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What Is Qualitative Research? | Methods & Examples
Published on June 19, 2020 by Pritha Bhandari . Revised on June 22, 2023.
Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.
Qualitative research is the opposite of quantitative research , which involves collecting and analyzing numerical data for statistical analysis.
Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, history, etc.
- How does social media shape body image in teenagers?
- How do children and adults interpret healthy eating in the UK?
- What factors influence employee retention in a large organization?
- How is anxiety experienced around the world?
- How can teachers integrate social issues into science curriculums?
Table of contents
Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, other interesting articles, frequently asked questions about qualitative research.
Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.
Common approaches include grounded theory, ethnography , action research , phenomenological research, and narrative research. They share some similarities, but emphasize different aims and perspectives.
Approach | What does it involve? |
---|---|
Grounded theory | Researchers collect rich data on a topic of interest and develop theories . |
Researchers immerse themselves in groups or organizations to understand their cultures. | |
Action research | Researchers and participants collaboratively link theory to practice to drive social change. |
Phenomenological research | Researchers investigate a phenomenon or event by describing and interpreting participants’ lived experiences. |
Narrative research | Researchers examine how stories are told to understand how participants perceive and make sense of their experiences. |
Note that qualitative research is at risk for certain research biases including the Hawthorne effect , observer bias , recall bias , and social desirability bias . While not always totally avoidable, awareness of potential biases as you collect and analyze your data can prevent them from impacting your work too much.
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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:
- Observations: recording what you have seen, heard, or encountered in detailed field notes.
- Interviews: personally asking people questions in one-on-one conversations.
- Focus groups: asking questions and generating discussion among a group of people.
- Surveys : distributing questionnaires with open-ended questions.
- Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
- You take field notes with observations and reflect on your own experiences of the company culture.
- You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
- You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.
Qualitative researchers often consider themselves “instruments” in research because all observations, interpretations and analyses are filtered through their own personal lens.
For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analyzing the data.
Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.
Most types of qualitative data analysis share the same five steps:
- Prepare and organize your data. This may mean transcribing interviews or typing up fieldnotes.
- Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
- Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorize your data.
- Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
- Identify recurring themes. Link codes together into cohesive, overarching themes.
There are several specific approaches to analyzing qualitative data. Although these methods share similar processes, they emphasize different concepts.
Approach | When to use | Example |
---|---|---|
To describe and categorize common words, phrases, and ideas in qualitative data. | A market researcher could perform content analysis to find out what kind of language is used in descriptions of therapeutic apps. | |
To identify and interpret patterns and themes in qualitative data. | A psychologist could apply thematic analysis to travel blogs to explore how tourism shapes self-identity. | |
To examine the content, structure, and design of texts. | A media researcher could use textual analysis to understand how news coverage of celebrities has changed in the past decade. | |
To study communication and how language is used to achieve effects in specific contexts. | A political scientist could use discourse analysis to study how politicians generate trust in election campaigns. |
Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:
- Flexibility
The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.
- Natural settings
Data collection occurs in real-world contexts or in naturalistic ways.
- Meaningful insights
Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.
- Generation of new ideas
Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.
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Researchers must consider practical and theoretical limitations in analyzing and interpreting their data. Qualitative research suffers from:
- Unreliability
The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.
- Subjectivity
Due to the researcher’s primary role in analyzing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.
- Limited generalizability
Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalizable conclusions because the data may be biased and unrepresentative of the wider population .
- Labor-intensive
Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.
If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.
- Chi square goodness of fit test
- Degrees of freedom
- Null hypothesis
- Discourse analysis
- Control groups
- Mixed methods research
- Non-probability sampling
- Quantitative research
- Inclusion and exclusion criteria
Research bias
- Rosenthal effect
- Implicit bias
- Cognitive bias
- Selection bias
- Negativity bias
- Status quo bias
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to systematically measure variables and test hypotheses . Qualitative methods allow you to explore concepts and experiences in more detail.
There are five common approaches to qualitative research :
- Grounded theory involves collecting data in order to develop new theories.
- Ethnography involves immersing yourself in a group or organization to understand its culture.
- Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
- Phenomenological research involves investigating phenomena through people’s lived experiences.
- Action research links theory and practice in several cycles to drive innovative changes.
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organizations.
There are various approaches to qualitative data analysis , but they all share five steps in common:
- Prepare and organize your data.
- Review and explore your data.
- Develop a data coding system.
- Assign codes to the data.
- Identify recurring themes.
The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .
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How to use and assess qualitative research methods
Loraine busetto.
1 Department of Neurology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany
Wolfgang Wick
2 Clinical Cooperation Unit Neuro-Oncology, German Cancer Research Center, Heidelberg, Germany
Christoph Gumbinger
Associated data.
Not applicable.
This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions, and focussing on intervention improvement. The most common methods of data collection are document study, (non-) participant observations, semi-structured interviews and focus groups. For data analysis, field-notes and audio-recordings are transcribed into protocols and transcripts, and coded using qualitative data management software. Criteria such as checklists, reflexivity, sampling strategies, piloting, co-coding, member-checking and stakeholder involvement can be used to enhance and assess the quality of the research conducted. Using qualitative in addition to quantitative designs will equip us with better tools to address a greater range of research problems, and to fill in blind spots in current neurological research and practice.
The aim of this paper is to provide an overview of qualitative research methods, including hands-on information on how they can be used, reported and assessed. This article is intended for beginning qualitative researchers in the health sciences as well as experienced quantitative researchers who wish to broaden their understanding of qualitative research.
What is qualitative research?
Qualitative research is defined as “the study of the nature of phenomena”, including “their quality, different manifestations, the context in which they appear or the perspectives from which they can be perceived” , but excluding “their range, frequency and place in an objectively determined chain of cause and effect” [ 1 ]. This formal definition can be complemented with a more pragmatic rule of thumb: qualitative research generally includes data in form of words rather than numbers [ 2 ].
Why conduct qualitative research?
Because some research questions cannot be answered using (only) quantitative methods. For example, one Australian study addressed the issue of why patients from Aboriginal communities often present late or not at all to specialist services offered by tertiary care hospitals. Using qualitative interviews with patients and staff, it found one of the most significant access barriers to be transportation problems, including some towns and communities simply not having a bus service to the hospital [ 3 ]. A quantitative study could have measured the number of patients over time or even looked at possible explanatory factors – but only those previously known or suspected to be of relevance. To discover reasons for observed patterns, especially the invisible or surprising ones, qualitative designs are needed.
While qualitative research is common in other fields, it is still relatively underrepresented in health services research. The latter field is more traditionally rooted in the evidence-based-medicine paradigm, as seen in " research that involves testing the effectiveness of various strategies to achieve changes in clinical practice, preferably applying randomised controlled trial study designs (...) " [ 4 ]. This focus on quantitative research and specifically randomised controlled trials (RCT) is visible in the idea of a hierarchy of research evidence which assumes that some research designs are objectively better than others, and that choosing a "lesser" design is only acceptable when the better ones are not practically or ethically feasible [ 5 , 6 ]. Others, however, argue that an objective hierarchy does not exist, and that, instead, the research design and methods should be chosen to fit the specific research question at hand – "questions before methods" [ 2 , 7 – 9 ]. This means that even when an RCT is possible, some research problems require a different design that is better suited to addressing them. Arguing in JAMA, Berwick uses the example of rapid response teams in hospitals, which he describes as " a complex, multicomponent intervention – essentially a process of social change" susceptible to a range of different context factors including leadership or organisation history. According to him, "[in] such complex terrain, the RCT is an impoverished way to learn. Critics who use it as a truth standard in this context are incorrect" [ 8 ] . Instead of limiting oneself to RCTs, Berwick recommends embracing a wider range of methods , including qualitative ones, which for "these specific applications, (...) are not compromises in learning how to improve; they are superior" [ 8 ].
Research problems that can be approached particularly well using qualitative methods include assessing complex multi-component interventions or systems (of change), addressing questions beyond “what works”, towards “what works for whom when, how and why”, and focussing on intervention improvement rather than accreditation [ 7 , 9 – 12 ]. Using qualitative methods can also help shed light on the “softer” side of medical treatment. For example, while quantitative trials can measure the costs and benefits of neuro-oncological treatment in terms of survival rates or adverse effects, qualitative research can help provide a better understanding of patient or caregiver stress, visibility of illness or out-of-pocket expenses.
How to conduct qualitative research?
Given that qualitative research is characterised by flexibility, openness and responsivity to context, the steps of data collection and analysis are not as separate and consecutive as they tend to be in quantitative research [ 13 , 14 ]. As Fossey puts it : “sampling, data collection, analysis and interpretation are related to each other in a cyclical (iterative) manner, rather than following one after another in a stepwise approach” [ 15 ]. The researcher can make educated decisions with regard to the choice of method, how they are implemented, and to which and how many units they are applied [ 13 ]. As shown in Fig. 1 , this can involve several back-and-forth steps between data collection and analysis where new insights and experiences can lead to adaption and expansion of the original plan. Some insights may also necessitate a revision of the research question and/or the research design as a whole. The process ends when saturation is achieved, i.e. when no relevant new information can be found (see also below: sampling and saturation). For reasons of transparency, it is essential for all decisions as well as the underlying reasoning to be well-documented.
![Click on image to zoom An external file that holds a picture, illustration, etc.
Object name is 42466_2020_59_Fig1_HTML.jpg](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7650082/bin/42466_2020_59_Fig1_HTML.jpg)
Iterative research process
While it is not always explicitly addressed, qualitative methods reflect a different underlying research paradigm than quantitative research (e.g. constructivism or interpretivism as opposed to positivism). The choice of methods can be based on the respective underlying substantive theory or theoretical framework used by the researcher [ 2 ].
Data collection
The methods of qualitative data collection most commonly used in health research are document study, observations, semi-structured interviews and focus groups [ 1 , 14 , 16 , 17 ].
Document study
Document study (also called document analysis) refers to the review by the researcher of written materials [ 14 ]. These can include personal and non-personal documents such as archives, annual reports, guidelines, policy documents, diaries or letters.
Observations
Observations are particularly useful to gain insights into a certain setting and actual behaviour – as opposed to reported behaviour or opinions [ 13 ]. Qualitative observations can be either participant or non-participant in nature. In participant observations, the observer is part of the observed setting, for example a nurse working in an intensive care unit [ 18 ]. In non-participant observations, the observer is “on the outside looking in”, i.e. present in but not part of the situation, trying not to influence the setting by their presence. Observations can be planned (e.g. for 3 h during the day or night shift) or ad hoc (e.g. as soon as a stroke patient arrives at the emergency room). During the observation, the observer takes notes on everything or certain pre-determined parts of what is happening around them, for example focusing on physician-patient interactions or communication between different professional groups. Written notes can be taken during or after the observations, depending on feasibility (which is usually lower during participant observations) and acceptability (e.g. when the observer is perceived to be judging the observed). Afterwards, these field notes are transcribed into observation protocols. If more than one observer was involved, field notes are taken independently, but notes can be consolidated into one protocol after discussions. Advantages of conducting observations include minimising the distance between the researcher and the researched, the potential discovery of topics that the researcher did not realise were relevant and gaining deeper insights into the real-world dimensions of the research problem at hand [ 18 ].
Semi-structured interviews
Hijmans & Kuyper describe qualitative interviews as “an exchange with an informal character, a conversation with a goal” [ 19 ]. Interviews are used to gain insights into a person’s subjective experiences, opinions and motivations – as opposed to facts or behaviours [ 13 ]. Interviews can be distinguished by the degree to which they are structured (i.e. a questionnaire), open (e.g. free conversation or autobiographical interviews) or semi-structured [ 2 , 13 ]. Semi-structured interviews are characterized by open-ended questions and the use of an interview guide (or topic guide/list) in which the broad areas of interest, sometimes including sub-questions, are defined [ 19 ]. The pre-defined topics in the interview guide can be derived from the literature, previous research or a preliminary method of data collection, e.g. document study or observations. The topic list is usually adapted and improved at the start of the data collection process as the interviewer learns more about the field [ 20 ]. Across interviews the focus on the different (blocks of) questions may differ and some questions may be skipped altogether (e.g. if the interviewee is not able or willing to answer the questions or for concerns about the total length of the interview) [ 20 ]. Qualitative interviews are usually not conducted in written format as it impedes on the interactive component of the method [ 20 ]. In comparison to written surveys, qualitative interviews have the advantage of being interactive and allowing for unexpected topics to emerge and to be taken up by the researcher. This can also help overcome a provider or researcher-centred bias often found in written surveys, which by nature, can only measure what is already known or expected to be of relevance to the researcher. Interviews can be audio- or video-taped; but sometimes it is only feasible or acceptable for the interviewer to take written notes [ 14 , 16 , 20 ].
Focus groups
Focus groups are group interviews to explore participants’ expertise and experiences, including explorations of how and why people behave in certain ways [ 1 ]. Focus groups usually consist of 6–8 people and are led by an experienced moderator following a topic guide or “script” [ 21 ]. They can involve an observer who takes note of the non-verbal aspects of the situation, possibly using an observation guide [ 21 ]. Depending on researchers’ and participants’ preferences, the discussions can be audio- or video-taped and transcribed afterwards [ 21 ]. Focus groups are useful for bringing together homogeneous (to a lesser extent heterogeneous) groups of participants with relevant expertise and experience on a given topic on which they can share detailed information [ 21 ]. Focus groups are a relatively easy, fast and inexpensive method to gain access to information on interactions in a given group, i.e. “the sharing and comparing” among participants [ 21 ]. Disadvantages include less control over the process and a lesser extent to which each individual may participate. Moreover, focus group moderators need experience, as do those tasked with the analysis of the resulting data. Focus groups can be less appropriate for discussing sensitive topics that participants might be reluctant to disclose in a group setting [ 13 ]. Moreover, attention must be paid to the emergence of “groupthink” as well as possible power dynamics within the group, e.g. when patients are awed or intimidated by health professionals.
