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An Introduction to Qualitative Research

Student resources, part 1 (chapters 1 – 5): foundations of qualitative research.

Chapter 5. Sampling

Introduction.

Most Americans will experience unemployment at some point in their lives. Sarah Damaske ( 2021 ) was interested in learning about how men and women experience unemployment differently. To answer this question, she interviewed unemployed people. After conducting a “pilot study” with twenty interviewees, she realized she was also interested in finding out how working-class and middle-class persons experienced unemployment differently. She found one hundred persons through local unemployment offices. She purposefully selected a roughly equal number of men and women and working-class and middle-class persons for the study. This would allow her to make the kinds of comparisons she was interested in. She further refined her selection of persons to interview:

I decided that I needed to be able to focus my attention on gender and class; therefore, I interviewed only people born between 1962 and 1987 (ages 28–52, the prime working and child-rearing years), those who worked full-time before their job loss, those who experienced an involuntary job loss during the past year, and those who did not lose a job for cause (e.g., were not fired because of their behavior at work). ( 244 )

The people she ultimately interviewed compose her sample. They represent (“sample”) the larger population of the involuntarily unemployed. This “theoretically informed stratified sampling design” allowed Damaske “to achieve relatively equal distribution of participation across gender and class,” but it came with some limitations. For one, the unemployment centers were located in primarily White areas of the country, so there were very few persons of color interviewed. Qualitative researchers must make these kinds of decisions all the time—who to include and who not to include. There is never an absolutely correct decision, as the choice is linked to the particular research question posed by the particular researcher, although some sampling choices are more compelling than others. In this case, Damaske made the choice to foreground both gender and class rather than compare all middle-class men and women or women of color from different class positions or just talk to White men. She leaves the door open for other researchers to sample differently. Because science is a collective enterprise, it is most likely someone will be inspired to conduct a similar study as Damaske’s but with an entirely different sample.

This chapter is all about sampling. After you have developed a research question and have a general idea of how you will collect data (observations or 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. You might remember studying sampling in a quantitative research course. Sampling is important here too, but it works a bit differently. Unlike quantitative research, qualitative research involves nonprobability sampling. This chapter explains why this is so and what qualities instead make a good sample for qualitative research.

Quick Terms Refresher

The population is the entire group that you want to draw conclusions about.
The sample is the specific group of individuals that you will collect data from.
Sampling frame is the actual list of individuals that the sample will be drawn from. Ideally, it should include the entire target population (and nobody who is not part of that population).
Sample size is how many individuals (or units) are included in your sample.

The “Who” of Your Research Study

After you have turned your general research interest into an actual research question and identified an approach you want to take to answer that question, you will need to specify the people you will be interviewing or observing. In most qualitative research, the objects of your study will indeed be people. In some cases, however, your objects might be content left by people (e.g., diaries, yearbooks, photographs) or documents (official or unofficial) or even institutions (e.g., schools, medical centers) and locations (e.g., nation-states, cities). Chances are, whatever “people, places, or things” are the objects of your study, you will not really be able to talk to, observe, or follow every single individual/object of the entire population of interest. You will need to create a sample of the population . Sampling in qualitative research has different purposes and goals than sampling in quantitative research. Sampling in both allows you to say something of interest about a population without having to include the entire population in your sample.

We begin this chapter with the case of a population of interest composed of actual people. After we have a better understanding of populations and samples that involve real people, we’ll discuss sampling in other types of qualitative research, such as archival research, content analysis, and case studies. We’ll then move to a larger discussion about the difference between sampling in qualitative research generally versus quantitative research, then we’ll move on to the idea of “theoretical” generalizability, and finally, we’ll conclude with some practical tips on the correct “number” to include in one’s sample.

Sampling People

To help think through samples, let’s imagine we want to know more about “vaccine hesitancy.” We’ve all lived through 2020 and 2021, and we know that a sizable number of people in the United States (and elsewhere) were slow to accept vaccines, even when these were freely available. By some accounts, about one-third of Americans initially refused vaccination. Why is this so? Well, as I write this in the summer of 2021, we know that some people actively refused the vaccination, thinking it was harmful or part of a government plot. Others were simply lazy or dismissed the necessity. And still others were worried about harmful side effects. The general population of interest here (all adult Americans who were not vaccinated by August 2021) may be as many as eighty million people. We clearly cannot talk to all of them. So we will have to narrow the number to something manageable. How can we do this?

First, we have to think about our actual research question and the form of research we are conducting. I am going to begin with a quantitative research question. Quantitative research questions tend to be simpler to visualize, at least when we are first starting out doing social science research. So let us say we want to know what percentage of each kind of resistance is out there and how race or class or gender affects vaccine hesitancy. Again, we don’t have the ability to talk to everyone. But harnessing what we know about normal probability distributions (see quantitative methods for more on this), we can find this out through a sample that represents the general population. We can’t really address these particular questions if we only talk to White women who go to college with us. And if you are really trying to generalize the specific findings of your sample to the larger population, you will have to employ probability sampling , a sampling technique where a researcher sets a selection of a few criteria and chooses members of a population randomly. Why randomly? If truly random, all the members have an equal opportunity to be a part of the sample, and thus we avoid the problem of having only our friends and neighbors (who may be very different from other people in the population) in the study. Mathematically, there is going to be a certain number that will be large enough to allow us to generalize our particular findings from our sample population to the population at large. It might surprise you how small that number can be. Election polls of no more than one thousand people are routinely used to predict actual election outcomes of millions of people. Below that number, however, you will not be able to make generalizations. Talking to five people at random is simply not enough people to predict a presidential election.

In order to answer quantitative research questions of causality, one must employ probability sampling. Quantitative researchers try to generalize their findings to a larger population. Samples are designed with that in mind. Qualitative researchers ask very different questions, though. Qualitative research questions are not about “how many” of a certain group do X (in this case, what percentage of the unvaccinated hesitate for concern about safety rather than reject vaccination on political grounds). Qualitative research employs nonprobability sampling . By definition, not everyone has an equal opportunity to be included in the sample. The researcher might select White women they go to college with to provide insight into racial and gender dynamics at play. Whatever is found by doing so will not be generalizable to everyone who has not been vaccinated, or even all White women who have not been vaccinated, or even all White women who have not been vaccinated who are in this particular college. That is not the point of qualitative research at all. This is a really important distinction, so I will repeat in bold: Qualitative researchers are not trying to statistically generalize specific findings to a larger population . They have not failed when their sample cannot be generalized, as that is not the point at all.

In the previous paragraph, I said it would be perfectly acceptable for a qualitative researcher to interview five White women with whom she goes to college about their vaccine hesitancy “to provide insight into racial and gender dynamics at play.” The key word here is “insight.” Rather than use a sample as a stand-in for the general population, as quantitative researchers do, the qualitative researcher uses the sample to gain insight into a process or phenomenon. The qualitative researcher is not going to be content with simply asking each of the women to state her reason for not being vaccinated and then draw conclusions that, because one in five of these women were concerned about their health, one in five of all people were also concerned about their health. That would be, frankly, a very poor study indeed. Rather, the qualitative researcher might sit down with each of the women and conduct a lengthy interview about what the vaccine means to her, why she is hesitant, how she manages her hesitancy (how she explains it to her friends), what she thinks about others who are unvaccinated, what she thinks of those who have been vaccinated, and what she knows or thinks she knows about COVID-19. The researcher might include specific interview questions about the college context, about their status as White women, about the political beliefs they hold about racism in the US, and about how their own political affiliations may or may not provide narrative scripts about “protective whiteness.” There are many interesting things to ask and learn about and many things to discover. Where a quantitative researcher begins with clear parameters to set their population and guide their sample selection process, the qualitative researcher is discovering new parameters, making it impossible to engage in probability sampling.

Looking at it this way, sampling for qualitative researchers needs to be more strategic. More theoretically informed. What persons can be interviewed or observed that would provide maximum insight into what is still unknown? In other words, qualitative researchers think through what cases they could learn the most from, and those are the cases selected to study: “What would be ‘bias’ in statistical sampling, and therefore a weakness, becomes intended focus in qualitative sampling, and therefore a strength. The logic and power of purposeful sampling like in selecting information-rich cases for study in depth. Information-rich cases are those from which one can learn a great deal about issues of central importance to the purpose of the inquiry, thus the term purposeful sampling” ( Patton 2002:230 ; emphases in the original).

Before selecting your sample, though, it is important to clearly identify the general population of interest. You need to know this before you can determine the sample. In our example case, it is “adult Americans who have not yet been vaccinated.” Depending on the specific qualitative research question, however, it might be “adult Americans who have been vaccinated for political reasons” or even “college students who have not been vaccinated.” What insights are you seeking? Do you want to know how politics is affecting vaccination? Or do you want to understand how people manage being an outlier in a particular setting (unvaccinated where vaccinations are heavily encouraged if not required)? More clearly stated, your population should align with your research question . Think back to the opening story about Damaske’s work studying the unemployed. She drew her sample narrowly to address the particular questions she was interested in pursuing. Knowing your questions or, at a minimum, why you are interested in the topic will allow you to draw the best sample possible to achieve insight.

