or phenomenon through qualitative methods, especially if the topic is previously unknown or the population is understudied and unfamiliar. These qualitative findings are then used to build the quantitative phase of a project (Creswell, 2014, p. 6).

Mixed methods approaches are useful in developing and testing new research or clinical measurement tools. For example, this is done in an exploratory sequential process whereby detail-rich qualitative data inform the creation of a quantitative instrument. The quantitative instrument is then tested in both quantitative and qualitative ways to confirm that it is adequate for its intended use. This iterative process is depicted in Figure 1-2.

Figure 1-2. Iterative qualitative and quantitative process of instrument development

One example of how this mixed-methods approach was utilized was in development of the Safe-At-Home instrument for assessing individuals’ subjective readiness to change their intimate partner violence behavior (Begun et al., 2003; 2008). The transtheoretical model of behavior change (TMBC) underlies the instrument’s development: identifying stages in readiness to change one’s behavior and matching these stages to the most appropriate type of intervention strategy (Begun et al., 2001). The first step in developing the intimate partner violence Safe-At-Home instrument for assessing readiness to change was to qualitatively generate a list of statements that could be used in a quantitative rating scale. Providers of treatment services to individuals arrested for domestic or relationship violence were engaged in mutual teaching/learning with the investigators concerning the TMBC as it might relate to the perpetration of intimate partner violence. They independently generated lists of the kinds of statements they heard from individuals in their treatment programs, statements they believed were demonstrative of what they understood as the different stages in the change process. The investigators then worked with them to reduce the amassed list of statements into stage-representative categories, eliminating duplicates and ambiguous statements, and retaining the original words and phrases they heard to the greatest extent possible. The second phase was both quantitative and qualitative in nature: testing the instrument with a small sample of men engaged in batters’ treatment programs and interviewing the men about the experience of using the instrument. Based on the results and their feedback, the instrument was revised. This process was followed through several iterations. The next phases were quantitative: determining the psychometric characteristics of the instrument and using it to quantitatively evaluate batterer treatment programs—the extent to which individuals were helped to move forward in stages of the change cycle.

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Chapter Summary

In this chapter you were introduced to three general approaches for moving from research question to research method. You were provided with a brief overview of the philosophical underpinnings and uses of qualitative, quantitative, and mixed-methods approaches. Next, you are provided with more detailed descriptions of qualitative and quantitative traditions and their associated methodologies.

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Designing a Research Question

• Ahmed Ibrahim 3 &
• Camille L. Bryant 3  
• First Online: 29 November 2023

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This chapter discusses (1) the important role of research questions for descriptive, predictive, and causal studies across the three research paradigms (i.e., quantitative, qualitative, and mixed methods); (2) characteristics of quality research questions, and (3) three frameworks to support the development of research questions and their dissemination within scholarly work. For the latter, a description of the P opulation/ P articipants, I ntervention/ I ndependent variable, C omparison, and O utcomes (PICO) framework for quantitative research as well as variations depending on the type of research is provided. Second, we discuss the P articipants, central Ph enomenon, T ime, and S pace (PPhTS) framework for qualitative research. The combination of these frameworks is discussed for mixed-methods research. Further, templates and examples are provided to support the novice health scholar in developing research questions for applied and theoretical studies. Finally, we discuss the Create a Research Space (CARS) model for introducing research questions as part of a research study, to demonstrate how scholars can apply their knowledge when disseminating research.

• Research purpose
• Research objective
• Question formation
• Research question
• PICO framework
• PPhTS framework

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Ibrahim, A., Bryant, C.L. (2023). Designing a Research Question. In: Fitzgerald, A.S., Bosch, G. (eds) Education Scholarship in Healthcare. Springer, Cham. https://doi.org/10.1007/978-3-031-38534-6_4

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Research Skills Tutorial

• Turning A Topic Into A Research Question
• Getting Background Information About Your Topic
• Portfolio Activity 1
• Types of Information Sources
• Scholarly, Popular and Trade Information Sources
• Primary, Secondary and Tertiary Information Sources
• Current and Retrospective Information Sources
• Information Sources for Different Audiences and Purposes
• Portfolio Activity 2
• Library Databases vs. the Web
• Creating a Concept Chart
• Boolean Operators
• Refining Results by Date, Peer Review and Document Type
• Advanced Searching
• Advanced Searching with Descriptors
• Descriptor Chaining
• Citation Chaining (or Reference Mining)
• Searching Outside the SUNY Empire Library
• Searching Google
• Portfolio Activity 3
• Understanding Search Results
• Saving Search Results
• Portfolio Activity 4
• Credible Sources
• What Does the Information Source Tell You About Itself?
• Reliability
• Some More About Validity
• Portfolio Activity 5
• What Is Citing?
• What Is a Citation?
• Citation Styles
• Citing Tools and Tips
• Practice Activity 6
• Practice Activity 7 - Final Project

What You Will Learn In Chapter 1

Learning objectives.