Choosing the “right” method
As explained above, the school of thought underlying qualitative research assumes no objective hierarchy of evidence and methods. This means that each choice of single or combined methods has to be based on the research question that needs to be answered and a critical assessment with regard to whether or to what extent the chosen method can accomplish this – i.e. the “fit” between question and method [ 14 ]. It is necessary for these decisions to be documented when they are being made, and to be critically discussed when reporting methods and results.
Let us assume that our research aim is to examine the (clinical) processes around acute endovascular treatment (EVT), from the patient’s arrival at the emergency room to recanalization, with the aim to identify possible causes for delay and/or other causes for sub-optimal treatment outcome. As a first step, we could conduct a document study of the relevant standard operating procedures (SOPs) for this phase of care – are they up-to-date and in line with current guidelines? Do they contain any mistakes, irregularities or uncertainties that could cause delays or other problems? Regardless of the answers to these questions, the results have to be interpreted based on what they are: a written outline of what care processes in this hospital should look like. If we want to know what they actually look like in practice, we can conduct observations of the processes described in the SOPs. These results can (and should) be analysed in themselves, but also in comparison to the results of the document analysis, especially as regards relevant discrepancies. Do the SOPs outline specific tests for which no equipment can be observed or tasks to be performed by specialized nurses who are not present during the observation? It might also be possible that the written SOP is outdated, but the actual care provided is in line with current best practice. In order to find out why these discrepancies exist, it can be useful to conduct interviews. Are the physicians simply not aware of the SOPs (because their existence is limited to the hospital’s intranet) or do they actively disagree with them or does the infrastructure make it impossible to provide the care as described? Another rationale for adding interviews is that some situations (or all of their possible variations for different patient groups or the day, night or weekend shift) cannot practically or ethically be observed. In this case, it is possible to ask those involved to report on their actions – being aware that this is not the same as the actual observation. A senior physician’s or hospital manager’s description of certain situations might differ from a nurse’s or junior physician’s one, maybe because they intentionally misrepresent facts or maybe because different aspects of the process are visible or important to them. In some cases, it can also be relevant to consider to whom the interviewee is disclosing this information – someone they trust, someone they are otherwise not connected to, or someone they suspect or are aware of being in a potentially “dangerous” power relationship to them. Lastly, a focus group could be conducted with representatives of the relevant professional groups to explore how and why exactly they provide care around EVT. The discussion might reveal discrepancies (between SOPs and actual care or between different physicians) and motivations to the researchers as well as to the focus group members that they might not have been aware of themselves. For the focus group to deliver relevant information, attention has to be paid to its composition and conduct, for example, to make sure that all participants feel safe to disclose sensitive or potentially problematic information or that the discussion is not dominated by (senior) physicians only. The resulting combination of data collection methods is shown in Fig. 2 .
![Click on image to zoom An external file that holds a picture, illustration, etc.
Object name is 42466_2020_59_Fig2_HTML.jpg](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7650082/bin/42466_2020_59_Fig2_HTML.jpg)
Possible combination of data collection methods
Attributions for icons: “Book” by Serhii Smirnov, “Interview” by Adrien Coquet, FR, “Magnifying Glass” by anggun, ID, “Business communication” by Vectors Market; all from the Noun Project
The combination of multiple data source as described for this example can be referred to as “triangulation”, in which multiple measurements are carried out from different angles to achieve a more comprehensive understanding of the phenomenon under study [ 22 , 23 ].
Data analysis
To analyse the data collected through observations, interviews and focus groups these need to be transcribed into protocols and transcripts (see Fig. 3 ). Interviews and focus groups can be transcribed verbatim , with or without annotations for behaviour (e.g. laughing, crying, pausing) and with or without phonetic transcription of dialects and filler words, depending on what is expected or known to be relevant for the analysis. In the next step, the protocols and transcripts are coded , that is, marked (or tagged, labelled) with one or more short descriptors of the content of a sentence or paragraph [ 2 , 15 , 23 ]. Jansen describes coding as “connecting the raw data with “theoretical” terms” [ 20 ]. In a more practical sense, coding makes raw data sortable. This makes it possible to extract and examine all segments describing, say, a tele-neurology consultation from multiple data sources (e.g. SOPs, emergency room observations, staff and patient interview). In a process of synthesis and abstraction, the codes are then grouped, summarised and/or categorised [ 15 , 20 ]. The end product of the coding or analysis process is a descriptive theory of the behavioural pattern under investigation [ 20 ]. The coding process is performed using qualitative data management software, the most common ones being InVivo, MaxQDA and Atlas.ti. It should be noted that these are data management tools which support the analysis performed by the researcher(s) [ 14 ].
![Click on image to zoom An external file that holds a picture, illustration, etc.
Object name is 42466_2020_59_Fig3_HTML.jpg](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7650082/bin/42466_2020_59_Fig3_HTML.jpg)
From data collection to data analysis
Attributions for icons: see Fig. Fig.2, 2 , also “Speech to text” by Trevor Dsouza, “Field Notes” by Mike O’Brien, US, “Voice Record” by ProSymbols, US, “Inspection” by Made, AU, and “Cloud” by Graphic Tigers; all from the Noun Project
How to report qualitative research?
Protocols of qualitative research can be published separately and in advance of the study results. However, the aim is not the same as in RCT protocols, i.e. to pre-define and set in stone the research questions and primary or secondary endpoints. Rather, it is a way to describe the research methods in detail, which might not be possible in the results paper given journals’ word limits. Qualitative research papers are usually longer than their quantitative counterparts to allow for deep understanding and so-called “thick description”. In the methods section, the focus is on transparency of the methods used, including why, how and by whom they were implemented in the specific study setting, so as to enable a discussion of whether and how this may have influenced data collection, analysis and interpretation. The results section usually starts with a paragraph outlining the main findings, followed by more detailed descriptions of, for example, the commonalities, discrepancies or exceptions per category [ 20 ]. Here it is important to support main findings by relevant quotations, which may add information, context, emphasis or real-life examples [ 20 , 23 ]. It is subject to debate in the field whether it is relevant to state the exact number or percentage of respondents supporting a certain statement (e.g. “Five interviewees expressed negative feelings towards XYZ”) [ 21 ].
How to combine qualitative with quantitative research?
Qualitative methods can be combined with other methods in multi- or mixed methods designs, which “[employ] two or more different methods [ …] within the same study or research program rather than confining the research to one single method” [ 24 ]. Reasons for combining methods can be diverse, including triangulation for corroboration of findings, complementarity for illustration and clarification of results, expansion to extend the breadth and range of the study, explanation of (unexpected) results generated with one method with the help of another, or offsetting the weakness of one method with the strength of another [ 1 , 17 , 24 – 26 ]. The resulting designs can be classified according to when, why and how the different quantitative and/or qualitative data strands are combined. The three most common types of mixed method designs are the convergent parallel design , the explanatory sequential design and the exploratory sequential design. The designs with examples are shown in Fig. 4 .
![Click on image to zoom An external file that holds a picture, illustration, etc.
Object name is 42466_2020_59_Fig4_HTML.jpg](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7650082/bin/42466_2020_59_Fig4_HTML.jpg)
Three common mixed methods designs
In the convergent parallel design, a qualitative study is conducted in parallel to and independently of a quantitative study, and the results of both studies are compared and combined at the stage of interpretation of results. Using the above example of EVT provision, this could entail setting up a quantitative EVT registry to measure process times and patient outcomes in parallel to conducting the qualitative research outlined above, and then comparing results. Amongst other things, this would make it possible to assess whether interview respondents’ subjective impressions of patients receiving good care match modified Rankin Scores at follow-up, or whether observed delays in care provision are exceptions or the rule when compared to door-to-needle times as documented in the registry. In the explanatory sequential design, a quantitative study is carried out first, followed by a qualitative study to help explain the results from the quantitative study. This would be an appropriate design if the registry alone had revealed relevant delays in door-to-needle times and the qualitative study would be used to understand where and why these occurred, and how they could be improved. In the exploratory design, the qualitative study is carried out first and its results help informing and building the quantitative study in the next step [ 26 ]. If the qualitative study around EVT provision had shown a high level of dissatisfaction among the staff members involved, a quantitative questionnaire investigating staff satisfaction could be set up in the next step, informed by the qualitative study on which topics dissatisfaction had been expressed. Amongst other things, the questionnaire design would make it possible to widen the reach of the research to more respondents from different (types of) hospitals, regions, countries or settings, and to conduct sub-group analyses for different professional groups.
How to assess qualitative research?
A variety of assessment criteria and lists have been developed for qualitative research, ranging in their focus and comprehensiveness [ 14 , 17 , 27 ]. However, none of these has been elevated to the “gold standard” in the field. In the following, we therefore focus on a set of commonly used assessment criteria that, from a practical standpoint, a researcher can look for when assessing a qualitative research report or paper.
Assessors should check the authors’ use of and adherence to the relevant reporting checklists (e.g. Standards for Reporting Qualitative Research (SRQR)) to make sure all items that are relevant for this type of research are addressed [ 23 , 28 ]. Discussions of quantitative measures in addition to or instead of these qualitative measures can be a sign of lower quality of the research (paper). Providing and adhering to a checklist for qualitative research contributes to an important quality criterion for qualitative research, namely transparency [ 15 , 17 , 23 ].
Reflexivity
While methodological transparency and complete reporting is relevant for all types of research, some additional criteria must be taken into account for qualitative research. This includes what is called reflexivity, i.e. sensitivity to the relationship between the researcher and the researched, including how contact was established and maintained, or the background and experience of the researcher(s) involved in data collection and analysis. Depending on the research question and population to be researched this can be limited to professional experience, but it may also include gender, age or ethnicity [ 17 , 27 ]. These details are relevant because in qualitative research, as opposed to quantitative research, the researcher as a person cannot be isolated from the research process [ 23 ]. It may influence the conversation when an interviewed patient speaks to an interviewer who is a physician, or when an interviewee is asked to discuss a gynaecological procedure with a male interviewer, and therefore the reader must be made aware of these details [ 19 ].
Sampling and saturation
The aim of qualitative sampling is for all variants of the objects of observation that are deemed relevant for the study to be present in the sample “ to see the issue and its meanings from as many angles as possible” [ 1 , 16 , 19 , 20 , 27 ] , and to ensure “information-richness [ 15 ]. An iterative sampling approach is advised, in which data collection (e.g. five interviews) is followed by data analysis, followed by more data collection to find variants that are lacking in the current sample. This process continues until no new (relevant) information can be found and further sampling becomes redundant – which is called saturation [ 1 , 15 ] . In other words: qualitative data collection finds its end point not a priori , but when the research team determines that saturation has been reached [ 29 , 30 ].
This is also the reason why most qualitative studies use deliberate instead of random sampling strategies. This is generally referred to as “ purposive sampling” , in which researchers pre-define which types of participants or cases they need to include so as to cover all variations that are expected to be of relevance, based on the literature, previous experience or theory (i.e. theoretical sampling) [ 14 , 20 ]. Other types of purposive sampling include (but are not limited to) maximum variation sampling, critical case sampling or extreme or deviant case sampling [ 2 ]. In the above EVT example, a purposive sample could include all relevant professional groups and/or all relevant stakeholders (patients, relatives) and/or all relevant times of observation (day, night and weekend shift).
Assessors of qualitative research should check whether the considerations underlying the sampling strategy were sound and whether or how researchers tried to adapt and improve their strategies in stepwise or cyclical approaches between data collection and analysis to achieve saturation [ 14 ].
Good qualitative research is iterative in nature, i.e. it goes back and forth between data collection and analysis, revising and improving the approach where necessary. One example of this are pilot interviews, where different aspects of the interview (especially the interview guide, but also, for example, the site of the interview or whether the interview can be audio-recorded) are tested with a small number of respondents, evaluated and revised [ 19 ]. In doing so, the interviewer learns which wording or types of questions work best, or which is the best length of an interview with patients who have trouble concentrating for an extended time. Of course, the same reasoning applies to observations or focus groups which can also be piloted.
Ideally, coding should be performed by at least two researchers, especially at the beginning of the coding process when a common approach must be defined, including the establishment of a useful coding list (or tree), and when a common meaning of individual codes must be established [ 23 ]. An initial sub-set or all transcripts can be coded independently by the coders and then compared and consolidated after regular discussions in the research team. This is to make sure that codes are applied consistently to the research data.
Member checking
Member checking, also called respondent validation , refers to the practice of checking back with study respondents to see if the research is in line with their views [ 14 , 27 ]. This can happen after data collection or analysis or when first results are available [ 23 ]. For example, interviewees can be provided with (summaries of) their transcripts and asked whether they believe this to be a complete representation of their views or whether they would like to clarify or elaborate on their responses [ 17 ]. Respondents’ feedback on these issues then becomes part of the data collection and analysis [ 27 ].
Stakeholder involvement
In those niches where qualitative approaches have been able to evolve and grow, a new trend has seen the inclusion of patients and their representatives not only as study participants (i.e. “members”, see above) but as consultants to and active participants in the broader research process [ 31 – 33 ]. The underlying assumption is that patients and other stakeholders hold unique perspectives and experiences that add value beyond their own single story, making the research more relevant and beneficial to researchers, study participants and (future) patients alike [ 34 , 35 ]. Using the example of patients on or nearing dialysis, a recent scoping review found that 80% of clinical research did not address the top 10 research priorities identified by patients and caregivers [ 32 , 36 ]. In this sense, the involvement of the relevant stakeholders, especially patients and relatives, is increasingly being seen as a quality indicator in and of itself.