Once you have your population in mind, how do you go about getting people to agree to be in your sample? In qualitative research, it is permissible to find people by convenience. Just ask for people who fit your sample criteria and see who shows up. Or reach out to friends and colleagues and see if they know anyone that fits. Don’t let the name convenience sampling mislead you; this is not exactly “easy,” and it is certainly a valid form of sampling in qualitative research. The more unknowns you have about what you will find, the more convenience sampling makes sense. If you don’t know how race or class or political affiliation might matter, and your population is unvaccinated college students, you can construct a sample of college students by placing an advertisement in the student paper or posting a flyer on a notice board. Whoever answers is your sample. That is what is meant by a convenience sample. A common variation of convenience sampling is snowball sampling . This is particularly useful if your target population is hard to find. Let’s say you posted a flyer about your study and only two college students responded. You could then ask those two students for referrals. They tell their friends, and those friends tell other friends, and, like a snowball, your sample gets bigger and bigger.

Researcher Note

Gaining Access: When Your Friend Is Your Research Subject

My early experience with qualitative research was rather unique. At that time, I needed to do a project that required me to interview first-generation college students, and my friends, with whom I had been sharing a dorm for two years, just perfectly fell into the sample category. Thus, I just asked them and easily “gained my access” to the research subject; I know them, we are friends, and I am part of them. I am an insider. I also thought, “Well, since I am part of the group, I can easily understand their language and norms, I can capture their honesty, read their nonverbal cues well, will get more information, as they will be more opened to me because they trust me.” All in all, easy access with rich information. But, gosh, I did not realize that my status as an insider came with a price! When structuring the interview questions, I began to realize that rather than focusing on the unique experiences of my friends, I mostly based the questions on my own experiences, assuming we have similar if not the same experiences. I began to struggle with my objectivity and even questioned my role; am I doing this as part of the group or as a researcher? I came to know later that my status as an insider or my “positionality” may impact my research. It not only shapes the process of data collection but might heavily influence my interpretation of the data. I came to realize that although my inside status came with a lot of benefits (especially for access), it could also bring some drawbacks.

—Dede Setiono, PhD student focusing on international development and environmental policy, Oregon State University

The more you know about what you might find, the more strategic you can be. If you wanted to compare how politically conservative and politically liberal college students explained their vaccine hesitancy, for example, you might construct a sample purposively, finding an equal number of both types of students so that you can make those comparisons in your analysis. This is what Damaske ( 2021 ) did. You could still use convenience or snowball sampling as a way of recruitment. Post a flyer at the conservative student club and then ask for referrals from the one student that agrees to be interviewed. As with convenience sampling, there are variations of purposive sampling as well as other names used (e.g., judgment, quota, stratified, criterion, theoretical). Try not to get bogged down in the nomenclature; instead, focus on identifying the general population that matches your research question and then using a sampling method that is most likely to provide insight, given the types of questions you have.

There are all kinds of ways of being strategic with sampling in qualitative research. Here are a few of my favorite techniques for maximizing insight:

Consider using “extreme” or “deviant” cases. Maybe your college houses a prominent anti-vaxxer who has written about and demonstrated against the college’s policy on vaccines. You could learn a lot from that single case (depending on your research question, of course).
Consider “intensity”: people and cases and circumstances where your questions are more likely to feature prominently (but not extremely or deviantly). For example, you could compare those who volunteer at local Republican and Democratic election headquarters during an election season in a study on why party matters. Those who volunteer are more likely to have something to say than those who are more apathetic.
Maximize variation, as with the case of “politically liberal” versus “politically conservative,” or include an array of social locations (young vs. old; Northwest vs. Southeast region). This kind of heterogeneity sampling can capture and describe the central themes that cut across the variations: any common patterns that emerge, even in this wildly mismatched sample, are probably important to note!
Rather than maximize the variation, you could select a small homogenous sample to describe some particular subgroup in depth. Focus groups are often the best form of data collection for homogeneity sampling.
Think about which cases are “critical” or politically important—ones that “if it happens here, it would happen anywhere” or a case that is politically sensitive, as with the single “blue” (Democratic) county in a “red” (Republican) state. In both, you are choosing a site that would yield the most information and have the greatest impact on the development of knowledge.
On the other hand, sometimes you want to select the “typical”—the typical college student, for example. You are trying to not generalize from the typical but illustrate aspects that may be typical of this case or group. When selecting for typicality, be clear with yourself about why the typical matches your research questions (and who might be excluded or marginalized in doing so).
Finally, it is often a good idea to look for disconfirming cases : if you are at the stage where you have a hypothesis (of sorts), you might select those who do not fit your hypothesis—you will surely learn something important there. They may be “exceptions that prove the rule” or exceptions that force you to alter your findings in order to make sense of these additional cases.

In addition to all these sampling variations, there is the theoretical approach taken by grounded theorists in which the researcher samples comparative people (or events) on the basis of their potential to represent important theoretical constructs. The sample, one can say, is by definition representative of the phenomenon of interest. It accompanies the constant comparative method of analysis. In the words of the funders of Grounded Theory , “Theoretical sampling is sampling on the basis of the emerging concepts, with the aim being to explore the dimensional range or varied conditions along which the properties of the concepts vary” ( Strauss and Corbin 1998:73 ).

When Your Population is Not Composed of People

I think it is easiest for most people to think of populations and samples in terms of people, but sometimes our units of analysis are not actually people. They could be places or institutions. Even so, you might still want to talk to people or observe the actions of people to understand those places or institutions. Or not! In the case of content analyses (see chapter 17), you won’t even have people involved at all but rather documents or films or photographs or news clippings. Everything we have covered about sampling applies to other units of analysis too. Let’s work through some examples.

Case Studies

When constructing a case study, it is helpful to think of your cases as sample populations in the same way that we considered people above. If, for example, you are comparing campus climates for diversity, your overall population may be “four-year college campuses in the US,” and from there you might decide to study three college campuses as your sample. Which three? Will you use purposeful sampling (perhaps [1] selecting three colleges in Oregon that are different sizes or [2] selecting three colleges across the US located in different political cultures or [3] varying the three colleges by racial makeup of the student body)? Or will you select three colleges at random, out of convenience? There are justifiable reasons for all approaches.

As with people, there are different ways of maximizing insight in your sample selection. Think about the following rationales: typical, diverse, extreme, deviant, influential, crucial, or even embodying a particular “pathway” ( Gerring 2008 ). When choosing a case or particular research site, Rubin ( 2021 ) suggests you bear in mind, first, what you are leaving out by selecting this particular case/site; second, what you might be overemphasizing by studying this case/site and not another; and, finally, whether you truly need to worry about either of those things—“that is, what are the sources of bias and how bad are they for what you are trying to do?” ( 89 ).

Once you have selected your cases, you may still want to include interviews with specific people or observations at particular sites within those cases. Then you go through possible sampling approaches all over again to determine which people will be contacted.

Content: Documents, Narrative Accounts, And So On

Although not often discussed as sampling, your selection of documents and other units to use in various content/historical analyses is subject to similar considerations. When you are asking quantitative-type questions (percentages and proportionalities of a general population), you will want to follow probabilistic sampling. For example, I created a random sample of accounts posted on the website studentloanjustice.org to delineate the types of problems people were having with student debt ( Hurst 2007 ). Even though my data was qualitative (narratives of student debt), I was actually asking a quantitative-type research question, so it was important that my sample was representative of the larger population (debtors who posted on the website). On the other hand, when you are asking qualitative-type questions, the selection process should be very different. In that case, use nonprobabilistic techniques, either convenience (where you are really new to this data and do not have the ability to set comparative criteria or even know what a deviant case would be) or some variant of purposive sampling. Let’s say you were interested in the visual representation of women in media published in the 1950s. You could select a national magazine like Time for a “typical” representation (and for its convenience, as all issues are freely available on the web and easy to search). Or you could compare one magazine known for its feminist content versus one antifeminist. The point is, sample selection is important even when you are not interviewing or observing people.

Goals of Qualitative Sampling versus Goals of Quantitative Sampling

We have already discussed some of the differences in the goals of quantitative and qualitative sampling above, but it is worth further discussion. The quantitative researcher seeks a sample that is representative of the population of interest so that they may properly generalize the results (e.g., if 80 percent of first-gen students in the sample were concerned with costs of college, then we can say there is a strong likelihood that 80 percent of first-gen students nationally are concerned with costs of college). The qualitative researcher does not seek to generalize in this way . They may want a representative sample because they are interested in typical responses or behaviors of the population of interest, but they may very well not want a representative sample at all. They might want an “extreme” or deviant case to highlight what could go wrong with a particular situation, or maybe they want to examine just one case as a way of understanding what elements might be of interest in further research. When thinking of your sample, you will have to know why you are selecting the units, and this relates back to your research question or sets of questions. It has nothing to do with having a representative sample to generalize results. You may be tempted—or it may be suggested to you by a quantitatively minded member of your committee—to create as large and representative a sample as you possibly can to earn credibility from quantitative researchers. Ignore this temptation or suggestion. The only thing you should be considering is what sample will best bring insight into the questions guiding your research. This has implications for the number of people (or units) in your study as well, which is the topic of the next section.