At the end of this section, you will be able to:

• develop a sufficiently narrow research question from a broader starting topic.
• get background information on and increase your understanding of terminology related to your research topic, using reference sources such as encyclopedias and dictionaries.
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• Knowledge Base
• Starting the research process
• 10 Research Question Examples to Guide Your Research Project

10 Research Question Examples to Guide your Research Project

Published on October 30, 2022 by Shona McCombes . Revised on October 19, 2023.

The research question is one of the most important parts of your research paper , thesis or dissertation . It’s important to spend some time assessing and refining your question before you get started.

The exact form of your question will depend on a few things, such as the length of your project, the type of research you’re conducting, the topic , and the research problem . However, all research questions should be focused, specific, and relevant to a timely social or scholarly issue.

Once you’ve read our guide on how to write a research question , you can use these examples to craft your own.

Note that the design of your research question can depend on what method you are pursuing. Here are a few options for qualitative, quantitative, and statistical research questions.

Other interesting articles

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

Methodology

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

 Statistics

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

Research bias

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

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Chapter 1: Forming the Research Question and Completing Research

By the end of this chapter, you should be able to:

• Answer key questions regarding a library search using library website (LO1)
• Execute better strategies for a successful search. (LO2)
• Locate scholarly resources using the library (LO3)

What is Research?

There are three types of research to know.

• A search for facts or data . This may be part of the search for the solution to a larger problem to simply the answer to simple question. Concerned with facts rather than knowledge or analysis. It is usually answers that can normally be found in a single source. Example: How did the band Queen decide on its name?
• A report or review to collect and synthesize existing information. This is a summary of the past. These answers can typically be found in a selection of books, articles, and web sites. Example: What is the history of pasta making?
• Gathering and analyzing a body of information for new meaning from it or developing unique solutions. This is “real” research and requires an open-ended question, which does not have a clear answer. This research type will very often include both of the previous types. Example: Determine whether gang violence is directly related to playing graphic video games.

Generating a Research Question

Review the resources below to learn more about how to generate a research question. Select the double-pointed arrow in the lower right corner to expand to full screen.

You have a focused, but not too focused, research question ready to go for a given project. But where do you begin searching? Below is general information about how to start.

General Web Searching

A search engine is something like Google or Bing, where algorithms are used to locate websites that align with the key words entered in the search bar. Search engines are great because they are broad, convenient, and free. Sometimes the information is too broad to find relevant materials or it is difficult to determine the credibility of the information. If you are looking for more general information, like Census data, general web searching with a search engine may be the best place to search.

Library Database

Library databases are collections of published information from books, magazines, newspapers, and journals. They can be focused on a single discipline or more general to include all disciplines. Libraries pay subscription fees so that faculty, staff, and students can access these databases as needed. You will need to use your university login and password to access these databases. Databases are great for research because they are reliable, relevant, and accessible. If you are looking for credible, scholarly sources, the library databases will be your best option.

Academic Search Complete is a great general database to find articles on most topics. Contact a librarian if you need recommendations or assistance.

Wikipedia is a free, online encyclopedia. When using it, keep in mind that anyone can add, create, or edit information. It is great for gathering general background information, generate search terms, or even to find potential sources. But it is important to note that it is user-created and has no mandatory review process. There is no guarantee the information is reliable, no credentials are provided, and can often contain biases.

References for Content:

EBSCO Tutorials (2022, March 23). EBSCOhost basic search – tutorial [Video]. YouTube. https://www.youtube.com/watch?v=vT833d5F2yI

Frances Wilson Thompson Library (2019. September 17). Brainstorming a research topic using a concept map {YouTube]. https://www.youtube.com/watch?v=AVtkrnHjMPk

PALNI (2022, June 3). Forming your research question. PALNI Information Literacy Modules. https://libguides.palni.edu/instruction_resources/ILModule1

PALNI (2022, June 3). Searching for information online . PALNI Information Literacy Modules. https://libguides.palni.edu/instruction_resources/ILModule2

SciToons (2020, October 5). What is research? [Video]. YouTube. https://www.youtube.com/watch?v=mV0bUQpz468

Steely Library NKU (2018, January 4). Developing a research question [Video]. YouTube. https://www.youtube.com/watch?v=QauomrFcrXk

TAMU Writing Center (2016, March 8). Brainstorming [Video]. YouTube. https://www.youtube.com/watch?v=HSufG-AIQYo

Research and Information Literacy with Library Resources by Andrea Bearman and Jill Noyes is licensed under a Creative Commons Attribution 4.0 International License , except where otherwise noted.

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An Introduction to Qualitative Research

Student resources, developing a research question.

Watch the videos for introductions to the key aspects of qualitative research.