How not to assess qualitative research
The above overview does not include certain items that are routine in assessments of quantitative research. What follows is a non-exhaustive, non-representative, experience-based list of the quantitative criteria often applied to the assessment of qualitative research, as well as an explanation of the limited usefulness of these endeavours.
Protocol adherence
Given the openness and flexibility of qualitative research, it should not be assessed by how well it adheres to pre-determined and fixed strategies – in other words: its rigidity. Instead, the assessor should look for signs of adaptation and refinement based on lessons learned from earlier steps in the research process.
Sample size
For the reasons explained above, qualitative research does not require specific sample sizes, nor does it require that the sample size be determined a priori [ 1 , 14 , 27 , 37 – 39 ]. Sample size can only be a useful quality indicator when related to the research purpose, the chosen methodology and the composition of the sample, i.e. who was included and why.
Randomisation
While some authors argue that randomisation can be used in qualitative research, this is not commonly the case, as neither its feasibility nor its necessity or usefulness has been convincingly established for qualitative research [ 13 , 27 ]. Relevant disadvantages include the negative impact of a too large sample size as well as the possibility (or probability) of selecting “ quiet, uncooperative or inarticulate individuals ” [ 17 ]. Qualitative studies do not use control groups, either.
Interrater reliability, variability and other “objectivity checks”
The concept of “interrater reliability” is sometimes used in qualitative research to assess to which extent the coding approach overlaps between the two co-coders. However, it is not clear what this measure tells us about the quality of the analysis [ 23 ]. This means that these scores can be included in qualitative research reports, preferably with some additional information on what the score means for the analysis, but it is not a requirement. Relatedly, it is not relevant for the quality or “objectivity” of qualitative research to separate those who recruited the study participants and collected and analysed the data. Experiences even show that it might be better to have the same person or team perform all of these tasks [ 20 ]. First, when researchers introduce themselves during recruitment this can enhance trust when the interview takes place days or weeks later with the same researcher. Second, when the audio-recording is transcribed for analysis, the researcher conducting the interviews will usually remember the interviewee and the specific interview situation during data analysis. This might be helpful in providing additional context information for interpretation of data, e.g. on whether something might have been meant as a joke [ 18 ].
Not being quantitative research
Being qualitative research instead of quantitative research should not be used as an assessment criterion if it is used irrespectively of the research problem at hand. Similarly, qualitative research should not be required to be combined with quantitative research per se – unless mixed methods research is judged as inherently better than single-method research. In this case, the same criterion should be applied for quantitative studies without a qualitative component.
The main take-away points of this paper are summarised in Table Table1. 1 . We aimed to show that, if conducted well, qualitative research can answer specific research questions that cannot to be adequately answered using (only) quantitative designs. Seeing qualitative and quantitative methods as equal will help us become more aware and critical of the “fit” between the research problem and our chosen methods: I can conduct an RCT to determine the reasons for transportation delays of acute stroke patients – but should I? It also provides us with a greater range of tools to tackle a greater range of research problems more appropriately and successfully, filling in the blind spots on one half of the methodological spectrum to better address the whole complexity of neurological research and practice.
Take-away-points
• Assessing complex multi-component interventions or systems (of change) • What works for whom when, how and why? • Focussing on intervention improvement | • Document study • Observations (participant or non-participant) • Interviews (especially semi-structured) • Focus groups | • Transcription of audio-recordings and field notes into transcripts and protocols • Coding of protocols • Using qualitative data management software |
• Combinations of quantitative and/or qualitative methods, e.g.: • : quali and quanti in parallel • : quanti followed by quali • : quali followed by quanti | • Checklists • Reflexivity • Sampling strategies • Piloting • Co-coding • Member checking • Stakeholder involvement | • Protocol adherence • Sample size • Randomization • Interrater reliability, variability and other “objectivity checks” • Not being quantitative research |
Acknowledgements
Abbreviations.
EVT | Endovascular treatment |
RCT | Randomised Controlled Trial |
SOP | Standard Operating Procedure |
SRQR | Standards for Reporting Qualitative Research |
Authors’ contributions
LB drafted the manuscript; WW and CG revised the manuscript; all authors approved the final versions.
no external funding.
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The authors declare no competing interests.
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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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Research Methods: Qualitative
What is qualitative research, about this guide, introduction.
- Qualitative Research Approaches
- Key Resources
- Finding Qualitative Studies
The purpose of this guide is to provide a starting point for learning about qualitative research. In this guide, you'll find:
- Resources on diverse types of qualitative research
- An overview of resources for data, methods, coding & analysis
- Popular qualitative software options
- Information on how to find qualitative studies
Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research. It answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data.
Qualitative researchers use multiple systems of inquiry for the study of human phenomena including biography, case study, historical analysis, discourse analysis, ethnography, grounded theory, and phenomenology.
Watch the following video to learn more about Qualitative Research:
(Video best viewed in Edge and Chrome browsers, or click here to view in the Sage Research Methods Database )
Qualitative Approaches
The case study approach is useful to employ when there is a need to obtain an in-depth appreciation of an issue, event or phenomenon of interest, in its natural real-life context.
Ethnography
Ethnographies are an in-depth, holistic type of research used to capture cultural practices, beliefs, traditions, and so on. Here, the researcher observes and interviews members of a culture an ethnic group, a clique, members of a religion, etc. and then analyzes their findings.
Grounded Theory
Researchers will create and test a hypothesis using qualitative data. Often, researchers use grounded theory to understand decision-making, problem-solving, and other types of behavior.
Narrative Research
Researchers use this type of framework to understand different aspects of the human experience and how their subjects assign meaning to their experiences. Researchers use interviews to collect data from a small group of subjects, then discuss those results in the form of a narrative or story.
Phenomenology
This type of research attempts to understand the lived experiences of a group and/or how members of that group find meaning in their experiences. Researchers use interviews, observation, and other qualitative methods to collect data.
Watch the video "Choosing among the Five Qualitative Approaches" from Sage Research Methods database for more on these qualitative approaches:
Note: Video is best viewed using Chrome, Edge, or Safari browsers.
Poth, C. (Academic). (2023). Choosing among five qualitative approaches [Video]. Sage Research Methods. doi.org/10.4135/9781529629866
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Home » Dissertation Methodology – Structure, Example and Writing Guide
Dissertation Methodology – Structure, Example and Writing Guide
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Dissertation Methodology
In any research, the methodology chapter is one of the key components of your dissertation. It provides a detailed description of the methods you used to conduct your research and helps readers understand how you obtained your data and how you plan to analyze it. This section is crucial for replicating the study and validating its results.
Here are the basic elements that are typically included in a dissertation methodology:
- Introduction : This section should explain the importance and goals of your research .
- Research Design : Outline your research approach and why it’s appropriate for your study. You might be conducting an experimental research, a qualitative research, a quantitative research, or a mixed-methods research.
- Data Collection : This section should detail the methods you used to collect your data. Did you use surveys, interviews, observations, etc.? Why did you choose these methods? You should also include who your participants were, how you recruited them, and any ethical considerations.
- Data Analysis : Explain how you intend to analyze the data you collected. This could include statistical analysis, thematic analysis, content analysis, etc., depending on the nature of your study.
- Reliability and Validity : Discuss how you’ve ensured the reliability and validity of your study. For instance, you could discuss measures taken to reduce bias, how you ensured that your measures accurately capture what they were intended to, or how you will handle any limitations in your study.
- Ethical Considerations : This is where you state how you have considered ethical issues related to your research, how you have protected the participants’ rights, and how you have complied with the relevant ethical guidelines.
- Limitations : Acknowledge any limitations of your methodology, including any biases and constraints that might have affected your study.
- Summary : Recap the key points of your methodology chapter, highlighting the overall approach and rationalization of your research.
Types of Dissertation Methodology
The type of methodology you choose for your dissertation will depend on the nature of your research question and the field you’re working in. Here are some of the most common types of methodologies used in dissertations:
Experimental Research
This involves creating an experiment that will test your hypothesis. You’ll need to design an experiment, manipulate variables, collect data, and analyze that data to draw conclusions. This is commonly used in fields like psychology, biology, and physics.
Survey Research
This type of research involves gathering data from a large number of participants using tools like questionnaires or surveys. It can be used to collect a large amount of data and is often used in fields like sociology, marketing, and public health.
Qualitative Research
This type of research is used to explore complex phenomena that can’t be easily quantified. Methods include interviews, focus groups, and observations. This methodology is common in fields like anthropology, sociology, and education.
Quantitative Research
Quantitative research uses numerical data to answer research questions. This can include statistical, mathematical, or computational techniques. It’s common in fields like economics, psychology, and health sciences.
Case Study Research
This type of research involves in-depth investigation of a particular case, such as an individual, group, or event. This methodology is often used in psychology, social sciences, and business.
Mixed Methods Research
This combines qualitative and quantitative research methods in a single study. It’s used to answer more complex research questions and is becoming more popular in fields like social sciences, health sciences, and education.
Action Research
This type of research involves taking action and then reflecting upon the results. This cycle of action-reflection-action continues throughout the study. It’s often used in fields like education and organizational development.
Longitudinal Research
This type of research involves studying the same group of individuals over an extended period of time. This could involve surveys, observations, or experiments. It’s common in fields like psychology, sociology, and medicine.
Ethnographic Research
This type of research involves the in-depth study of people and cultures. Researchers immerse themselves in the culture they’re studying to collect data. This is often used in fields like anthropology and social sciences.
Structure of Dissertation Methodology
The structure of a dissertation methodology can vary depending on your field of study, the nature of your research, and the guidelines of your institution. However, a standard structure typically includes the following elements:
- Introduction : Briefly introduce your overall approach to the research. Explain what you plan to explore and why it’s important.
- Research Design/Approach : Describe your overall research design. This can be qualitative, quantitative, or mixed methods. Explain the rationale behind your chosen design and why it is suitable for your research questions or hypotheses.
- Data Collection Methods : Detail the methods you used to collect your data. You should include what type of data you collected, how you collected it, and why you chose this method. If relevant, you can also include information about your sample population, such as how many people participated, how they were chosen, and any relevant demographic information.
- Data Analysis Methods : Explain how you plan to analyze your collected data. This will depend on the nature of your data. For example, if you collected quantitative data, you might discuss statistical analysis techniques. If you collected qualitative data, you might discuss coding strategies, thematic analysis, or narrative analysis.
- Reliability and Validity : Discuss how you’ve ensured the reliability and validity of your research. This might include steps you took to reduce bias or increase the accuracy of your measurements.
- Ethical Considerations : If relevant, discuss any ethical issues associated with your research. This might include how you obtained informed consent from participants, how you ensured participants’ privacy and confidentiality, or any potential conflicts of interest.
- Limitations : Acknowledge any limitations in your research methodology. This could include potential sources of bias, difficulties with data collection, or limitations in your analysis methods.
- Summary/Conclusion : Briefly summarize the key points of your methodology, emphasizing how it helps answer your research questions or hypotheses.
How to Write Dissertation Methodology
Writing a dissertation methodology requires you to be clear and precise about the way you’ve carried out your research. It’s an opportunity to convince your readers of the appropriateness and reliability of your approach to your research question. Here is a basic guideline on how to write your methodology section:
1. Introduction
Start your methodology section by restating your research question(s) or objective(s). This ensures your methodology directly ties into the aim of your research.
2. Approach
Identify your overall approach: qualitative, quantitative, or mixed methods. Explain why you have chosen this approach.
- Qualitative methods are typically used for exploratory research and involve collecting non-numerical data. This might involve interviews, observations, or analysis of texts.
- Quantitative methods are used for research that relies on numerical data. This might involve surveys, experiments, or statistical analysis.
- Mixed methods use a combination of both qualitative and quantitative research methods.
3. Research Design
Describe the overall design of your research. This could involve explaining the type of study (e.g., case study, ethnography, experimental research, etc.), how you’ve defined and measured your variables, and any control measures you’ve implemented.
4. Data Collection
Explain in detail how you collected your data.
- If you’ve used qualitative methods, you might detail how you selected participants for interviews or focus groups, how you conducted observations, or how you analyzed existing texts.
- If you’ve used quantitative methods, you might detail how you designed your survey or experiment, how you collected responses, and how you ensured your data is reliable and valid.
5. Data Analysis
Describe how you analyzed your data.
- If you’re doing qualitative research, this might involve thematic analysis, discourse analysis, or grounded theory.
- If you’re doing quantitative research, you might be conducting statistical tests, regression analysis, or factor analysis.
Discuss any ethical issues related to your research. This might involve explaining how you obtained informed consent, how you’re protecting participants’ privacy, or how you’re managing any potential harms to participants.
7. Reliability and Validity
Discuss the steps you’ve taken to ensure the reliability and validity of your data.
- Reliability refers to the consistency of your measurements, and you might discuss how you’ve piloted your instruments or used standardized measures.
- Validity refers to the accuracy of your measurements, and you might discuss how you’ve ensured your measures reflect the concepts they’re supposed to measure.
8. Limitations
Every study has its limitations. Discuss the potential weaknesses of your chosen methods and explain any obstacles you faced in your research.
9. Conclusion
Summarize the key points of your methodology, emphasizing how it helps to address your research question or objective.
Example of Dissertation Methodology
An Example of Dissertation Methodology is as follows:
Chapter 3: Methodology
- Introduction
This chapter details the methodology adopted in this research. The study aimed to explore the relationship between stress and productivity in the workplace. A mixed-methods research design was used to collect and analyze data.
Research Design
This study adopted a mixed-methods approach, combining quantitative surveys with qualitative interviews to provide a comprehensive understanding of the research problem. The rationale for this approach is that while quantitative data can provide a broad overview of the relationships between variables, qualitative data can provide deeper insights into the nuances of these relationships.