What is the Correct “Number” to Sample?

Because we are not trying to create a generalizable representative sample, the guidelines for the “number” of people to interview or news stories to code are also a bit more nebulous. There are some brilliant insightful studies out there with an n of 1 (meaning one person or one account used as the entire set of data). This is particularly so in the case of autoethnography, a variation of ethnographic research that uses the researcher’s own subject position and experiences as the basis of data collection and analysis. But it is true for all forms of qualitative research. There are no hard-and-fast rules here. The number to include is what is relevant and insightful to your particular study.

That said, humans do not thrive well under such ambiguity, and there are a few helpful suggestions that can be made. First, many qualitative researchers talk about “saturation” as the end point for data collection. You stop adding participants when you are no longer getting any new information (or so very little that the cost of adding another interview subject or spending another day in the field exceeds any likely benefits to the research). The term saturation was first used here by Glaser and Strauss ( 1967 ), the founders of Grounded Theory. Here is their explanation: “The criterion for judging when to stop sampling the different groups pertinent to a category is the category’s theoretical saturation . Saturation means that no additional data are being found whereby the sociologist can develop properties of the category. As he [or she] sees similar instances over and over again, the researcher becomes empirically confident that a category is saturated. [They go] out of [their] way to look for groups that stretch diversity of data as far as possible, just to make certain that saturation is based on the widest possible range of data on the category” ( 61 ).

It makes sense that the term was developed by grounded theorists, since this approach is rather more open-ended than other approaches used by qualitative researchers. With so much left open, having a guideline of “stop collecting data when you don’t find anything new” is reasonable. However, saturation can’t help much when first setting out your sample. How do you know how many people to contact to interview? What number will you put down in your institutional review board (IRB) protocol (see chapter 8)? You may guess how many people or units it will take to reach saturation, but there really is no way to know in advance. The best you can do is think about your population and your questions and look at what others have done with similar populations and questions.

Here are some suggestions to use as a starting point: For phenomenological studies, try to interview at least ten people for each major category or group of people . If you are comparing male-identified, female-identified, and gender-neutral college students in a study on gender regimes in social clubs, that means you might want to design a sample of thirty students, ten from each group. This is the minimum suggested number. Damaske’s ( 2021 ) sample of one hundred allows room for up to twenty-five participants in each of four “buckets” (e.g., working-class*female, working-class*male, middle-class*female, middle-class*male). If there is more than one comparative group (e.g., you are comparing students attending three different colleges, and you are comparing White and Black students in each), you can sometimes reduce the number for each group in your sample to five for, in this case, thirty total students. But that is really a bare minimum you will want to go. A lot of people will not trust you with only “five” cases in a bucket. Lareau ( 2021:24 ) advises a minimum of seven or nine for each bucket (or “cell,” in her words). The point is to think about what your analyses might look like and how comfortable you will be with a certain number of persons fitting each category.

Because qualitative research takes so much time and effort, it is rare for a beginning researcher to include more than thirty to fifty people or units in the study. You may not be able to conduct all the comparisons you might want simply because you cannot manage a larger sample. In that case, the limits of who you can reach or what you can include may influence you to rethink an original overcomplicated research design. Rather than include students from every racial group on a campus, for example, you might want to sample strategically, thinking about the most contrast (insightful), possibly excluding majority-race (White) students entirely, and simply using previous literature to fill in gaps in our understanding. For example, one of my former students was interested in discovering how race and class worked at a predominantly White institution (PWI). Due to time constraints, she simplified her study from an original sample frame of middle-class and working-class domestic Black and international African students (four buckets) to a sample frame of domestic Black and international African students (two buckets), allowing the complexities of class to come through individual accounts rather than from part of the sample frame. She wisely decided not to include White students in the sample, as her focus was on how minoritized students navigated the PWI. She was able to successfully complete her project and develop insights from the data with fewer than twenty interviewees. [1]

But what if you had unlimited time and resources? Would it always be better to interview more people or include more accounts, documents, and units of analysis? No! Your sample size should reflect your research question and the goals you have set yourself. Larger numbers can sometimes work against your goals. If, for example, you want to help bring out individual stories of success against the odds, adding more people to the analysis can end up drowning out those individual stories. Sometimes, the perfect size really is one (or three, or five). It really depends on what you are trying to discover and achieve in your study. Furthermore, studies of one hundred or more (people, documents, accounts, etc.) can sometimes be mistaken for quantitative research. Inevitably, the large sample size will push the researcher into simplifying the data numerically. And readers will begin to expect generalizability from such a large sample.

To summarize, “There are no rules for sample size in qualitative inquiry. Sample size depends on what you want to know, the purpose of the inquiry, what’s at stake, what will be useful, what will have credibility, and what can be done with available time and resources” ( Patton 2002:244 ).

How did you find/construct a sample?

Since qualitative researchers work with comparatively small sample sizes, getting your sample right is rather important. Yet it is also difficult to accomplish. For instance, a key question you need to ask yourself is whether you want a homogeneous or heterogeneous sample. In other words, do you want to include people in your study who are by and large the same, or do you want to have diversity in your sample?

For many years, I have studied the experiences of students who were the first in their families to attend university. There is a rather large number of sampling decisions I need to consider before starting the study. (1) Should I only talk to first-in-family students, or should I have a comparison group of students who are not first-in-family? (2) Do I need to strive for a gender distribution that matches undergraduate enrollment patterns? (3) Should I include participants that reflect diversity in gender identity and sexuality? (4) How about racial diversity? First-in-family status is strongly related to some ethnic or racial identity. (5) And how about areas of study?

As you can see, if I wanted to accommodate all these differences and get enough study participants in each category, I would quickly end up with a sample size of hundreds, which is not feasible in most qualitative research. In the end, for me, the most important decision was to maximize the voices of first-in-family students, which meant that I only included them in my sample. As for the other categories, I figured it was going to be hard enough to find first-in-family students, so I started recruiting with an open mind and an understanding that I may have to accept a lack of gender, sexuality, or racial diversity and then not be able to say anything about these issues. But I would definitely be able to speak about the experiences of being first-in-family.

—Wolfgang Lehmann, author of “Habitus Transformation and Hidden Injuries”

Examples of “Sample” Sections in Journal Articles

Think about some of the studies you have read in college, especially those with rich stories and accounts about people’s lives. Do you know how the people were selected to be the focus of those stories? If the account was published by an academic press (e.g., University of California Press or Princeton University Press) or in an academic journal, chances are that the author included a description of their sample selection. You can usually find these in a methodological appendix (book) or a section on “research methods” (article).

Here are two examples from recent books and one example from a recent article:

Example 1 . In It’s Not like I’m Poor: How Working Families Make Ends Meet in a Post-welfare World , the research team employed a mixed methods approach to understand how parents use the earned income tax credit, a refundable tax credit designed to provide relief for low- to moderate-income working people ( Halpern-Meekin et al. 2015 ). At the end of their book, their first appendix is “Introduction to Boston and the Research Project.” After describing the context of the study, they include the following description of their sample selection:

In June 2007, we drew 120 names at random from the roughly 332 surveys we gathered between February and April. Within each racial and ethnic group, we aimed for one-third married couples with children and two-thirds unmarried parents. We sent each of these families a letter informing them of the opportunity to participate in the in-depth portion of our study and then began calling the home and cell phone numbers they provided us on the surveys and knocking on the doors of the addresses they provided.…In the end, we interviewed 115 of the 120 families originally selected for the in-depth interview sample (the remaining five families declined to participate). ( 22 )

Was their sample selection based on convenience or purpose? Why do you think it was important for them to tell you that five families declined to be interviewed? There is actually a trick here, as the names were pulled randomly from a survey whose sample design was probabilistic. Why is this important to know? What can we say about the representativeness or the uniqueness of whatever findings are reported here?

Example 2 . In When Diversity Drops , Park ( 2013 ) examines the impact of decreasing campus diversity on the lives of college students. She does this through a case study of one student club, the InterVarsity Christian Fellowship (IVCF), at one university (“California University,” a pseudonym). Here is her description:

I supplemented participant observation with individual in-depth interviews with sixty IVCF associates, including thirty-four current students, eight former and current staff members, eleven alumni, and seven regional or national staff members. The racial/ethnic breakdown was twenty-five Asian Americans (41.6 percent), one Armenian (1.6 percent), twelve people who were black (20.0 percent), eight Latino/as (13.3 percent), three South Asian Americans (5.0 percent), and eleven people who were white (18.3 percent). Twenty-nine were men, and thirty-one were women. Looking back, I note that the higher number of Asian Americans reflected both the group’s racial/ethnic composition and my relative ease about approaching them for interviews. ( 156 )

How can you tell this is a convenience sample? What else do you note about the sample selection from this description?

Example 3. The last example is taken from an article published in the journal Research in Higher Education . Published articles tend to be more formal than books, at least when it comes to the presentation of qualitative research. In this article, Lawson ( 2021 ) is seeking to understand why female-identified college students drop out of majors that are dominated by male-identified students (e.g., engineering, computer science, music theory). Here is the entire relevant section of the article:

Method Participants Data were collected as part of a larger study designed to better understand the daily experiences of women in MDMs [male-dominated majors].…Participants included 120 students from a midsize, Midwestern University. This sample included 40 women and 40 men from MDMs—defined as any major where at least 2/3 of students are men at both the university and nationally—and 40 women from GNMs—defined as any may where 40–60% of students are women at both the university and nationally.… Procedure A multi-faceted approach was used to recruit participants; participants were sent targeted emails (obtained based on participants’ reported gender and major listings), campus-wide emails sent through the University’s Communication Center, flyers, and in-class presentations. Recruitment materials stated that the research focused on the daily experiences of college students, including classroom experiences, stressors, positive experiences, departmental contexts, and career aspirations. Interested participants were directed to email the study coordinator to verify eligibility (at least 18 years old, man/woman in MDM or woman in GNM, access to a smartphone). Sixteen interested individuals were not eligible for the study due to the gender/major combination. ( 482ff .)

What method of sample selection was used by Lawson? Why is it important to define “MDM” at the outset? How does this definition relate to sampling? Why were interested participants directed to the study coordinator to verify eligibility?

Final Words

I have found that students often find it difficult to be specific enough when defining and choosing their sample. It might help to think about your sample design and sample recruitment like a cookbook. You want all the details there so that someone else can pick up your study and conduct it as you intended. That person could be yourself, but this analogy might work better if you have someone else in mind. When I am writing down recipes, I often think of my sister and try to convey the details she would need to duplicate the dish. We share a grandmother whose recipes are full of handwritten notes in the margins, in spidery ink, that tell us what bowl to use when or where things could go wrong. Describe your sample clearly, convey the steps required accurately, and then add any other details that will help keep you on track and remind you why you have chosen to limit possible interviewees to those of a certain age or class or location. Imagine actually going out and getting your sample (making your dish). Do you have all the necessary details to get started?

Table 5.1. Sampling Type and Strategies

The Qualitative Worldview

Individuals engaged in qualitative research approach their projects from a different perspective than quantitative and rhetorical researchers. Even though all researchers share an interest in accurately reflecting social reality and in crafting an intellectual argument that is built on the foundations of valid data collection and observation, several assumptions are specific to qualitative research. Understanding these assumptions can help you better determine whether you need to use qualitative methods for the particular study in which you are interested.

Assumptions of Qualitative Research

Our knowledge of social reality is based on subjective interpretation. Qualitative researchers assume that due to our limited perception and our individual experiences, our understanding of social reality is necessarily subjective. Due to this, qualitative researchers reject the realist worldview that postulates an objective, measurable reality. Instead, reality is a social construction, given life through intersubjective agreement – that is, the contours of reality are defined by general agreement between humans in the society. Another way to think of this is that reality isn't completely objective – existing externally from humans, but subjective – existing in the interpretations of humans. Concepts such as love, democracy, and friendship are difficult to quantify, and are often the result of negotiated understandings between pairs or groups of people. Therefore, for qualitative researchers, it is important to understand how individuals and groups subjectively understand their experiences.

Subjectivity, in regards to qualitative research, manifests itself in two ways. On one hand, there is the recognition that the participants in the research have their own unique way of interpreting and understanding events and their own social actions. For example, a researcher studying leadership would recognize that research participants, whether they are CEOs or workers, coaches or players, preachers or congregation members, have their own unique perspective on leadership. In order to fully understand leadership, a qualitative researcher would need to consider all, or at least as many as possible, of the various subjective understandings of leadership.

On the other hand, the researcher recognizes that he or she is the primary data collection instrument, and her or his subjectivity affects the study. Rather than utilizing a survey, specifically designed to reduce bias and maintain objectivity, a qualitative researcher, whether through observation or interviewing, filters all of the data through his or her own understanding. In this way, a qualitative researcher must recognize his or her subjectivity regarding the collection and analysis of data.

Research proceeds inductively . Induction is the process of moving from a series of specific observations to a general conclusion or theory. Unlike quantitative research, which often proceeds deductively from a general premise or theory to specific examples, qualitative research, through the gathering of subjective interpretations, seeks to develop general understanding through the analysis of the collected data.

For example, it is unlikely that qualitative research will begin with a theory, such as Inoculation Theory (a theory concerning how people resist persuasion), and then through experimental or survey designs, seek to validate and support the theory. In fact, it is quite the opposite. Qualitative researchers, interested in how people resist persuasion, might begin by asking participants for accounts of times when they have successfully resisted persuasive attempts. Qualitative researchers deliberately avoid beginning with the conclusion. After collecting these individual accounts from participants, researchers analyze the data in order to identify situational rules that then facilitate understanding of social action.

The goal of qualitative research is understanding . Nineteenth century German philosopher Wilhelm Dilthey (2010), articulating the difference between the natural and the social sciences, stated that the former sought causes and effects while the latter sought verstehen . Simply put, verstehen means understanding. One of the founders of sociology, Max Weber, elaborated on Dilthey’s work and stated that the purpose and method of the social sciences should be verstehen . Weber (1962) believed that it was not possible to fully predict human social action. Therefore, rather than attempting to predict and control human behavior, qualitative social scientists should seek to understand social action. It is important to recognize that human social action varies immensely, and it would be difficult to identify social actions that are likely to be consistent from one person to the next and across a variety of circumstances. For example, humans would have a wide range of responses to an embrace from an acquaintance, an insult, slapstick humor, physical violence, or being ignored.

Researchers emphasize credibility, rather than validity/reliability . Many qualitative researchers use the word credibility rather than validity or reliability. This is not to say that qualitative researchers do not desire validity, but rather to recognize that currently validity and reliability are synonymous with the quantitative approach to research. The use of the term credibility is a deliberate choice and refers to the veracity and accuracy of the data collected. Essentially, qualitative researchers are creating an argument—an argument which claims that the conclusions derived from the qualitative research are an accurate reflection of social reality. For example, if a U.S. Senator were giving a speech, we might ask whether or not the speaker is credible and whether or not the information presented in the speech is credible. In much the same way, we might evaluate qualitative research by asking whether or not the researcher and the argument presented in the research are credible.

Knowledge is created through intersubjective agreement . Qualitative researchers believe that knowledge is built through intersubjective agreement. For example, a researcher investigating friendship development among college students realizes that his or her study is only one piece of the puzzle and that a similar study would likely reveal new elements or focus on different characteristics of friendship. It is through the sharing of this body of knowledge that understanding is built. In fact, it is the very process of how research participants collectively construct multiple understandings in which the researcher is interested. Participants define and construct understanding intersubjectively and researchers document this process, enter their findings into the public record through publication, and then jointly construct meaning with other researchers, other participants, and other publications. Participants then become co-researchers with the researcher. This process results in an intersubjective, rather than an objective, understanding of the social world.

The social setting or context is an important element in understanding any communication interaction . Qualitative researchers believe that context is integral to understanding communication. Research often takes place within the natural setting of the participants. For example, a researcher conducting an ethnography of college wrestling would observe the participants at practice, meetings, and competitions, etc.—paying careful attention to the characteristics of the setting. So, why is the context so important? In the case of a wrestling ethnography, many contextual factors aid our understanding of the group. Is the coach new or a seasoned veteran? Does the program have a stellar reputation or is it struggling for respectability? Does the team have 15 members or 45? Does the program have a state-of-the-art practice facility? All of these distinctions can help facilitate the researcher’s understanding of a group in a way that differs from quantitative research involving a survey of 200 wrestlers.

The values of the researcher cannot be completely separated from the research . Qualitative research is a subjective endeavor. A researcher relies on his or her ability to accurately interpret the available data in order to make a valid argument regarding the phenomena under investigation. Because the researcher is the data collection instrument and the values of the researcher are present during the interpretation, extra effort must be made to ensure that the biases of the researcher do not diminish the quality of the interpretation.

In life, it is obvious that people often see what they want to see. If a politician is giving a speech, it is likely that supporters will interpret elements of the speech in a manner that is entirely different from the way that detractors interpret those same elements. Because of this, it is important that researchers recognize and acknowledge the role that their values play in the interpretation of the data and to ensure that their conclusions are built on fully substantiated and supported claims.

In summary, qualitative assumptions include:

Knowledge of social reality is based on subjective interpretation;
Research proceeds inductively;
The goal of qualitative research is understanding;
Researchers emphasize credibility;
Knowledge is created through intersubjective agreement;
The social setting or context is an important element in understanding any communication interaction; and
The values of the researcher cannot be completely separated from the research.