Data Collection Methods
Quantitative Data Collection : An online self-report questionnaire was used to collect data from participants. The questionnaire consisted of two standardized scales: the Perceived Stress Scale (PSS) to measure stress levels and the Individual Work Productivity Questionnaire (IWPQ) to measure productivity. The sample consisted of 200 office workers randomly selected from various companies in the city.
Qualitative Data Collection : Semi-structured interviews were conducted with 20 participants chosen from the initial sample. The interview guide included questions about participants’ experiences with stress and how they perceived its impact on their productivity.
Data Analysis Methods
Quantitative Data Analysis : Descriptive and inferential statistics were used to analyze the survey data. Pearson’s correlation was used to examine the relationship between stress and productivity.
Qualitative Data Analysis : Interviews were transcribed and subjected to thematic analysis using NVivo software. This process allowed for identifying and analyzing patterns and themes regarding the impact of stress on productivity.
Reliability and Validity
To ensure reliability and validity, standardized measures with good psychometric properties were used. In qualitative data analysis, triangulation was employed by having two researchers independently analyze the data and then compare findings.
Ethical Considerations
All participants provided informed consent prior to their involvement in the study. They were informed about the purpose of the study, their rights as participants, and the confidentiality of their responses.
Limitations
The main limitation of this study is its reliance on self-report measures, which can be subject to biases such as social desirability bias. Moreover, the sample was drawn from a single city, which may limit the generalizability of the findings.
Where to Write Dissertation Methodology
In a dissertation or thesis, the Methodology section usually follows the Literature Review. This placement allows the Methodology to build upon the theoretical framework and existing research outlined in the Literature Review, and precedes the Results or Findings section. Here’s a basic outline of how most dissertations are structured:
- Acknowledgements
- Literature Review (or it may be interspersed throughout the dissertation)
- Methodology
- Results/Findings
- References/Bibliography
In the Methodology chapter, you will discuss the research design, data collection methods, data analysis methods, and any ethical considerations pertaining to your study. This allows your readers to understand how your research was conducted and how you arrived at your results.
Advantages of Dissertation Methodology
The dissertation methodology section plays an important role in a dissertation for several reasons. Here are some of the advantages of having a well-crafted methodology section in your dissertation:
- Clarifies Your Research Approach : The methodology section explains how you plan to tackle your research question, providing a clear plan for data collection and analysis.
- Enables Replication : A detailed methodology allows other researchers to replicate your study. Replication is an important aspect of scientific research because it provides validation of the study’s results.
- Demonstrates Rigor : A well-written methodology shows that you’ve thought critically about your research methods and have chosen the most appropriate ones for your research question. This adds credibility to your study.
- Enhances Transparency : Detailing your methods allows readers to understand the steps you took in your research. This increases the transparency of your study and allows readers to evaluate potential biases or limitations.
- Helps in Addressing Research Limitations : In your methodology section, you can acknowledge and explain the limitations of your research. This is important as it shows you understand that no research method is perfect and there are always potential weaknesses.
- Facilitates Peer Review : A detailed methodology helps peer reviewers assess the soundness of your research design. This is an important part of the publication process if you aim to publish your dissertation in a peer-reviewed journal.
- Establishes the Validity and Reliability : Your methodology section should also include a discussion of the steps you took to ensure the validity and reliability of your measurements, which is crucial for establishing the overall quality of your research.
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- What Is Qualitative Research? | Methods & Examples
What Is Qualitative Research? | Methods & Examples
Published on 4 April 2022 by Pritha Bhandari . Revised on 30 January 2023.
Qualitative research involves collecting and analysing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research.
Qualitative research is the opposite of quantitative research , which involves collecting and analysing numerical data for statistical analysis.
Qualitative research is commonly used in the humanities and social sciences, in subjects such as anthropology, sociology, education, health sciences, and history.
- How does social media shape body image in teenagers?
- How do children and adults interpret healthy eating in the UK?
- What factors influence employee retention in a large organisation?
- How is anxiety experienced around the world?
- How can teachers integrate social issues into science curriculums?
Table of contents
Approaches to qualitative research, qualitative research methods, qualitative data analysis, advantages of qualitative research, disadvantages of qualitative research, frequently asked questions about qualitative research.
Qualitative research is used to understand how people experience the world. While there are many approaches to qualitative research, they tend to be flexible and focus on retaining rich meaning when interpreting data.
Common approaches include grounded theory, ethnography, action research, phenomenological research, and narrative research. They share some similarities, but emphasise different aims and perspectives.
Approach | What does it involve? |
---|---|
Grounded theory | Researchers collect rich data on a topic of interest and develop theories . |
Researchers immerse themselves in groups or organisations to understand their cultures. | |
Researchers and participants collaboratively link theory to practice to drive social change. | |
Phenomenological research | Researchers investigate a phenomenon or event by describing and interpreting participants’ lived experiences. |
Narrative research | Researchers examine how stories are told to understand how participants perceive and make sense of their experiences. |
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Each of the research approaches involve using one or more data collection methods . These are some of the most common qualitative methods:
- Observations: recording what you have seen, heard, or encountered in detailed field notes.
- Interviews: personally asking people questions in one-on-one conversations.
- Focus groups: asking questions and generating discussion among a group of people.
- Surveys : distributing questionnaires with open-ended questions.
- Secondary research: collecting existing data in the form of texts, images, audio or video recordings, etc.
- You take field notes with observations and reflect on your own experiences of the company culture.
- You distribute open-ended surveys to employees across all the company’s offices by email to find out if the culture varies across locations.
- You conduct in-depth interviews with employees in your office to learn about their experiences and perspectives in greater detail.
Qualitative researchers often consider themselves ‘instruments’ in research because all observations, interpretations and analyses are filtered through their own personal lens.
For this reason, when writing up your methodology for qualitative research, it’s important to reflect on your approach and to thoroughly explain the choices you made in collecting and analysing the data.
Qualitative data can take the form of texts, photos, videos and audio. For example, you might be working with interview transcripts, survey responses, fieldnotes, or recordings from natural settings.
Most types of qualitative data analysis share the same five steps:
- Prepare and organise your data. This may mean transcribing interviews or typing up fieldnotes.
- Review and explore your data. Examine the data for patterns or repeated ideas that emerge.
- Develop a data coding system. Based on your initial ideas, establish a set of codes that you can apply to categorise your data.
- Assign codes to the data. For example, in qualitative survey analysis, this may mean going through each participant’s responses and tagging them with codes in a spreadsheet. As you go through your data, you can create new codes to add to your system if necessary.
- Identify recurring themes. Link codes together into cohesive, overarching themes.
There are several specific approaches to analysing qualitative data. Although these methods share similar processes, they emphasise different concepts.
Approach | When to use | Example |
---|---|---|
To describe and categorise common words, phrases, and ideas in qualitative data. | A market researcher could perform content analysis to find out what kind of language is used in descriptions of therapeutic apps. | |
To identify and interpret patterns and themes in qualitative data. | A psychologist could apply thematic analysis to travel blogs to explore how tourism shapes self-identity. | |
To examine the content, structure, and design of texts. | A media researcher could use textual analysis to understand how news coverage of celebrities has changed in the past decade. | |
To study communication and how language is used to achieve effects in specific contexts. | A political scientist could use discourse analysis to study how politicians generate trust in election campaigns. |
Qualitative research often tries to preserve the voice and perspective of participants and can be adjusted as new research questions arise. Qualitative research is good for:
- Flexibility
The data collection and analysis process can be adapted as new ideas or patterns emerge. They are not rigidly decided beforehand.
- Natural settings
Data collection occurs in real-world contexts or in naturalistic ways.
- Meaningful insights
Detailed descriptions of people’s experiences, feelings and perceptions can be used in designing, testing or improving systems or products.
- Generation of new ideas
Open-ended responses mean that researchers can uncover novel problems or opportunities that they wouldn’t have thought of otherwise.
Researchers must consider practical and theoretical limitations in analysing and interpreting their data. Qualitative research suffers from:
- Unreliability
The real-world setting often makes qualitative research unreliable because of uncontrolled factors that affect the data.
- Subjectivity
Due to the researcher’s primary role in analysing and interpreting data, qualitative research cannot be replicated . The researcher decides what is important and what is irrelevant in data analysis, so interpretations of the same data can vary greatly.
- Limited generalisability
Small samples are often used to gather detailed data about specific contexts. Despite rigorous analysis procedures, it is difficult to draw generalisable conclusions because the data may be biased and unrepresentative of the wider population .
- Labour-intensive
Although software can be used to manage and record large amounts of text, data analysis often has to be checked or performed manually.
Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.
Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.
There are five common approaches to qualitative research :
- Grounded theory involves collecting data in order to develop new theories.
- Ethnography involves immersing yourself in a group or organisation to understand its culture.
- Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
- Phenomenological research involves investigating phenomena through people’s lived experiences.
- Action research links theory and practice in several cycles to drive innovative changes.
Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.
There are various approaches to qualitative data analysis , but they all share five steps in common:
- Prepare and organise your data.
- Review and explore your data.
- Develop a data coding system.
- Assign codes to the data.
- Identify recurring themes.
The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .
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Qualitative dissertation methodology : a guide for research design and methods
Available online.
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Creators/contributors, contents/summary.
- Preface Acknowledgments
- PART 1 PREPARING FOR METHODOLOGICAL WORK
- Chapter 1 Working as a Qualitative Methodologist in Dissertation Contexts Ensuring That Qualitative Methodology Is the Right Fit for Your Dissertation Research Interests Developing a Qualitative Methodology for Your Dissertation Becoming a Qualitative Dissertation Methodologist Designing an Executable Qualitative Dissertation Methodology Putting Together Your Qualitative Dissertation Advising Chair and Committee Chapter Summary Questions for Application
- Chapter 2 Understanding a Dissertation as Qualitative Methodology: A Section-by-Section Approach Dissertations as Socially Constructed Processes and Products of Cultural Values and Rituals Current Thinking on the Dissertation: Critiques and Emerging Approaches Understanding Methodology in Qualitative Research Qualitative Dissertation Methodology in Doctoral Program Contexts Contextualizing Qualitative Methodology in Dissertation Research Meaningfully Designing a Qualitative Methodological Framework: A Section-by-Section Approach Chapter Summary Questions for Application
- PART 2 DEVELOPING A METHODOLOGY CHAPTER
- Chapter 3 Framing a Dissertation Study Through a Research Tradition A Story About Research Traditions in Qualitative Dissertation Methodology Leading to Qualitative Research Traditions: Research Paradigms in Qualitative Inquiry Qualitative Research Traditions in Dissertations Integrating Methodology in Qualitative Dissertations Through Research Traditions Conceptualizing a Qualitative Research Tradition Chapter Section Writing a Qualitative Research Tradition Section: Methodology Chapter Template Chapter Summary Checklist for Methodology Chapter Development Questions for Application
- Chapter 4 Identifying a Research Setting and Exploring Research Contexts Connecting Research and Practice: Initial Considerations in Research Settings Site Selection as a Process: Using a Systematic Approach With Physical or Virtual Locations When Research Settings Do Not Lead to a Specific Site or Sites Gaining Access and Seeking Approval to Work at a Site Describing Research Settings: Historical, Contextual, and Locational Cues Integrating Methodology in Qualitative Dissertations: Research Settings Conceptualizing a Qualitative Research Setting Chapter Section Writing a Qualitative Research Setting Section: Methodology Chapter Template Chapter Summary Checklist for Methodology Chapter Development Questions for Application
- Chapter 5 Working With Data Sources: Selecting Research Participants and Forming Research Samples A Transition From Sampling at the Site Level to the Participant Level Decisions About Research Participants: Data Sources, Data Types, and Data Collection Methods Sampling and Selection Strategies With Research Participants Successful Outcomes: Inviting and Negotiating Research Participation Describing Research Samples: Sharing Their Stories, Protecting Their Identities Integrating Methodology in Qualitative Dissertations: Data Sources and Sample Conceptualizing a Data Sources and Sample Chapter Section Writing a Data Sources and Sample Section: Qualitative Methodology Chapter Template Chapter Summary Checklist for Methodology Chapter Development Questions for Application
- Chapter 6 Developing Data Collection Instruments and Describing Data Collection Procedures Gathering Information: Detailing Data Collection Methods, Procedures, and Instruments Instrumentation in Qualitative Inquiry: Constructing and Integrating Your Guides Procedural Steps With Collecting Data: From Standard Practice to Pragmatic Considerations Building a Social Network in the Field: Practical Considerations to Facilitate Data Collection Power Dynamics in the Field: Accounting for Positions and Positionality in Research Contexts Integrating Methodology in Qualitative Dissertations: Data Collection Instruments and Procedures Conceptualizing a Data Collection Instruments and Procedures Chapter Section Writing a Data Collection Instruments and Procedures Section: Qualitative Methodology Chapter Template Chapter Summary Checklist for Methodology Chapter Development Questions for Application
- Chapter 7 Articulating Data Analysis Procedures Understanding the Analytical Process in Qualitative Research Analysis as a Three-Phase Process in Qualitative Dissertation Methodology Computer-Aided Qualitative Data Analysis Software (CAQDAS) in Dissertations Integrating Methodology in Qualitative Dissertations: Data Analysis Procedures Conceptualizing a Data Analysis Procedures Chapter Section Writing a Data Analysis Section: Qualitative Methodology Chapter Template Chapter Summary Checklist for Methodology Chapter Development Questions for Application
- Chapter 8 Adopting a Reflexive Practice With a Discussion of Researcher Roles Why Consider Researcher Roles in Your Dissertation Research? Roles and Subjectivities, or What You and Participants (and Readers) Bring to Your Study Research Effects on Methodology: Implications for Results and Findings Mitigating Research Effects: Strategies to Account for Who You Are in Your Study Integrating Methodology in Qualitative Dissertations: Researcher Roles Conceptualizing a Researcher Roles Chapter Section Writing a Researcher Roles Section: Qualitative Methodology Chapter Template Chapter Summary Checklist for Methodology Chapter Development Questions for Application
- PART 3 TRANSITIONING TO WORK AFTER A METHODOLOGY CHAPTER
- Chapter 9 Protecting Human Research Participants in Qualitative Dissertation Methodology The Methodology Chapter as an Ethical Contract Background to Human Subjects Protections and Research Governance Recent Changes in Human Subjects Research: Updates to the Common Rule Research Governance as a Process: Navigating Institutional Review Board (IRB) Procedural Requirements Discussing Protections of Human Research Subjects in Qualitative Dissertation Methodology Writing and Revising an IRB Protocol: Strategies for Practice Chapter Summary Checklist for Methodology Chapter Development Questions for Application
- Chapter 10 Writing Up and Presenting Results of Qualitative Data Analysis Why Think About Your Results and Conclusions Chapter(s) Now? The Overall Functions of Qualitative Dissertation Results and Findings Chapters Strategies to Display Data and Communicate Results and Findings Organizing a Dissertation Chapter or Chapters on Results and Interpretation of Data Analysis Disseminating and Presenting Results of Your Qualitative Dissertation Work Chapter Summary Questions for Application References Index About the Author.