These assumptions represent the worldview shared by qualitative researchers. Ultimately, decisions regarding methodology rest on the types of questions that the researcher wants to answer. If your goal is to understand a particular communication phenomenon in depth, qualitative methods are a good research choice for you.

The Traditions of Qualitative Research

While quantitative research has the firmly established tradition of the scientific method, qualitative research locates its roots in a variety of philosophical strains. Cultural studies, critical theory, ethnomethodology, and others have all contributed to the theoretical traditions of qualitative methodology. However, the three traditions to be discussed here are hermeneutics, phenomenology, and symbolic interactionism.

Hermeneutics

According to Schwandt (2001), hermeneutics refers “to the art, theory, and philosophy of interpreting the meaning of an object” (p. 115). The “object” under examination can take a variety of forms: a Black-Eyed Peas song, a conversation between friends, a commercial for the latest iPhone, or a Presidential State of the Union Address. Hermeneutists call these objects “texts,” and they serve as the data for a hermeneutic study. The process of interpreting meaning makes hermeneutic analysis so fundamental to qualitative research. This process goes beyond the translation of a text and involves an effort to interpret the text. We are engaged in the process of interpretation every day. For example, lawyers, judges, and politicians are constantly in the process of interpreting laws. An ongoing discussion in the United States is whether or not the Bill of Rights is a “living, breathing document,” thus necessitating new interpretation, or is an unchanging document that means the same today as it did upon its ratification in 1791.

Hermeneutics, or interpretation, as a scholarly practice traces its roots to ancient Greek society. However, it is in the area of biblical scholarship that the more recent foundation of hermeneutics rests. Biblical scholars must not only translate ancient religious documents, but must interpret them for a new time period. For example, during the Protestant Reformation, new interpretations of biblical passages strengthened the Protestant cause while shifting away from Roman Catholic interpretations of the text. This process of interpretation is important because it acknowledges that texts must be reevaluated and re-interpreted in order to ascertain applicability and relevance.

Modern hermeneutics, as developed by Dilthey (2010), Gadamer (1976), and Ricoeur (1981), moved hermeneutic analysis beyond the study of ancient texts to include the range of “texts” that we consider for analysis today. Texts can include a near limitless range of social actions—transcripts from an interview, a movie, Congressional proceedings, a commercial, etc. In order to properly understand a text, the interpreter must have an understanding of not only the text, but of the cultural and historical epoch from which it originates. What do we know about the whole of the text? What do we know about the author or authors of the text? What do we know about the time period in which the text was created? Remember, the charge for a hermeneutic researcher is to interpret the text, and the goal of the hermeneutic researcher is understanding. Scholars in this tradition believe that one cannot fully understand a text until one understands the range of forces involved in the creation of the text. In this tradition, the emphasis is on the relationship among the text, author, context, and the researcher.

Phenomenology

While the centrality of interpretation in hermeneutic scholarship marks an approach that is clearly divergent from quantitative research with its scientific method roots, it is with phenomenology that we see a deliberate rejection of quantitative social science and its focus on an objective, measurable reality. Phenomenologists deny the existence of a reality that exists independent of our perceptions.

Phenomenology originated with the work of Edmund Husserl (1990) as he sought to develop a way of objectively studying subjective experiences. Husserl focused on understanding events or phenomena by understanding how people consciously experience those events or phenomena. Husserl’s form of phenomenology, known as transcendental phenomenology , included carefully cataloguing all of the attributes of an item, such as democracy, and then bracketing, or setting aside, those attributes of democracy that are completely subjective—byproducts of culture and the perceptions of the person conducting the analysis. Therefore, if a researcher wanted to understand a concept such as democracy , he or she would identify all of the essential characteristics of democracy. Husserl would then advocate that those items on our list of essential characteristics of democracy that are culturally situated (for example, there are aspects of current U.S. democracy that differ from how other countries define democracy) be bracketed or set aside. By removing our cultural assumptions from the list through the process of bracketing, we are left with those items that seem universally, rather than contextually, valid—the essential characteristics of democracy.

While Husserl was interested in bracketing out the culturally based characteristics of a phenomenon, his student, Alfred Schutz (1967), found that the cultural variations that manifest in individual interpretation of experiences are the most interesting facets of the phenomenon. Therefore, Schutz’s social phenomenology emphasizes the subjective interpretation of everyday experiences. According to Schutz, these types of localized understandings are represented by people’s values, beliefs, etc. He called these typifications. In summary, while Husserl encouraged us to set aside our biases, Schutz asked us to consider how and why our biases develop.

Phenomenology focuses on intersubjectivity . One way to understand the phenomenological concept of intersubjectivity is to imagine a group of researchers independently studying a previously undiscovered tropical island. One researcher, who is able to study the island via helicopter, is able to chronicle those island characteristics viewable from the air. Another researcher studies the island from a submarine and is able to describe the island characteristics viewable from this undersea vantage point. Finally, a third researcher is able to walk around the island and study it from within, and is able to see the island from a different perspective than either the aerial or nautical researcher. When the three researchers get together to share their findings, they identify those areas where their data overlaps—thereby revealing the essential characteristics of the island and achieving an intersubjective understanding. This does not mean that the observations unique to each researcher are invalid, just that it is never fully possible for others to experience the world in exactly the same manner as someone else and that the process of understanding a phenomenon is a process that is both ongoing and contingent. In distinguishing between the phenomenological approaches of Husserl and Schutz, Husserl would focus on where the researchers overlap, while Schutz would be more interested in the unique observations of each of the researchers.

Stewart and Mickunas (1990), after noting the lack of consensus in defining phenomenology, stated, “one can characterize phenomenological philosophy as centering on the following basic themes: a return to the traditional tasks of philosophy, the search for a philosophy without presuppositions, the intentionality of consciousness, and the refusal of the subject-object dichotomy” (p. 5). In summary, phenomenology contributes to qualitative research with its recognition of subjective experiences and its goal of intersubjective meaning construction. Quantitative researchers use sophisticated surveys as measuring devices. In qualitative research, the researcher is the data collection device.

Symbolic Interactionism

The third tradition influencing modern qualitative scholarship is Symbolic Interactionism. The aim for researchers in this tradition is to ascertain how meaning develops. Humans use symbols (words, phrases, images, nonverbal gestures, etc.) to interact with one another. How is it that people are able to agree on common understandings for these symbols? According to Symbolic Interactionists like Mead and Blumer (1986), the cultural meanings that people attach to symbols develop through their interactions with members of their social network, mediated images in their environment, and social context in a larger sense. Through these shared symbolic understandings, people are able to make sense and interpret their experiences.

Symbolic Interactionism focuses on the interplay among mind, self, and society. Mind includes individual human thoughts, while self considers interaction with others. Society provides the context in which meaning is made possible. What each know, their stock of knowledge, is shaped by their experiences and their interactions within a societal network, and knowledge, in turn, impacts the societal network.

Even though people often successfully share meanings, it is important to remember that meanings are constantly under negotiation. While most might share a collective interpretation of the essential characteristics of a dog, the meanings of other terms, like liberal or conservative , are constantly under negotiation. Your own political orientation, the political orientation of your social group, and the political orientation of your family members all shape your understanding of these terms. Additionally, other factors such as how distinct media outlets define liberal or conservative or how you feel about specific politicians influence and guide how you conceptualize these terms. Over the course of the evolution of Symbolic Interactionism, key components developed to further explain the results of interaction among social groups. Significant symbols and significant others are two examples of essential characteristics of this approach to human social action. Significant symbols are those, that when used, elicit understanding among the social group. For example, others might interpret the use of an image of an eagle or an American flag pin on your lapel as representative of your patriotism. The term significant others refers to those whom most shape a person’s understanding of cultural symbols.

Consider a concept such as corporate branding—where a corporation hopes to build a specific connection between a symbol representing their company and their target audience. For example, Nike wants customers and athletes to immediately connect the swoosh on their logo with quality or performance. However, it is important to remember the roles social groups play in people’s interpretation of significant symbols like the Nike swoosh. Some, due to Nike’s lawsuits, might associate the swoosh with unfair labor practices or poor working conditions. This example serves to further demonstrate that cultural understandings are always contingent.

If one considers that these three philosophical traditions represent the foundation of qualitative research, the individual pillars of the foundation reveal themselves. From hermeneutics comes the centrality of interpretation and the identification of texts (in all their myriad forms) as fundamental elements of scholarly analysis. From phenomenology comes the recognition that everything a person understands about reality is filtered through her or his own individual perceptions and that we should strive for intersubjective understandings of reality. Finally, from symbolic interactionism comes the realization that how people experience reality is shaped by the shared symbolic meanings that arise from their social network, cultural group, or philosophical standpoint. All three of these foundations reject a realist ontology; that is, the idea that there is a single objective reality that we can know independent of our subjective interpretation. Elements from nearly all of the assumptions of qualitative research, interpretation, textual artifacts, subjective understanding, and contextual shaping can be traced back to these pillars.

Attributes of Qualitative Research

Before proceeding to an in-depth examination of specific steps for initiating and conducting a qualitative research project, there are a few general attributes and elements of qualitative research to consider. In this section, the authors discuss the primacy of observation as an essential attribute for a qualitative researcher, the types of questions posed by researchers, the different forms of data common to qualitative research, the varieties of sampling, and ways to improve the accuracy of your qualitative findings.

Observation

Having established the relationship between subjectivity and qualitative research and having established that the qualitative researcher, unlike the quantitative researcher, is the primary data collection instrument, it is necessary to consider one of the primary means of data collection in qualitative research: observation. It is common in qualitative research for researchers to immerse themselves in the social environment under investigation. People naturally engage in the process of observation every day—seeing what the weather is like, paying attention to what friends or professors are saying, or attending a meeting with a campus organization. However, systematic, scholarly observation differs from casual observation.

One way to think of how qualitative observation differs from casual observation is to consider playing a game of Texas Hold ‘Em poker. When you get together and play with your friends for skittles or peanuts, you may or may not pay enough attention to see if your opponents are bluffing. Now imagine that you are playing Texas Hold ‘Em on ESPN for ten million dollars. Under those circumstances it is critical that players are able to read the behaviors of others and also have a high awareness of their own behaviors. This is similar to the characteristics of a scholarly observer. When conducting observations for research purposes, researchers need to be able to sort through, process, and accurately capture the variety of stimuli occurring simultaneously in the environment. Additionally, researchers need to be cognizant of their own interpersonal behaviors and consider how they are impacting those in the environment.

Observation plays a very specific role in ethnography, which is when the researcher immerses him or herself into the culture or group being investigated. It also takes a keen eye for observation when conducting focus groups or interviews. Oftentimes, during the early stages of a research project, the researcher might rely on observation to get a preliminary sense of the communication context of the research participants. In general, the observation continuum looks like this:

While the explanation of each type of observation is fairly straightforward, it is worth exploring how each differs from the other. When a researcher takes on the role of complete observer , he or she is usually not already a member of the group under observation. When we study a group as an outsider, we call this adopting an etic perspective . Simply put, it would be difficult to carry out our day-to-day responsibilities as a group member and focus extensively on capturing detailed notes of our observations of the group. Consider a student on the campus of who is having difficulty understanding why the student organization in which he or she is a member (e.g., the Chess Club) is having trouble functioning effectively. This student might identify successful student organizations with the intent of sitting in as an observer in order to try to determine what those groups do that contributes to their success. The student might select a public relations student organization and attend several meetings, not with the intention of joining, but with the intention of identifying the social actions that help make the PR group a successful organization. By carefully and successfully documenting the procedures and activities of the public relations organization, the observer might be able to integrate these behaviors into her or his own organization.

On the other side of the continuum is the complete participant , someone who is already a member of the organization that he or she wants to study. Imagine again that you are the president of the Chess Club, and you want to improve the functioning of your student organization. Because you are the president and have all of the responsibilities associated with that position, it would be very difficult to take time off from your regular duties to take extensive field notes about the Chess Club’s organizational procedures. When you study an organization from an insider’s perspective, as you are in this example, it is called taking an emic perspective . In this case, the complete participant wants to carry out his or her routine responsibilities and then, after the meeting, attempt to write detailed notes describing the activities and experiences of the meeting.

Before discussing the two perspectives that mark the middle areas of the continuum, it is necessary to highlight three salient points regarding differences between taking an etic perspective or an emic perspective.

Although complete observers may bring a fresh set of eyes and be able to focus exclusively on the act of observing, they may find that access is limited and acceptance of their presence is not guaranteed.
Although complete participants have the advantage of understanding the history, rituals, and jargon of the organization, their pre-existing biases may greatly cloud their interpretation of events.
Both types of observers must pay considerable attention to the concept of trust—complete observers, if the participants are aware of his or her presence, may have difficulty gaining the trust of the group and getting them to behave as they naturally would (consider the Hawthorne effect that states that people behave artificially when they know that they are being observed). Complete participants may begin with the trust of the participants, but will likely find themselves navigating a difficult path, particularly if they become aware of behaviors and activities that portray some members of the group in a negative light.

So what is the difference between an observer-as-participant and a participant-as-observer? A few years ago, a colleague was doing an ethnographic study of the emergency room in a large hospital. She had no training in the medical profession. She received permission to conduct observations and interviews over the course of several months. She began the study as a complete observer. However, over the course of her ethnographic study, she had multiple experiences that caused her to shift from complete observer to an observer-as-participant role. On one occasion, due to shortages on the staff, she was asked to hold a patient’s leg in place in order for the doctor to attempt to set the broken leg prior to putting it in a cast. Needless to say, the colleague was not expecting to play any kind of active role in the hospital emergency room other than active observation. So, an observer as participant is when an individual maintains the primary role of observation, but on occasion is asked to participate. Another example is when other professors visit your classroom in order to observe and evaluate your professor or teaching assistant. In this case the primary role is the observation, but in some circumstances the observers find themselves participating in class activities such as discussion or role-playing. Now imagine that you are a nurse in an emergency room who has been asked by administration to document communication patterns in the emergency room and recommend improvements. The participant-as-observer still has the primary responsibility of being a nurse in the emergency room, but he or she might also have specific time in meetings or every hour or so to document and reflect on observations. In this way she/he fulfills the primary role of nurse, but also is able to allocate time to observation and analysis on the side.

It is important to determine which observation role is best suited for your research. You must consider whether you are an insider or an outsider for the organization. You must then determine if you will be taking a covert (undercover) role or a more overt (out in the open) role. Regardless of the type of observation in which the researcher engages, specific and systematic expectations for data gathering and analysis govern your research. The role that you take impacts the type of data that you are able to collect.

Research Questions, Seldom Hypotheses

Qualitative research proceeds inductively—beginning with a specific group or a specific question and then gathering data in order to lead to a general explanation or perhaps even a theory. Qualitative researchers are seldom engaged in testing existing theory in the same sense that quantitative researchers are. Therefore, qualitative research relies on broad research questions asking “how” or “what” rather than testable hypotheses that make clear predictions. Consider the following sample research questions from three different qualitative studies.

RQ1: In what ways are employees’ constructions of mistreatment in the workplace muted or privileged? RQ2: What are the processes that silence or encourage discussion of mistreatment by employees? (Meares, Oetzel, Torres, Derkacs, & Ginossar, 2004, p. 9)

RQ1: What are the components of high self-esteem for the women in the study? RQ2: How do they say they manage the construction and maintenance of high self-esteem in their lives? (DeFrancisco & Chatham-Carpenter, 2000, p. 77)

RQ1: How do disabled organizational members experience and negotiate organizational assimilation? (Cohen & Avanzino, 2010, p. 278)

While these three qualitative studies clearly follow the pattern of asking “how” or “what” questions, it is important to remember that, in general, there is more flexibility regarding the normative presentation of qualitative research. In some cases, such as the research of Wong and Goodwin (2009), because there was already an existing body of evidence on which to base their research, they proffered hypotheses with their qualitative study on marital satisfaction. Their hypotheses included:

H1: Bonding and the interactions between the spouses would be more important in individuals’ evaluation of marital relationships in modernized societies where independence is valued. H2: Relationships with other family members would be more important in the evaluation of marital relationships in societies where interdependence is valued. H3: Financial security would be a more important factor in marital satisfaction in less modernized settings. (Wong & Goodwin, 2009, p. 1014)

Wong and Goodwin gathered their data through in-depth qualitative interviews, but due to the large body of existing scholarship on marital satisfaction, they were confident in presenting hypotheses. However, it is necessary to point out that while hypotheses in qualitative research may exist, they are rare.

To further demonstrate the variation in qualitative research, some research studies may eschew research questions altogether. In these cases there is often a research purpose stated prior to describing the methods, but this purpose may take the form of a tentative statement rather than a research question. For example, Weinstein (2007) used field observations, interviews, and written documents to explore how inner city youths used writing (poetry, lyrics, etc.) to negotiate gender and sexual identity. She states, “I hope to contribute to the ongoing work done by researchers on adolescents’ and young adults’ uses of written and oral composition to find workable identities in the midst of multiple and shifting social contexts” (Weinstein, 2007, p. 30). In another case, Hundley and Shyles (2010) studied teenagers’ perceptions of technology and, rather than asking a research question, they simply stated, “this research continues the line of inquiry by listening to teenagers and gaining a perspective on what they think about emerging digital technologies and the functions various devices serve in their lives” (p. 418).

Thus, variation exists regarding the presentation of research goals in qualitative research. Goals may range from general purpose statements to specific research questions. Although hypotheses are rare, and research questions and research statements are more typical in qualitative research, one must remember that regardless of the approach, the methodology must be in the service of the overall research purpose.