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How To Choose Your Research Methodology
Qualitative vs quantitative vs mixed methods.
By: Derek Jansen (MBA). Expert Reviewed By: Dr Eunice Rautenbach | June 2021
Without a doubt, one of the most common questions we receive at Grad Coach is “ How do I choose the right methodology for my research? ”. It’s easy to see why – with so many options on the research design table, it’s easy to get intimidated, especially with all the complex lingo!
In this post, we’ll explain the three overarching types of research – qualitative, quantitative and mixed methods – and how you can go about choosing the best methodological approach for your research.
Overview: Choosing Your Methodology
Understanding the options – Qualitative research – Quantitative research – Mixed methods-based research
Choosing a research methodology – Nature of the research – Research area norms – Practicalities
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1. Understanding the options
Before we jump into the question of how to choose a research methodology, it’s useful to take a step back to understand the three overarching types of research – qualitative , quantitative and mixed methods -based research. Each of these options takes a different methodological approach.
Qualitative research utilises data that is not numbers-based. In other words, qualitative research focuses on words , descriptions , concepts or ideas – while quantitative research makes use of numbers and statistics. Qualitative research investigates the “softer side” of things to explore and describe, while quantitative research focuses on the “hard numbers”, to measure differences between variables and the relationships between them.
Importantly, qualitative research methods are typically used to explore and gain a deeper understanding of the complexity of a situation – to draw a rich picture . In contrast to this, quantitative methods are usually used to confirm or test hypotheses . In other words, they have distinctly different purposes. The table below highlights a few of the key differences between qualitative and quantitative research – you can learn more about the differences here.
- Uses an inductive approach
- Is used to build theories
- Takes a subjective approach
- Adopts an open and flexible approach
- The researcher is close to the respondents
- Interviews and focus groups are oftentimes used to collect word-based data.
- Generally, draws on small sample sizes
- Uses qualitative data analysis techniques (e.g. content analysis , thematic analysis , etc)
- Uses a deductive approach
- Is used to test theories
- Takes an objective approach
- Adopts a closed, highly planned approach
- The research is disconnected from respondents
- Surveys or laboratory equipment are often used to collect number-based data.
- Generally, requires large sample sizes
- Uses statistical analysis techniques to make sense of the data
Mixed methods -based research, as you’d expect, attempts to bring these two types of research together, drawing on both qualitative and quantitative data. Quite often, mixed methods-based studies will use qualitative research to explore a situation and develop a potential model of understanding (this is called a conceptual framework), and then go on to use quantitative methods to test that model empirically.
In other words, while qualitative and quantitative methods (and the philosophies that underpin them) are completely different, they are not at odds with each other. It’s not a competition of qualitative vs quantitative. On the contrary, they can be used together to develop a high-quality piece of research. Of course, this is easier said than done, so we usually recommend that first-time researchers stick to a single approach , unless the nature of their study truly warrants a mixed-methods approach.
The key takeaway here, and the reason we started by looking at the three options, is that it’s important to understand that each methodological approach has a different purpose – for example, to explore and understand situations (qualitative), to test and measure (quantitative) or to do both. They’re not simply alternative tools for the same job.
Right – now that we’ve got that out of the way, let’s look at how you can go about choosing the right methodology for your research.
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2. How to choose a research methodology
To choose the right research methodology for your dissertation or thesis, you need to consider three important factors . Based on these three factors, you can decide on your overarching approach – qualitative, quantitative or mixed methods. Once you’ve made that decision, you can flesh out the finer details of your methodology, such as the sampling , data collection methods and analysis techniques (we discuss these separately in other posts ).
The three factors you need to consider are:
- The nature of your research aims, objectives and research questions
- The methodological approaches taken in the existing literature
- Practicalities and constraints
Let’s take a look at each of these.
Factor #1: The nature of your research
As I mentioned earlier, each type of research (and therefore, research methodology), whether qualitative, quantitative or mixed, has a different purpose and helps solve a different type of question. So, it’s logical that the key deciding factor in terms of which research methodology you adopt is the nature of your research aims, objectives and research questions .
But, what types of research exist?
Broadly speaking, research can fall into one of three categories:
- Exploratory – getting a better understanding of an issue and potentially developing a theory regarding it
- Confirmatory – confirming a potential theory or hypothesis by testing it empirically
- A mix of both – building a potential theory or hypothesis and then testing it
As a rule of thumb, exploratory research tends to adopt a qualitative approach , whereas confirmatory research tends to use quantitative methods . This isn’t set in stone, but it’s a very useful heuristic. Naturally then, research that combines a mix of both, or is seeking to develop a theory from the ground up and then test that theory, would utilize a mixed-methods approach.
![confirmatory-exploratory-research Exploratory vs confirmatory research](https://gradcoach.com/wp-content/uploads/confirmatory-exploratory-research.png)
Let’s look at an example in action.
If your research aims were to understand the perspectives of war veterans regarding certain political matters, you’d likely adopt a qualitative methodology, making use of interviews to collect data and one or more qualitative data analysis methods to make sense of the data.
If, on the other hand, your research aims involved testing a set of hypotheses regarding the link between political leaning and income levels, you’d likely adopt a quantitative methodology, using numbers-based data from a survey to measure the links between variables and/or constructs .
So, the first (and most important thing) thing you need to consider when deciding which methodological approach to use for your research project is the nature of your research aims , objectives and research questions. Specifically, you need to assess whether your research leans in an exploratory or confirmatory direction or involves a mix of both.
The importance of achieving solid alignment between these three factors and your methodology can’t be overstated. If they’re misaligned, you’re going to be forcing a square peg into a round hole. In other words, you’ll be using the wrong tool for the job, and your research will become a disjointed mess.
If your research is a mix of both exploratory and confirmatory, but you have a tight word count limit, you may need to consider trimming down the scope a little and focusing on one or the other. One methodology executed well has a far better chance of earning marks than a poorly executed mixed methods approach. So, don’t try to be a hero, unless there is a very strong underpinning logic.
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Factor #2: The disciplinary norms
Choosing the right methodology for your research also involves looking at the approaches used by other researchers in the field, and studies with similar research aims and objectives to yours. Oftentimes, within a discipline, there is a common methodological approach (or set of approaches) used in studies. While this doesn’t mean you should follow the herd “just because”, you should at least consider these approaches and evaluate their merit within your context.
A major benefit of reviewing the research methodologies used by similar studies in your field is that you can often piggyback on the data collection techniques that other (more experienced) researchers have developed. For example, if you’re undertaking a quantitative study, you can often find tried and tested survey scales with high Cronbach’s alphas. These are usually included in the appendices of journal articles, so you don’t even have to contact the original authors. By using these, you’ll save a lot of time and ensure that your study stands on the proverbial “shoulders of giants” by using high-quality measurement instruments .
Of course, when reviewing existing literature, keep point #1 front of mind. In other words, your methodology needs to align with your research aims, objectives and questions. Don’t fall into the trap of adopting the methodological “norm” of other studies just because it’s popular. Only adopt that which is relevant to your research.
Factor #3: Practicalities
When choosing a research methodology, there will always be a tension between doing what’s theoretically best (i.e., the most scientifically rigorous research design ) and doing what’s practical , given your constraints . This is the nature of doing research and there are always trade-offs, as with anything else.
But what constraints, you ask?
When you’re evaluating your methodological options, you need to consider the following constraints:
- Data access
- Equipment and software
- Your knowledge and skills
Let’s look at each of these.
Constraint #1: Data access
The first practical constraint you need to consider is your access to data . If you’re going to be undertaking primary research , you need to think critically about the sample of respondents you realistically have access to. For example, if you plan to use in-person interviews , you need to ask yourself how many people you’ll need to interview, whether they’ll be agreeable to being interviewed, where they’re located, and so on.
If you’re wanting to undertake a quantitative approach using surveys to collect data, you’ll need to consider how many responses you’ll require to achieve statistically significant results. For many statistical tests, a sample of a few hundred respondents is typically needed to develop convincing conclusions.
So, think carefully about what data you’ll need access to, how much data you’ll need and how you’ll collect it. The last thing you want is to spend a huge amount of time on your research only to find that you can’t get access to the required data.
Constraint #2: Time
The next constraint is time. If you’re undertaking research as part of a PhD, you may have a fairly open-ended time limit, but this is unlikely to be the case for undergrad and Masters-level projects. So, pay attention to your timeline, as the data collection and analysis components of different methodologies have a major impact on time requirements . Also, keep in mind that these stages of the research often take a lot longer than originally anticipated.
Another practical implication of time limits is that it will directly impact which time horizon you can use – i.e. longitudinal vs cross-sectional . For example, if you’ve got a 6-month limit for your entire research project, it’s quite unlikely that you’ll be able to adopt a longitudinal time horizon.
Constraint #3: Money
As with so many things, money is another important constraint you’ll need to consider when deciding on your research methodology. While some research designs will cost near zero to execute, others may require a substantial budget .
Some of the costs that may arise include:
- Software costs – e.g. survey hosting services, analysis software, etc.
- Promotion costs – e.g. advertising a survey to attract respondents
- Incentive costs – e.g. providing a prize or cash payment incentive to attract respondents
- Equipment rental costs – e.g. recording equipment, lab equipment, etc.
- Travel costs
- Food & beverages
These are just a handful of costs that can creep into your research budget. Like most projects, the actual costs tend to be higher than the estimates, so be sure to err on the conservative side and expect the unexpected. It’s critically important that you’re honest with yourself about these costs, or you could end up getting stuck midway through your project because you’ve run out of money.
![research budget Budgeting for your research](https://gradcoach.com/wp-content/uploads/research-budget.png)
Constraint #4: Equipment & software
Another practical consideration is the hardware and/or software you’ll need in order to undertake your research. Of course, this variable will depend on the type of data you’re collecting and analysing. For example, you may need lab equipment to analyse substances, or you may need specific analysis software to analyse statistical data. So, be sure to think about what hardware and/or software you’ll need for each potential methodological approach, and whether you have access to these.
Constraint #5: Your knowledge and skillset
The final practical constraint is a big one. Naturally, the research process involves a lot of learning and development along the way, so you will accrue knowledge and skills as you progress. However, when considering your methodological options, you should still consider your current position on the ladder.
Some of the questions you should ask yourself are:
- Am I more of a “numbers person” or a “words person”?
- How much do I know about the analysis methods I’ll potentially use (e.g. statistical analysis)?
- How much do I know about the software and/or hardware that I’ll potentially use?
- How excited am I to learn new research skills and gain new knowledge?
- How much time do I have to learn the things I need to learn?
Answering these questions honestly will provide you with another set of criteria against which you can evaluate the research methodology options you’ve shortlisted.
So, as you can see, there is a wide range of practicalities and constraints that you need to take into account when you’re deciding on a research methodology. These practicalities create a tension between the “ideal” methodology and the methodology that you can realistically pull off. This is perfectly normal, and it’s your job to find the option that presents the best set of trade-offs.
Recap: Choosing a methodology
In this post, we’ve discussed how to go about choosing a research methodology. The three major deciding factors we looked at were:
- Exploratory
- Confirmatory
- Combination
- Research area norms
- Hardware and software
- Your knowledge and skillset
If you have any questions, feel free to leave a comment below. If you’d like a helping hand with your research methodology, check out our 1-on-1 research coaching service , or book a free consultation with a friendly Grad Coach.
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This post was based on one of our popular Research Bootcamps . If you're working on a research project, you'll definitely want to check this out ...
Very useful and informative especially for beginners
Nice article! I’m a beginner in the field of cybersecurity research. I am a Telecom and Network Engineer and Also aiming for PhD scholarship.
I find the article very informative especially for my decitation it has been helpful and an eye opener.
Hi I am Anna ,
I am a PHD candidate in the area of cyber security, maybe we can link up
The Examples shows by you, for sure they are really direct me and others to knows and practices the Research Design and prepration.
I found the post very informative and practical.
I struggle so much with designs of the research for sure!
I’m the process of constructing my research design and I want to know if the data analysis I plan to present in my thesis defense proposal possibly change especially after I gathered the data already.
Thank you so much this site is such a life saver. How I wish 1-1 coaching is available in our country but sadly it’s not.
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Basics of Methodology
Research is a process of inquiry that is carried out in a pondered, organized, and strategic manner. In order to obtain high quality results, it is important to understand methodology.
Research methodology refers to how your project will be designed, what you will observe or measure, and how you will collect and analyze data. The methods you choose must be appropriate for your field and for the specific research questions you are setting out to answer.
A strong understanding of methodology will help you:
- apply appropriate research techniques
- design effective data collection instruments
- analyze and interpret your data
- develop well-founded conclusions
Below, you will find resources that mostly cover general aspects of research methodology. In the left column, you will find resources that specifically cover qualitative, quantitative, and mixed methods research.
General Works on Methodology
Qualitative Research
Quantitative Research
Mixed Methods Research
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- Last Updated: Jul 22, 2024 10:48 AM
- URL: https://library.guilford.edu/thesis-guide
Dissertations and research projects
- Sessions and recordings
- Skill guide
- Finding the gap
- Developing research questions
- Epistemology
- Ethical approval
- Methodology and Methods
- Recruiting participants
- Planning your analysis
- Writing your research proposal
- Hypothesis testing
- Reliability and validity
- Approaches to quantitative research
- Developing a theoretical framework
- Reflecting on your position
- Extended literature reviews
- Presenting qualitative data
- Introduction
- Literature review
- Methodology
- Conclusions
- 5) Working with a supervisor
- e-learning and books
- Quick resources
- SkillsCheck This link opens in a new window
- Review this resource
Qualitative research
In this section on Qualitative Research you can find out about:
You might also want to consult our other sections on Planning your research , Quantitative research and Writing up research , and check out the Additional resources .
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Library Guides
Dissertations 4: methodology: methods.
- Introduction & Philosophy
- Methodology
Primary & Secondary Sources, Primary & Secondary Data
When describing your research methods, you can start by stating what kind of secondary and, if applicable, primary sources you used in your research. Explain why you chose such sources, how well they served your research, and identify possible issues encountered using these sources.
Definitions
There is some confusion on the use of the terms primary and secondary sources, and primary and secondary data. The confusion is also due to disciplinary differences (Lombard 2010). Whilst you are advised to consult the research methods literature in your field, we can generalise as follows:
Secondary sources
Secondary sources normally include the literature (books and articles) with the experts' findings, analysis and discussions on a certain topic (Cottrell, 2014, p123). Secondary sources often interpret primary sources.
Primary sources
Primary sources are "first-hand" information such as raw data, statistics, interviews, surveys, law statutes and law cases. Even literary texts, pictures and films can be primary sources if they are the object of research (rather than, for example, documentaries reporting on something else, in which case they would be secondary sources). The distinction between primary and secondary sources sometimes lies on the use you make of them (Cottrell, 2014, p123).
Primary data
Primary data are data (primary sources) you directly obtained through your empirical work (Saunders, Lewis and Thornhill 2015, p316).
Secondary data
Secondary data are data (primary sources) that were originally collected by someone else (Saunders, Lewis and Thornhill 2015, p316).
Comparison between primary and secondary data
Primary data | Secondary data |
Data collected directly | Data collected from previously done research, existing research is summarised and collated to enhance the overall effectiveness of the research. |
Examples: Interviews (face-to-face or telephonic), Online surveys, Focus groups and Observations | Examples: data available via the internet, non-government and government agencies, public libraries, educational institutions, commercial/business information |
Advantages: •Data collected is first hand and accurate. •Data collected can be controlled. No dilution of data. •Research method can be customized to suit personal requirements and needs of the research. | Advantages: •Information is readily available •Less expensive and less time-consuming •Quicker to conduct |
Disadvantages: •Can be quite extensive to conduct, requiring a lot of time and resources •Sometimes one primary research method is not enough; therefore a mixed method is require, which can be even more time consuming. | Disadvantages: •It is necessary to check the credibility of the data •May not be as up to date •Success of your research depends on the quality of research previously conducted by others. |
Use
Virtually all research will use secondary sources, at least as background information.
Often, especially at the postgraduate level, it will also use primary sources - secondary and/or primary data. The engagement with primary sources is generally appreciated, as less reliant on others' interpretations, and closer to 'facts'.
The use of primary data, as opposed to secondary data, demonstrates the researcher's effort to do empirical work and find evidence to answer her specific research question and fulfill her specific research objectives. Thus, primary data contribute to the originality of the research.
Ultimately, you should state in this section of the methodology:
What sources and data you are using and why (how are they going to help you answer the research question and/or test the hypothesis.
If using primary data, why you employed certain strategies to collect them.
What the advantages and disadvantages of your strategies to collect the data (also refer to the research in you field and research methods literature).
Quantitative, Qualitative & Mixed Methods
The methodology chapter should reference your use of quantitative research, qualitative research and/or mixed methods. The following is a description of each along with their advantages and disadvantages.
Quantitative research
Quantitative research uses numerical data (quantities) deriving, for example, from experiments, closed questions in surveys, questionnaires, structured interviews or published data sets (Cottrell, 2014, p93). It normally processes and analyses this data using quantitative analysis techniques like tables, graphs and statistics to explore, present and examine relationships and trends within the data (Saunders, Lewis and Thornhill, 2015, p496).
Advantages | Disadvantages |
The study can be undertaken on a broader scale, generating large amounts of data that contribute to generalisation of results | Quantitative methods can be difficult, expensive and time consuming (especially if using primary data, rather than secondary data). |
Suitable when the phenomenon is relatively simple, and can be analysed according to identified variables. | Not everything can be easily measured. |
| Less suitable for complex social phenomena. |
| Less suitable for why type questions. |
Qualitative research
Qualitative research is generally undertaken to study human behaviour and psyche. It uses methods like in-depth case studies, open-ended survey questions, unstructured interviews, focus groups, or unstructured observations (Cottrell, 2014, p93). The nature of the data is subjective, and also the analysis of the researcher involves a degree of subjective interpretation. Subjectivity can be controlled for in the research design, or has to be acknowledged as a feature of the research. Subject-specific books on (qualitative) research methods offer guidance on such research designs.
Advantages | Disadvantages |
Qualitative methods are good for in-depth analysis of individual people, businesses, organisations, events. | The findings can be accurate about the particular case, but not generally applicable. |
Sample sizes don’t need to be large, so the studies can be cheaper and simpler. | More prone to subjectivity. |
Mixed methods
Mixed-method approaches combine both qualitative and quantitative methods, and therefore combine the strengths of both types of research. Mixed methods have gained popularity in recent years.
When undertaking mixed-methods research you can collect the qualitative and quantitative data either concurrently or sequentially. If sequentially, you can for example, start with a few semi-structured interviews, providing qualitative insights, and then design a questionnaire to obtain quantitative evidence that your qualitative findings can also apply to a wider population (Specht, 2019, p138).
Ultimately, your methodology chapter should state:
Whether you used quantitative research, qualitative research or mixed methods.
Why you chose such methods (and refer to research method sources).
Why you rejected other methods.
How well the method served your research.
The problems or limitations you encountered.
Doug Specht, Senior Lecturer at the Westminster School of Media and Communication, explains mixed methods research in the following video:
LinkedIn Learning Video on Academic Research Foundations: Quantitative
The video covers the characteristics of quantitative research, and explains how to approach different parts of the research process, such as creating a solid research question and developing a literature review. He goes over the elements of a study, explains how to collect and analyze data, and shows how to present your data in written and numeric form.
Link to quantitative research video
Some Types of Methods
There are several methods you can use to get primary data. To reiterate, the choice of the methods should depend on your research question/hypothesis.
Whatever methods you will use, you will need to consider:
why did you choose one technique over another? What were the advantages and disadvantages of the technique you chose?
what was the size of your sample? Who made up your sample? How did you select your sample population? Why did you choose that particular sampling strategy?)
ethical considerations (see also tab...)
safety considerations
validity
feasibility
recording
procedure of the research (see box procedural method...).
Check Stella Cottrell's book Dissertations and Project Reports: A Step by Step Guide for some succinct yet comprehensive information on most methods (the following account draws mostly on her work). Check a research methods book in your discipline for more specific guidance.
Experiments
Experiments are useful to investigate cause and effect, when the variables can be tightly controlled. They can test a theory or hypothesis in controlled conditions. Experiments do not prove or disprove an hypothesis, instead they support or not support an hypothesis. When using the empirical and inductive method it is not possible to achieve conclusive results. The results may only be valid until falsified by other experiments and observations.
For more information on Scientific Method, click here .
Observations
Observational methods are useful for in-depth analyses of behaviours in people, animals, organisations, events or phenomena. They can test a theory or products in real life or simulated settings. They generally a qualitative research method.
Questionnaires and surveys
Questionnaires and surveys are useful to gain opinions, attitudes, preferences, understandings on certain matters. They can provide quantitative data that can be collated systematically; qualitative data, if they include opportunities for open-ended responses; or both qualitative and quantitative elements.
Interviews
Interviews are useful to gain rich, qualitative information about individuals' experiences, attitudes or perspectives. With interviews you can follow up immediately on responses for clarification or further details. There are three main types of interviews: structured (following a strict pattern of questions, which expect short answers), semi-structured (following a list of questions, with the opportunity to follow up the answers with improvised questions), and unstructured (following a short list of broad questions, where the respondent can lead more the conversation) (Specht, 2019, p142).
This short video on qualitative interviews discusses best practices and covers qualitative interview design, preparation and data collection methods.
Focus groups
In this case, a group of people (normally, 4-12) is gathered for an interview where the interviewer asks questions to such group of participants. Group interactions and discussions can be highly productive, but the researcher has to beware of the group effect, whereby certain participants and views dominate the interview (Saunders, Lewis and Thornhill 2015, p419). The researcher can try to minimise this by encouraging involvement of all participants and promoting a multiplicity of views.
This video focuses on strategies for conducting research using focus groups.
Check out the guidance on online focus groups by Aliaksandr Herasimenka, which is attached at the bottom of this text box.
Case study
Case studies are often a convenient way to narrow the focus of your research by studying how a theory or literature fares with regard to a specific person, group, organisation, event or other type of entity or phenomenon you identify. Case studies can be researched using other methods, including those described in this section. Case studies give in-depth insights on the particular reality that has been examined, but may not be representative of what happens in general, they may not be generalisable, and may not be relevant to other contexts. These limitations have to be acknowledged by the researcher.
Content analysis
Content analysis consists in the study of words or images within a text. In its broad definition, texts include books, articles, essays, historical documents, speeches, conversations, advertising, interviews, social media posts, films, theatre, paintings or other visuals. Content analysis can be quantitative (e.g. word frequency) or qualitative (e.g. analysing intention and implications of the communication). It can detect propaganda, identify intentions of writers, and can see differences in types of communication (Specht, 2019, p146). Check this page on collecting, cleaning and visualising Twitter data.
Extra links and resources:
Research Methods
A clear and comprehensive overview of research methods by Emerald Publishing. It includes: crowdsourcing as a research tool; mixed methods research; case study; discourse analysis; ground theory; repertory grid; ethnographic method and participant observation; interviews; focus group; action research; analysis of qualitative data; survey design; questionnaires; statistics; experiments; empirical research; literature review; secondary data and archival materials; data collection.
Doing your dissertation during the COVID-19 pandemic
Resources providing guidance on doing dissertation research during the pandemic: Online research methods; Secondary data sources; Webinars, conferences and podcasts;
- Virtual Focus Groups Guidance on managing virtual focus groups
5 Minute Methods Videos
The following are a series of useful videos that introduce research methods in five minutes. These resources have been produced by lecturers and students with the University of Westminster's School of Media and Communication.
Case Study Research
Research Ethics
Quantitative Content Analysis
Sequential Analysis
Qualitative Content Analysis
Thematic Analysis
Social Media Research
Mixed Method Research
Procedural Method
In this part, provide an accurate, detailed account of the methods and procedures that were used in the study or the experiment (if applicable!).
Include specifics about participants, sample, materials, design and methods.
If the research involves human subjects, then include a detailed description of who and how many participated along with how the participants were selected.
Describe all materials used for the study, including equipment, written materials and testing instruments.
Identify the study's design and any variables or controls employed.
Write out the steps in the order that they were completed.
Indicate what participants were asked to do, how measurements were taken and any calculations made to raw data collected.
Specify statistical techniques applied to the data to reach your conclusions.
Provide evidence that you incorporated rigor into your research. This is the quality of being thorough and accurate and considers the logic behind your research design.
Highlight any drawbacks that may have limited your ability to conduct your research thoroughly.
You have to provide details to allow others to replicate the experiment and/or verify the data, to test the validity of the research.
Bibliography
Cottrell, S. (2014). Dissertations and project reports: a step by step guide. Hampshire, England: Palgrave Macmillan.
Lombard, E. (2010). Primary and secondary sources. The Journal of Academic Librarianship , 36(3), 250-253
Saunders, M.N.K., Lewis, P. and Thornhill, A. (2015). Research Methods for Business Students. New York: Pearson Education.
Specht, D. (2019). The Media And Communications Study Skills Student Guide . London: University of Westminster Press.
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- Last Updated: Sep 14, 2022 12:58 PM
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What is qualitative research? Approaches, methods, and examples
Published 19 Jul 2024
Students in social sciences frequently seek to understand how people feel, think, and behave in specific situations or relationships that evolve over time. To achieve this, they employ various techniques and data collection methods in qualitative research allowing for a deeper exploration of human experiences. Participant observation, in-depth interviews, and other qualitative methods are commonly used to gather rich, detailed data to uncover key aspects of social behavior and relationships. What is qualitative research? This article will answer this question and guide you through the essentials of this methodology, including data collection techniques and analytical approaches.
Qualitative research definition and significance
This inquiry method is helpful for learners interested in how to conduct research . It focuses on understanding human behavior, experiences, and social phenomena from the perspective of those involved. What does qualitative mean? It uses non-numerical data, such as interviews, observations, and textual analysis, to understand people’s feelings, thoughts, and actions.
Where and when is it used?