Types of Data in Qualitative Research

The data for qualitative research takes many forms. Interviews and focus groups provide responses to carefully designed questions. Observation and ethnography provide detailed notes of the research setting. Participant responses or observation events may range from brief, specific responses to detailed, descriptive stories. A truly extensive ethnography, for example, might combine detailed field notes, descriptive stories, and specific responses to field interview questions. Stories, field notes, and interview/focus group responses are all valid forms of qualitative research data.

Stories. Some qualitative techniques, such as narrative analysis, seek to elicit stories from the research participants, while in other cases, like interviews or focus groups, stories may arise naturally over the course of the research. Fisher (1984) said that it is natural for humans to communicate using stories. It is not hard to imagine the range of situations in which stories may either be elicited or arise spontaneously. Imagine an interview question where the researcher asks, “tell me about a time when you experienced conflict with a co-worker?” Or, consider doing research on U.S. wedding rehearsal dinner rituals. One can imagine the richness of the stories naturally arising in that setting. Qualitative research offers details and descriptions that are richer and more in-depth than quantitative research—the collecting of stories is a perfect way to capture the richness of our social activity.

Field notes . Whether one is observing a focus group, an emergency room, or the proceedings of a student organization meeting, field notes are a necessary tool for capturing the social activity as it unfolds. If the researcher is conducting an ethnography, and is involved in the act of cultural immersion, the observational field notes provide the data for the study. Field notes are a record of the activities of the participants of a study. The field notes are a written log of the researcher’s observations. Perhaps you like to go to the mall and watch the people as they come and go. Even with a good memory it is doubtful that you would be able to remember more than one or two interesting points if asked about it the next day. It is for this reason that detailed field notes, which describe the setting and participants in real time, are the best way of documenting a researcher’s time in the social environment.

For an ethnographer, the field notes are the data that allow the researcher to develop a credible argument in the final report. For a researcher observing a focus group, field notes enable the researcher to note the physical setting of the focus group or to chart how interaction proceeds over the course of the focus group. One of the most common ways to set up your field notes is to divide your page from top to bottom down the middle. On the left side of the page, the researcher should include specific observations, while on the right side of the page, the researcher should include tentative questions or concepts or future ideas. It is always important to also include the date, time, and location of the observation—and perhaps even a map of the research setting.

A good student activity is to select a location—the union, a class, a restaurant, etc.—and practice taking your own field notes. Just spend 30 minutes observing the location and see how accurately you are able to capture the setting and the ongoing interaction among the participants.

Consider the following example of field notes from observation of a graduate class:

In-depth interviews & focus groups. Quite a bit of qualitative data is neither collected using field notes nor involves a detailed story. Much of the data follows the natural give and take of everyday conversation. Whenever possible, an audio recorder is a useful tool for capturing participant responses to interview questions. Open-ended responses that are not as extensive as a detailed story are very common in qualitative data. If brief, closed-ended responses are the type of data you need, you probably want to consider a quantitative survey. However, if you are interested in understanding how and why participants engage in certain activities or adopt certain values, qualitative interviewing will likely provide you with the type of data you need.

Stories, field notes, interview and focus group responses, and field notes are three common forms of data in qualitative research. All researchers are interested in producing the most accurate and valid conclusions from their data. Prior to and during the research process, there are choices the researcher can make to strengthen his or her results. The choices are rooted in a process called triangulation , which means you may choose multiple ways to collect data or multiple methods to explore the answer to your research question/s (Denzin, 2006).

Sampling Characteristics

Selecting the participants for a qualitative study often relies on a very deliberate process. Whereas quantitative research improves its accuracy through random sampling that is representative of the population to which it seeks to extend its results, qualitative research, with its emphasis on context and focus on understanding, will generally use a purposive non-random sampling strategy, rather than a random, sampling process. Once again, the fact that qualitative research proceeds inductively (starting with a specific group or setting), rather than deductively, reinforces the necessity of purposive sampling practices. If a researcher wants to observe and understand the communication practices at a large retail store, he or she would purposely select a retail store as the setting for the study. According to Schwandt (2001), qualitative samples “are chosen not for their representativeness but for their relevance to the research question, analytical framework, and explanation or account being developed in the research” (p. 232).

Another characteristic of qualitative research samples concerns sample size. Because qualitative research focuses on understanding rather than generalizations, the size of the sample is typically much smaller than a sample for a quantitative survey. For example, consider the amount of time it takes to set up, conduct, and transcribe ten average length interviews compared to an on-line survey that automatically compiles the data and uploads it into a statistical program. Also, if a researcher wants to study the large retail store with many departments, it is easy to imagine the amount of time necessary to complete a thorough ethnography. Even if the researcher only chooses to focus on a single department within a retail store, observing different shifts and different workers would take a considerable investment of time. Qualitative samples are both purposefully selected, to meet the research objective, and deliberately small, to be manageable for the researcher.

The Importance of Triangulation

All researchers seek to produce an accurate or credible account of the phenomenon under investigation. Researchers have a variety of options to improve the credibility of their studies. Triangulation is the process of using two or more types of evidence to provide a more clear and accurate interpretation of the data. Triangulation takes multiple forms from researcher triangulation to data triangulation. The basic premise behind triangulation is that if the multiple data sources converge, validity/credibility has been enhanced. We will briefly discuss several of the more popular forms of triangulation.

Multiple methodologies . This type of triangulation involves the researcher or researchers using multiple techniques to gather the data. Suppose that a researcher wants to study the communication practices of a local restaurant. One of the ways that the researcher might collect data is by interviewing the employees of the restaurant. The results of the interviews might paint a very accurate picture of restaurant activities. However, the researcher might also want to observe the restaurant as the social actors engage in their day-to-day activities. The idea behind triangulation is that the data collected from the interviews and the data collected from the observations of the restaurant, when combined, paint a more complete and accurate picture of the restaurant than either one of the methods alone. Of course, a researcher could also include a third method, focus groups, in an effort to corroborate the conclusions drawn from the interviews and the observations. Using multiple methodologies for triangulation does not have to be limited to qualitative methods. For example, it is very common for a researcher to conduct interviews in order to gain a basic understanding of a concept and then use that information to create quantitative surveys to distribute to a larger sample. The goal is to create the most credible interpretation of the data, and triangulation of methods is one way to improve the accuracy of a study.

Multiple researchers . This type of triangulation involves multiple researchers gathering data on the same subject. In the example regarding the ethnographic study of a retail establishment, it is easy to see how a research team would have an easier time collecting observations than an individual researcher would. It is not just that multiple researchers can spread out and cover more ground, thereby creating a more fully realized picture of the organization, but also that multiple researchers increase the chance of accurately capturing all of the activities occurring when viewing the same event. Think of all of the activities going on during a typical organizational meeting—multiple researchers would be able to capture a fuller spectrum of social activity in less time than just one researcher. Additionally, multiple researchers contribute to the development of intersubjective understanding. Multiple researchers can mitigate some of the biases of each researcher, helping to avoid reaching a premature conclusion or being overly subjective.

There are other forms of triangulation, such as multiple research settings (observing at different times or in different places) or multiple disciplinary approaches (one observer versed in organizational communication and another versed in organizational behavior). These forms of triangulation are not mutually exclusive; researchers can combine, and often do combine, a variety of these approaches.

General Strengths and Weaknesses of Qualitative Research

Perhaps the greatest strength of qualitative research is the sheer amount of depth it can bring to our understanding of social action. Qualitative data can capture many of the complexities of human interaction that are unable to be uncovered through a quantitative survey. Because it proceeds inductively, it is both strong at discovering new phenomena and at generating theories of human behavior. Qualitative data collection often occurs in the participants’ natural environment, improving the ecological validity of the study. As long as the researchers are able to overcome the Hawthorne effect, the data collected should reflect actual behaviors in ways that self-reported surveys or laboratory studies are unable to reflect. Finally, qualitative researchers allow the participants to tell their own stories rather than reducing the stories to numbers.

Qualitative research also has obvious weaknesses because the researcher is the data collection instrument, so the quality of the data is only as good as the researcher. Has the researcher collected enough data to paint an accurate picture? Has the researcher attempted to minimize individual bias to the fullest extent? These concerns represent just a few of the problems that could result from the subjective nature of qualitative research. Qualitative research is not good for generalizing results to a larger population and it is not good for examining causal relationships. There is also a considerable investment of time associated with this type of research.

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The Oxford Handbook of Qualitative Research (2nd edn)

Patricia Leavy Independent Scholar Kennebunk, ME, USA

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The Oxford Handbook of Qualitative Research, second edition, presents a comprehensive retrospective and prospective review of the field of qualitative research. Original, accessible chapters written by interdisciplinary leaders in the field make this a critical reference work. Filled with robust examples from real-world research; ample discussion of the historical, theoretical, and methodological foundations of the field; and coverage of key issues including data collection, interpretation, representation, assessment, and teaching, this handbook aims to be a valuable text for students, professors, and researchers. This newly revised and expanded edition features up-to-date examples and topics, including seven new chapters on duoethnography, team research, writing ethnographically, creative approaches to writing, writing for performance, writing for the public, and teaching qualitative research.