Qualitative analysis is crucial in education, healthcare, social sciences, marketing, and business. It helps gain detailed insights into behaviors, experiences, and cultural phenomena. This approach is fundamental during exploratory phases, for understanding complex issues, and when context-specific insights are required. By focusing on depth over breadth, this approach is often employed when researchers seek to explore complex issues, understand the context of a phenomenon, or investigate things that are not easily quantifiable. It uncovers rich, nuanced data essential for developing theories and evaluating programs.
Why is qualitative research important in academia?
- It sheds light on complex phenomena and human experiences that quantitative methods may overlook.
- This method offers contextual understanding by studying subjects in their natural environments, which is crucial for grasping real-world complexities.
- It adapts flexibly to evolving study findings and allows for adjusting approaches as new ideas emerge.
- It collects rich, detailed data through interviews, observations, and analysis, offering a comprehensive view of the exploration topic.
- Qualitative research studies focus on new or less explored areas, helping to identify key variables and generate hypotheses for further study.
- This approach focuses on understanding individuals' perspectives, motivations, and emotions, essential in fields like sociology, psychology, and education.
- It supports theory development by providing empirical data that can create new theories and frameworks (you may read about “ What is a conceptual framework ?” and learn about other frameworks on the EduBirdie website).
- It improves practices in fields such as education and healthcare by offering insights into practitioners' and clients' needs and experiences.
The difference between qualitative and quantitative studies
Now that you know the answer to “Why is qualitative data important?”, let’s consider how this method differs from quantitative. Both studies represent two main types of research methods. The qualitative approach focuses on understanding behaviors, experiences, and perspectives using interviews, observations, and analyzing texts. These studies are based on reflexivity and aim to explore complexities and contexts, often generating new ideas or theories. Researchers analyze data to find patterns and themes, clarifying the details. However, findings demonstrated in the results section of a research paper may not apply broadly because they often use small, specific groups rather than large, random samples.
Quantitative studies, on the other hand, emphasize numerical data and statistical analysis to measure variables and relationships. They use methods such as surveys, experiments, or analyzing existing data to collect structured information. The goal is quantifying phenomena, testing hypotheses, and determining correlations or causes. Statistical methods are used to analyze data, identifying patterns and significance. Quantitative studies produce results that can be applied to larger populations, providing generalizable findings. However, they may lack the detailed context that qualitative methods offer.
The approaches to qualitative research
To better understand the answer to “What is qualitative research?”, it’s necessary to consider various approaches within this methodology, each with its unique focus, implications, and functions.
1. Phenomenology.
This theory aims to understand and describe the lived experiences of individuals regarding a particular phenomenon.
Peculiarities:
- Focuses on personal experiences and perceptions.
- Seeks to uncover the essence of a phenomenon.
- Uses in-depth interviews and first-person accounts.
Example: Studying the experiences of people living with chronic illness to understand how it affects their daily lives.
2. Ethnography.
The approach involves immersive, long-term observation and participation in particular cultural or social contexts.
- Provides a deep understanding of cultural practices and social interactions.
- Involves participant observation and fieldwork.
- Researchers often live within the community they are studying.
Example: Observing and participating in the daily life of a rural village to understand its social structure and cultural practices.
3. Grounded theory.
This approach seeks to develop a research paper problem statement and theories based on participant data.
- Focuses on creating new theories rather than analyzing existing ones.
- Uses a systematic process of data collection and analysis.
- Involves constant comparison and coding of data.
Example: Developing a theory on how people cope with job loss by interviewing and analyzing the experiences of unemployed individuals.
4. Case study.
Case studies involve an in-depth examination of a single case or a small number of cases.
- Provides detailed, holistic insights.
- Can involve individuals, groups, organizations, or events.
- Uses multiple data sources such as interviews, observations, and documents.
Example: One of the qualitative research examples is analyzing a specific company’s approach to innovation to understand its success factors.
5. Narrative research.
This methodology focuses on the stories and personal interpretations of individuals.
- Emphasizes the chronological sequence and context of events.
- Seeks to understand how people make sense of their experiences.
- Uses interviews, diaries, and autobiographies.
Example: Collecting and analyzing the life stories of veterans to understand their experiences during and after military service.
6. Action research.
This theoretical model involves a collaborative approach in which researchers and participants work together to solve a problem or improve a situation.
- Aims for practical outcomes and improvements.
- Involves cycles of planning, acting, observing, and reflecting.
- Often used in educational, organizational, and community settings.
Example: Teachers collaborating with researchers to develop and test new teaching approaches to improve student engagement.
7. Discourse analysis.
It examines language use in texts, conversations, and other forms of communication.
- Focuses on how language shapes social reality and power dynamics.
- Analyzes speech, written texts, and media content.
- Explores the underlying meanings and implications of language.
Example: Analyzing political speeches to understand how leaders construct and convey their messages to the public.
Each of these examples of qualitative research offers unique tools and perspectives, enabling researchers to delve deeply into complex issues and gain a rich understanding of the issue they study.
Qualitative research methods
Various techniques exist to explore phenomena in depth and understand the complexities of human behavior, experiences, and social interactions. Some key methodologies that are commonly used in different sciences include several approaches.
Unstructured interviews;
These are informal and open-ended, designed to capture detailed narratives without imposing preconceived notions. Researchers typically start with a broad question and encourage interviewees to share their stories freely.
Semi-structured interviews;
They involve a core set of questions that allow researchers to explore topics deeply, adapting their inquiries based on responses received. This method of qualitative research design aims to gather rich, descriptive information, such as understanding what qualities make a good teacher.
Open questionnaire surveys;
They differ from closed-ended surveys in that they seek opinions and descriptions through open-ended questions. They allow for gathering diverse viewpoints from a larger group than one-on-one interviews would permit.
Observation;
It relies on researchers' skills to observe and interpret unbiased behaviors or activities. For instance, in education research, observation might track how students stay focused and manage distractions, recorded through field notes taken during or shortly after the observation.
Keeping logs and diaries;
This involves participants or researchers documenting daily activities or study contexts. Participants might record their social interactions or exercise routines, giving detailed data for later analysis. Researchers may also maintain diaries to document study contexts, helping to explain findings and other information sources.
All types of qualitative research have their strengths for gathering detailed information and exploring the social, cultural, and psychological aspects of exploration topics. Learners often use several methods (triangulation) to confirm their findings and deepen their understanding of complex subjects. If you need assistance choosing the most appropriate method to explore, feel free to contact our website, as we offer essays for sale and support with academic papers.
Advantages and disadvantages of the qualitative research methodology
This approach has unique strengths, making it valuable in many sciences. One of the primary advantages of qualitative research is its ability to capture participants' voices and perspectives accurately. It is highly adaptable, allowing researchers to modify the technique as new questions and ideas arise. This flexibility allows researchers to investigate new ideas and trends without being limited to set methods from the start. While this approach has many strengths, it also has significant drawbacks. A research paper writer faces practical and theoretical limitations when analyzing and interpreting data. Let’s consider all the pros and cons of this methodology in detail.
Strengths of qualitative research:
- Adaptability: Data gathering and analysis can be adjusted as new patterns or ideas develop, ensuring the study remains relevant and responsive.
- Real-world contexts: Research often occurs in natural conditions, providing a more authentic understanding of phenomena and describing the particularities of human behavior and interactions.
- Rich insights: Detailed analysis of people’s feelings, perceptions, and experiences can be useful for designing, testing, or developing systems, products, and services.
- Innovation: Open-ended responses allow experts to discover new problems or opportunities, leading to innovative ideas and approaches.
Limitations of qualitative research:
- Unpredictability: Real-world conditions often introduce uncontrolled factors, making this approach less reliable and difficult to replicate.
- Bias: The qualitative method relies heavily on the researcher’s viewpoint, leading to subjective interpretations. This makes it challenging to replicate studies and achieve consistent results.
- Limited applicability: Small, specific samples give detailed information but limit the ability to generalize findings to a broader population. Conclusions about the qualitative research topics may be biased and not representative of the wider population.
- Time and effort: Analyzing qualitative data is time-consuming and labor-intensive. While software can help, much of the analysis must be done manually, requiring significant effort and expertise.
So, qualitative methodology offers significant benefits, such as adaptability, real-world context, rich insights, and fostering innovation. However, it also presents challenges like unpredictability, bias, limited applicability, or time- and labor-intensive. Understanding these pros and cons helps researchers make informed decisions about when and how to effectively utilize various types of qualitative research designs in their studies.
Final thoughts
Qualitative research provides a valuable understanding of complicated human experiences and social situations, making it a strong tool in various areas of study. Despite its challenges, such as unreliability, subjectivity, and limited generalizability, its strengths in flexibility, natural settings, and generating meaningful insights make it an essential approach. If you are one of the students looking to incorporate qualitative methodology into their academic papers, EduBirdie is here to help. Our experts can guide you through the process, ensuring your work is thorough, credible, and impactful.
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What is qualitative data? How to understand, collect, and analyze it
A comprehensive guide to qualitative data, how it differs from quantitative data, and why it's a valuable tool for solving problems.
What is qualitative research?
Importance of qualitative data.
- Differences between qualitative and quantitative data
Characteristics of qualitative data
Types of qualitative data.
- Pros and cons
- Collection methods
Everything that’s done digitally—from surfing the web to conducting a transaction—creates a data trail. And data analysts are constantly exploring and examining that trail, trying to find out ways to use data to make better decisions.
Different types of data define more and more of our interactions online—one of the most common and well-known being qualitative data or data that can be expressed in descriptions and feelings.
This guide takes a deep look at what qualitative data is, what it can be used for, how it’s collected, and how it’s important to you.
Key takeaways:
Qualitative data gives insights into people's thoughts and feelings through detailed descriptions from interviews, observations, and visual materials.
The three main types of qualitative data are binary, nominal, and ordinal.
There are many different types of qualitative data, like data in research, work, and statistics.
Both qualitative and quantitative research are conducted through surveys and interviews, among other methods.
What is qualitative data?
Qualitative data is descriptive information that captures observable qualities and characteristics not quantifiable by numbers. It is collected from interviews, focus groups, observations, and documents offering insights into experiences, perceptions, and behaviors.
Qualitative data analysis cannot be counted or measured because it describes the data. It refers to the words or labels used to describe certain characteristics or traits.
This type of data answers the "why" or "how" behind the analysis . It’s often used to conduct open-ended studies, allowing those partaking to show their true feelings and actions without direction.
Think of qualitative data as the type of data you’d get if you were to ask someone why they did something—what was their reasoning?
Qualitative research not only helps to collect data, it also gives the researcher a chance to understand the trends and meanings of natural actions.
This type of data research focuses on the qualities of users—the actions behind the numbers. Qualitative research is the descriptive and subjective research that helps bring context to quantitative data.
It’s flexible and iterative. For example:
The music had a light tone that filled the kitchen.
Every blue button had white lettering, while the red buttons had yellow.
The little girl had red hair with a white hat.
Qualitative data is important in determining the frequency of traits or characteristics.
Understanding your data can help you understand your customers, users, or visitors better. And, when you understand your audience better, you can make them happier. First-party data , which is collected directly from your own audience, is especially valuable as it provides the most accurate and relevant insights for your specific needs.
Qualitative data helps the market researcher answer questions like what issues or problems they are facing, what motivates them, and what improvements can be made.
Examples of qualitative data
You’ve most likely used qualitative data today. This type of data is found in your everyday work and in statistics all over the web. Here are some examples of qualitative data in descriptions, research, work, and statistics.
Qualitative data in descriptions
Analysis of qualitative data requires descriptive context in order to support its theories and hypothesis. Here are some core examples of descriptive qualitative data:
The extremely short woman has curly hair and brilliant blue eyes.
A bright white light pierced the small dark space.
The plump fish jumped out of crystal-clear waters.
The fluffy brown dog jumped over the tall white fence.
A soft cloud floated by an otherwise bright blue sky.
Qualitative data in research
Qualitative data research methods allow analysts to use contextual information to create theories and models. These open- and closed-ended questions can be helpful to understand the reasoning behind motivations, frustrations, and actions —in any type of case.
Some examples of qualitative data collection in research:
What country do you work in?
What is your most recent job title?
How do you rank in the search engines?
How do you rate your purchase: good, bad, or exceptional?
Qualitative data at work
Professionals in various industries use qualitative observations in their work and research. Examples of this type of data in the workforce include:
A manager gives an employee constructive criticism on their skills. "Your efforts are solid and you understand the product knowledge well, just have patience."
A judge shares the verdict with the courtroom. "The man was found not guilty and is free to go."
A sales associate collects feedback from customers. "The customer said the check-out button did not work.”
A teacher gives feedback to their student. "I gave you an A on this project because of your dedication and commitment to the cause."
A digital marketer watches a session replay to get an understand of how users use their platform.
Qualitative data in statistics
Qualitative data can provide important statistics about any industry, any group of users, and any products. Here are some examples of qualitative data set collections in statistics:
The age, weight, and height of a group of body types to determine clothing size charts.
The origin, gender, and location for a census reading.
The name, title, and profession of people attending a conference to aid in follow-up emails.
Difference between qualitative and quantitative data
Qualitative and quantitative data are much different, but bring equal value to any data analysis. When it comes to understanding data research, there are different analysis methods, collection types and uses.
Here are the differences between qualitative and quantitative data :
Qualitative data is individualized, descriptive, and relating to emotions.
Quantitative data is countable, measurable and relating to numbers.
Qualitative data helps us understand why, or how something occurred behind certain behaviors .
Quantitative data helps us understand how many, how much, or how often something occurred.
Qualitative data is subjective and personalized.
Quantitative data is fixed and ubiquitous.
Qualitative research methods are conducted through observations or in-depth interviews.
Quantitative research methods are conducted through surveys and factual measuring.
Qualitative data is analyzed by grouping the data into classifications and topics.
Quantitative data is analyzed using statistical analysis.
Both provide a ton of value for any data collection and are key to truly understanding trending use cases and patterns in behavior . Dig deeper into quantitative data examples .