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iman permana

Andzar Azmi

Perkembangan sektor parawisata halal di Indonesia terus berkembang, terkhusus di Jawa Barat. Hal tersebut berdampak pada industry perhotelan syariah,. Semakin maraknya pariwisata halal, masyarakat cenderung memilih hotel syariah sebagai alternative untuk menginap. Ada beberapa factor yang mempengaruhi keputusan konsumen dalam pengambilan keputusan untuk menginap, diantaranya adalah harga, fasilitas dan kualitas pelayanan yang diberikan oleh perusahaan hotel. Tujuan penelitian ini adalah untuk mengetahui: (1) pengaruh tingkat harga terhadap keputusan konsumen menginap di Narapati Indah Boutique Hotel Syariah Bandung secara parsial, (2) pengaruh fasilitas terhadap keputusan konsumen menginap di Narapati Indah Boutique Hotel Syariah Bandung secara parsial, (3) pengaruh kualitas pelayanan terhadap keputusan konsumen menginap di Narapati Indah Boutique Hotel Syariah Bandung secara parsial, (4) pengaruh tingkat harga, fasilitas dan kualitas pelayanan terhadap keputusan konsumen menginap d...

JELAJAH: Journal of Tourism and Hospitality

Riani Ishak

Cleanliness and sanitation are the most important things that must be considered to ensure that the products served to customers are safe and free from various viruses and bacteria. These issues, Hygiene Sanitation, and promotion must be considered by food and beverage entrepreneurs to increase the interest of buyers. The purpose of this study was to determine whether or not Hygiene Sanitation and Promotion influenced the purchase decisions at Favela Sunset Cafe Paledang, Bogor. The research method used is quantitative research. The data analysis used in this study consisted of multiple linear regression analysis with SPSS V 20.0. The result of the study concluded that the Effect of Hygiene Sanitation and Promotion on Purchase Decisions at Favela Sunset Cafe Paledang Bogor had a positive and significant influence.

Maribel Pili

Bertrand Alexander J Lesaca

Nada Nilam Suri

The research objectives were to determine students 'perceptions about preserving the school environment and to find out students' perceptions of school regulations on preserving the school environment. This research uses a quantitative approach with quantitative descriptive. The population in this study were all students, so the sample used by the researcher was class XI, amounting to 406 students with a sample of 201 students. Based on the results of this study, it was found that 1) students 'perceptions of the preservation of the school environment from outside perception factors stated strongly agree with a percentage of 37.44% and the perception factor from within agreed with a percentage of 41.48%, 2) students' perceptions of school regulations on environmental preservation of cleanliness school (K3) agreed with a percentage of 51.32% and environmental preservation agreed with a percentage of 41.48%. Tujuan penelitian yaitu untuk mengetahui persepsi siswa ter...

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Part 1 (Chapters 1
Chapter 1: Why and How to Do Qualitative Research; Chapter 2: The Qualitative-Quantitative Distinction; Chapter 3: Theoretical Frameworks; Chapter 4: Methods and Data in Qualitative Research; Chapter 5: Subjectivity, Identity, and Texts in Qualitative Research; Part 2 (Chapters 6 - 13): Research Design. Chapter 6: Formulating a Research ...
(PDF) CHAPTER 5 SUMMARY, CONCLUSIONS, IMPLICATIONS AND ...
The conclusions are as stated below: i. Students' use of language in the oral sessions depicted their beliefs and values. based on their intentions. The oral sessions prompted the students to be ...
Chapter 1. Introduction
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 ...
What Is Qualitative Research?
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 ...
PDF Analyzing and Interpreting Findings
Qualitative research begins with questions, and its ultimate purpose is learning. To inform ... presents what an analysis chapter might look like. By using the example carried throughout this book, we analyze and interpret the findings ... Figure 5.1 gives some idea of how such a tool can be developed. A sample completed
Chapter 5. Sampling
Sampling in qualitative research has different purposes and goals than sampling in quantitative research. Sampling in both allows you to say something of interest about a population without having to include the entire population in your sample. We begin this chapter with the case of a population of interest composed of actual people.
Chapter Five: Qualitative Methods (Part 1)
Chapter Five: Qualitative Methods (Part 1) Every day you are confronted with the need to understand research methodology. In your work life, you are asked to compile and process data. Whether you are researching leadership techniques or analyzing sales statistics, you must be able to interpret the data you encounter.
The Oxford Handbook of Qualitative Research
Abstract. The Oxford Handbook of Qualitative Research, second edition, presents a comprehensive retrospective and prospective review of the field of qualitative research. Original, accessible chapters written by interdisciplinary leaders in the field make this a critical reference work. Filled with robust examples from real-world research ...
The nature of qualitative research (Chapter 1)
This chapter presents an overview of qualitative research and its place in information work from a practical perspective. To achieve this we work through some definitions and a touch of theory, but this discussion is tempered with practical examples of research that should enhance your understanding of theoretical perspectives.
PDF CHAPTER I: INTRODUCTION
CHAPTER I: INTRODUCTION. 1. The purpose of this qualitative grounded theory study was to identify what motivates. women to stay in or return to science, technology, engineering, and math professions. (STEM), leading to a motivation model. As illustrated in the literature review, research has. abbreviations. introduce introduce you can use Once ...
PDF CHAPTER 1 THE PROBLEM AND ITS BACKGROUND
It shows that on the pre-test majority of the. respondents had a low range score in Endurance Dimension of AQ® (49 or. 27.07%) and the rest got a below average score (61 or 33.70%), 47 or 25.97%. got an average score, 19 or 10.48% got an above average score and 5 or 2.76%. got a high score.
PDF Chapter 1 Qualitative Research: An Overview
1 Chapter 1 Qualitative Research: An Overview Abstract. Qualitative research is one of the most commonly used types of research and methodology in the social sciences. Unfortunately, qualitative research is com- ... 5 For example, a qualitative research can ask the following question: "How can institutional change .
PDF CHAPTER 5: QUALITATIVE RESEARCH
5.2 PHASES OF QUALITATIVE DATA COLLECTING. The phases of the qualitative data collecting included the following: Phase 1: Pre-test the semi-structured interview schedule with a purposively chosen focus group that is not part of the main research investigation. Phase 2: Pre-test the semi-structured interview schedule with a purposively chosen ...
PDF CHAPTER V: DISCUSSION
Dissertation Chapter 5 Sample. be research. CHAPTER V: DISCUSSION be. The purpose of this qualitative grounded theory study was to identify what motivates. Outline the organization. women to stay in or return to STEM professions, leading to a model of motivation. This.
PDF Chapter 5 Analysis and interpretation of the qualitative research 5.1
This chapter outlines the procedure to be followed in the qualitative research. This study is an empirical investigation into whether school principals who lack effective managerial and leadership skills are partly responsible for the continuous low matriculation pass rates in the Eastern Cape Province.
RESEARCH-PAPER-CHAPTER-1-5 (1)
RESEARCH-PAPER-CHAPTER-1-5 (1) Polledo, Cyrish Kiel DP. study and definition of terms that will help the researchers to introduce and formulate the research. face to face classes into online learning. This research context compels students to experience new. systems implemented learning modalities.
PDF DISSERTATION Chapters 1-5 Section Rubric
Dissertation Chapter 1 - 5 Sections Rubric - Version 1 May 1, 2019. • If small numbers are grouped with large numbers in a comparison, use numerals (e.g., 7, 8, 10, and 13 trials); but, do not do this when numbers are used for different purposes (e.g., 10 items on each of four surveys).
Research Paper Sample Chapter 1 To 5
Research Paper Sample Chapter 1 to 5 - Free download as PDF File (.pdf), Text File (.txt) or read online for free. research paper sample chapter 1 to 5
Chapter 5
This chapter provides a detailed overview of the valuable insights gained from studying the analysis of qualitative data collected during the research study. By employing qualitative methods such as interviews, observations, and analysis, this research aimed to understand the experiences and coping mechanisms of adopted students.
(DOC) Chapter 1-5 final research paper
This research uses a quantitative approach with quantitative descriptive. The population in this study were all students, so the sample used by the researcher was class XI, amounting to 406 students with a sample of 201 students. Based on the results of this study, it was found that 1) students 'perceptions of the preservation of the school ...
Chapter 1 qualitative research
A sample of chapter 1 of a qualitative research for grade 11 students chapter introduction background of the study language in the educational system has made. Skip to document. University; ... LP-Nov.23,2018- RW - Practical research 1 Qualitative Research; BIO1 11 12 Q1 0204 FD - The study of cells is vital to know about other fields ...
Qualitative Research Sample Chapter 1-3
Qualitative Research Sample Chapter 1-3 - Free download as Word Doc (.doc / .docx), PDF File (.pdf), Text File (.txt) or read online for free. Sample for Qualitative research, 2019