![qualitative research thesis method Qualtitative vs quantitative examples](https://images.ctfassets.net/dkgr2j75jrom/6EkS63alrQ62cHmOClGQnZ/b96701f832d50d393f859d73225c2b57/PillarPage-Qual-Quan__1_-min.png?w=750&h=383&q=50&fm=png&bg=transparent)
The characteristics of qualitative data are vast. There are a few traits that stand out amongst other data that should be understood for successful data analysis.
Descriptive : describing or classifying in an objective and nonjudgmental way.
Detailed : to give an account in words with full particulars.
Open-ended : having no determined limit or boundary.
Non-numerical : not containing numbers.
Subjective : based on or influenced by personal feelings, tastes, or opinions.
With qualitative data samples, these traits can help you understand the meaning behind the equation—or for lack of a better term, what’s behind the results.
As we narrow down the importance of qualitative data, you should understand that there are different data types. Data analysts often categorize qualitative data into three types:
1. Binary data
Binary data is numerically represented by a combination of zeros and ones. Binary data is the only category of data that can be directly understood and executed by a computer.
Data analysts use binary data to create statistical models that predict how often the study subject is likely to be positive or negative, up or down, right or wrong—based on a zero scale.
2. Nominal data
Nominal data , also referred to as “named, labeled data” or “nominal scaled data,” is any type of data used to label something without giving it a numerical value.
Data analysts use nominal data to determine statistically significant differences between sets of qualitative data.
For example, a multiple-choice test to profile participants’ skills in a study.
3. Ordinal data
Ordinal data is qualitative data categorized in a particular order or on a ranging scale. When researchers use ordinal data, the order of the qualitative information matters more than the difference between each category. Data analysts might use ordinal data when creating charts, while researchers might use it to classify groups, such as age, gender, or class.
For example, a Net Promoter Score ( NPS ) survey has results that are on a 0-10 satisfaction scale.
When should you use qualitative research?
One of the important things to learn about qualitative data is when to use it.
Qualitative data is used when you need to determine the particular trends of traits or characteristics or to form parameters for larger data sets to be observed. Qualitative data provides the means by which analysts can quantify the world around them.
You would use qualitative data to help answer questions like who your customers are, what issues or problems they’re facing, and where they need to focus their attention, so you can better solve those issues.
Qualitative data is widely used to understand language consumers speak—so apply it where necessary.
Pros and cons of qualitative data
Qualitative data is a detailed, deep understanding of a topic through observing and interviewing a sample of people. There are both benefits and drawbacks to this type of data.
Pros of qualitative data
Qualitative research is affordable and requires a small sample size.
Qualitative data provides a predictive element and provides specific insight into development.
Qualitative research focuses on the details of personal choice and uses these individual choices as workable data.
Qualitative research works to remove bias from its collected data by using an open-ended response process.
Qualitative data research provides useful content in any thematic analysis.
Cons of qualitative data
Qualitative data can be time-consuming to collect and can be difficult to scale out to a larger population.
Qualitative research creates subjective information points.
Qualitative research can involve significant levels of repetition and is often difficult to replicate.
Qualitative research relies on the knowledge of the researchers.
Qualitative research does not offer statistical analysis, for that, you have to turn to quantitative data.
Qualitative data collection methods
Here are the main approaches and collection methods of qualitative studies and data:
1. Interviews
Personal interviews are one of the most commonly used deductive data collection methods for qualitative research, because of its personal approach.
The interview may be informal and unstructured and is often conversational in nature. The interviewer or the researcher collects data directly from the interviewee one-to-one. Mostly the open-ended questions are asked spontaneously, with the interviewer allowing the flow of the interview to dictate the questions and answers.
The point of the interview is to obtain how the interviewee feels about the subject.
2. Focus groups
Focus groups are held in a discussion-style setting with 6 to 10 people. The moderator is assigned to monitor and dictate the discussion based on focus questions.
Depending on the qualitative data that is needed, the members of the group may have something in common. For example, a researcher conducting a study on dog sled runners understands dogs, sleds, and snow and would have sufficient knowledge of the subject matter.
3. Data records
Data doesn’t start with your collection, it has most likely been obtained in the past.
Using already existing reliable data and similar sources of information as the data source is a surefire way to obtain qualitative research. Much like going to a library, you can review books and other reference material to collect relevant data that can be used in the research.
For example, if you were to study the trends of dictionaries, you would want to know the past history of every dictionary made, starting with the very first one.
4. Observation
Observation is a longstanding qualitative data collection method, where the researcher simply observes behaviors in a participant's natural setting. They keep a keen eye on the participants and take down transcript notes to find out innate responses and reactions without prompting.
Typically observation is an inductive approach, which is used when a researcher has very little or no idea of the research phenomenon.
Other documentation methods, such as video recordings, audio recordings, and photo imagery, may be used to obtain qualitative data.
Further reading: Site observations through heatmaps
5. Case studies
Case studies are an intensive analysis of an individual person or community with a stress on developmental factors in relation to the environment.
In this method, data is gathered by an in-depth analysis and is used to understand both simple and complex subjects. The goal of a case study is to see how using a product or service has positively impacted the subject, showcasing a solution to a problem or the like.
6. Longitudinal studies
A longitudinal study is where people who share a single characteristic are studied over a period of time.
This data collection method is performed on the same subject repeatedly over an extended period. It is an observational research method that goes on for a few years and, in some cases, decades. The goal is to find correlations of subjects with common traits.
For example, medical researchers conduct longitudinal studies to ascertain the effects of a drug or the symptoms related.
Qualitative data analysis tools
And, as with anything—you aren’t able to be successful without the right tools. Here are a few qualitative data analysis tools to have in your toolbox:
MAXQDA —A qualitative and mixed-method data analysis software
Fullstory —A behavioral data and analysis platform
ATLAS.ti —A powerful qualitative data tool that offers AI-based functions
Quirkos —Qualitative data analysis software for the simple learner
Dedoose —A project management and analysis tool for collaboration and teamwork
Taguette —A free, open-source, data analysis and organization platform
MonkeyLearn —AI-powered, qualitative text analysis, and visualization tool
Qualtrics —Experience management software
Frequently asked questions about qualitative data
Is qualitative data subjective.
Yes, categorical data or qualitative data is information that cannot generally be proven. For instance, the statement “the chair is too small” depends on what it is used for and by whom it is being used.
Who uses qualitative data?
If you’re interested in the following, you should use qualitative data:
Understand emotional connections to your brand
Identify obstacles in any funnel, for example with session replay
Uncover confusion about your messaging
Locate product feature gaps
Improve usability of your website, app, or experience
Observe how people talk, think, and feel about your brand
Learn how an organization selects vendors and partners
What are the steps for qualitative data?
1. Transcribe your data : Once you’ve collected all the data, you need to transcribe it. The first step in analyzing your data is arranging it systematically. Arranging data means converting all the data into a text format.
2. Organize your data : Go back to your research objectives and organize the data based on the questions asked. Arrange your research objective in a table, so it appears visually clear. Avoid working with unorganized data, there will be no conclusive results obtained.
3. Categorize and assign the data : The coding process of qualitative data means categorizing and assigning variables, properties, and patterns. Coding is an important step in qualitative data analysis, as you can derive theories from relevant research findings. You can then begin to gain in-depth insight into the data that help make informed decisions.
4. Validate your data : Data validation is a recurring step that should be followed throughout the research process. There are two sides to validating data: the accuracy and reliability of your research methods, which is the extent to which the methods produce accurate data consistently.
5. Conclude the data analysis : Present your data in a report that shares the method used to conduct the research studies, the outcomes, and the projected hypothesis of your findings in any related areas.
Is qualitative data better than quantitative data?
One is not better than the other, rather they work cohesively to create a better overall data analysis experience. Understanding the importance of both qualitative and quantitative data is going to produce the best possible data content analysis outcome for any study.
Further reading : Qualitative vs. quantitative data — what's the difference?
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Qualitative research involves collecting and analyzing non-numerical data (e.g., text, video, or audio) to understand concepts, opinions, or experiences. It can be used to gather in-depth insights into a problem or generate new ideas for research. Qualitative research is the opposite of quantitative research, which involves collecting and ...
While many books and articles guide various qualitative research methods and analyses, there is currently no concise resource that explains and differentiates among the most common qualitative approaches. We believe novice qualitative researchers, students planning the design of a qualitative study or taking an introductory qualitative research course, and faculty teaching such courses can ...
This is for PhD students working on a qualitative thesis who have completed their data collection and analysis and are at the stage of writing up. The materials should also be useful if you are writing up a 'mixed-methods' thesis, including chapters of analysis and discussion of qualitative data.
Abstract. This paper aims to provide an overview of the use and assessment of qualitative research methods in the health sciences. Qualitative research can be defined as the study of the nature of phenomena and is especially appropriate for answering questions of why something is (not) observed, assessing complex multi-component interventions ...
Qualitative Research. Qualitative research is a type of research methodology that focuses on exploring and understanding people's beliefs, attitudes, behaviors, and experiences through the collection and analysis of non-numerical data. It seeks to answer research questions through the examination of subjective data, such as interviews, focus groups, observations, and textual analysis.
Completing Your Qualitative Dissertation. 2nd ed. Thousand Oaks, CA: SAGE. Specifically designed to guide graduate students through the research process. ... Qualitative Research Methods for the Social Sciences. Pearson. Although a good introduction to qualitative methods, the authors favor symbolic interactionist and dramaturgical approaches ...
It can be used to gather in-depth insights into a problem or generate new ideas for research. It answers the hows and whys instead of how many or how much. It could be structured as a stand-alone study, purely relying on qualitative data or it could be part of mixed-methods research that combines qualitative and quantitative data.
Dissertation Methodology. In any research, the methodology chapter is one of the key components of your dissertation. ... This combines qualitative and quantitative research methods in a single study. It's used to answer more complex research questions and is becoming more popular in fields like social sciences, health sciences, and education.
Qualitative research methods. Each of the research approaches involve using one or more data collection methods.These are some of the most common qualitative methods: Observations: recording what you have seen, heard, or encountered in detailed field notes. Interviews: personally asking people questions in one-on-one conversations. Focus groups: asking questions and generating discussion among ...
Bibliography Includes bibliographical references and index. Contents. Preface Acknowledgments; PART 1 PREPARING FOR METHODOLOGICAL WORK; Chapter 1 Working as a Qualitative Methodologist in Dissertation Contexts Ensuring That Qualitative Methodology Is the Right Fit for Your Dissertation Research Interests Developing a Qualitative Methodology for Your Dissertation Becoming a Qualitative ...
your chosen research method, and describe the process and participants in your study). The Methodology chapter is perhaps the part of a qualitative thesis that is most unlike its equivalent in a quantitative study. Students doing quantitative research have an established conventional 'model' to work to, which comprises these possible elements:
How to choose a research methodology. To choose the right research methodology for your dissertation or thesis, you need to consider three important factors. Based on these three factors, you can decide on your overarching approach - qualitative, quantitative or mixed methods. Once you've made that decision, you can flesh out the finer ...
Introduction to Qualitative Research Methods by Steven J. Taylor; Robert Bogdan; Marjorie DeVault An informative real-world guide to studying the "why" of human behavior Introduction to Qualitative Research Methods is a practical, comprehensive guide to the collection and presentation of qualitative data. Unique in the market, this book ...
Designing and writing a qualitative dissertation methodology chapter can be done! Qualitative Dissertation Methodology: A Guide for Research Design and Methods functions as a dissertation advisor to help students construct and write a qualitative methodological framework for their research.
The book examines questions such as why people do such research, how they go about doing it, what results it leads to, and how results can be presented in a plausible and useful way. Its ...
Rationale for Qualitative Methods The purpose of qualitative research is to understand and explain participant meaning (Morrow & Smith, 2000). More specifically, Creswell (1998) defines qualitative research as, an inquiry process of understanding based on distinct methodological traditions of inquiry that explore a social or human problem.
It is very important to choose the right research methodology and methods for your thesis, as your research is the base that your entire thesis will rest on. ... You will first have to choose whether you wish to use quantitative or qualitative research methods. Quantitative research involves experiments, surveys, testing, and structured content ...
In this section on Qualitative Research you can find out about: Developing a theoretical framework; Reflecting on your position; Extended literature reviews; Presenting qualitative data; You might also want to consult our other sections on Planning your research, Quantitative research and Writing up research, and check out the Additional resources.
The method you choose will depend on your research objectives and questions. These are the most common qualitative data analysis methods to help you complete your dissertation: 2. Content analysis: This method is used to analyze documented information from texts, email, media and tangible items.
Observational methods are useful for in-depth analyses of behaviours in people, animals, organisations, events or phenomena. They can test a theory or products in real life or simulated settings. They generally a qualitative research method. Questionnaires and surveys.
qualitative research professor. I was positive that I would design a quantitative research study but the qualitative courses in the program highlighted the merits of qualitative research. Dr. Cozza and Ms. Rosaria Cimino, thanks for the advisement support. To all the Ed.D. candidates that I encountered on my academic journey, especially my
completion of this dissertation. I am truly privileged to have had the support and valuable guidance of Dr. Jim Ryan, my thesis supervisor during this research. The effort, encouragement, wisdom, and valuable recommendations and guidance he imparted greatly supported me throughout this research completion. Many thanks, Jim.
To achieve this, they employ various techniques and data collection methods in qualitative research allowing for a deeper exploration of human experiences. Participant observation, in-depth interviews, and other qualitative methods are commonly used to gather rich, detailed data to uncover key aspects of social behavior and relationships.
Qualitative data collection methods. Here are the main approaches and collection methods of qualitative studies and data: 1. Interviews. Personal interviews are one of the most commonly used deductive data collection methods for qualitative research, because of its personal approach.