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The Essential Guide to Doing Your Research Project

Student resources, chapter 8: understanding methodologies.

What Is Best: Quantitative, Qualitative or Mixed Approaches?

Dr Zina O'Leary discusses whether qualitative, quantitative, or mixed methods are best. Each approach has its benefits and drawbacks. The best approach is whichever method answers the research question with credibility.

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Chapter 8: Complex Research Designs

In Chapter 1 we briefly described a study conducted by Simone Schnall and her colleagues, in which they found that washing one’s hands leads people to view moral transgressions as less wrong (Schnall, Benton, & Harvey, 2008) [1] . In a different but related study, Schnall and her colleagues investigated whether feeling physically disgusted causes people to make harsher moral judgments (Schnall, Haidt, Clore, & Jordan, 2008) [2] . In this experiment, they manipulated participants’ feelings of disgust by testing them in either a clean room or a messy room that contained dirty dishes, an overflowing wastebasket, and a chewed-up pen. They also used a self-report questionnaire to measure the amount of attention that people pay to their own bodily sensations. They called this “private body consciousness.” They measured their primary dependent variable, the harshness of people’s moral judgments, by describing different behaviours (e.g., eating one’s dead dog, failing to return a found wallet) and having participants rate the moral acceptability of each one on a scale of 1 to 7. They also measured some other dependent variables, including participants’ willingness to eat at a new restaurant. Finally, the researchers asked participants to rate their current level of disgust and other emotions. The primary results of this study were that participants in the messy room were in fact more disgusted and made harsher moral judgments than participants in the clean room—but only if they scored relatively high in private body consciousness.

The research designs we have considered so far have been simple—focusing on a question about one variable or about a statistical relationship between two variables. But in many ways the complex design of this experiment undertaken by Schnall and her colleagues is more typical of research in psychology. Fortunately, we have already covered the basic elements of such designs in previous chapters. In this chapter, we look closely at how and why researchers  combine  these basic elements into more complex designs. We start with complex experiments—considering first the inclusion of multiple dependent variables and then the inclusion of multiple independent variables. Finally, we look at complex correlational designs.

• Schnall, S., Benton, J., & Harvey, S. (2008). With a clean conscience: Cleanliness reduces the severity of moral judgments. Psychological Science, 19 (12), 1219-1222. doi: 10.1111/j.1467-9280.2008.02227.x ↵
• Schnall, S., Haidt, J., Clore, G. L., & Jordan, A. H. (2008). Disgust as embodied moral judgment. Personality and Social Psychology Bulletin, 34 , 1096–1109. ↵

Research Methods in Psychology - 2nd Canadian Edition Copyright © 2015 by Paul C. Price, Rajiv Jhangiani, & I-Chant A. Chiang is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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Learning Goals

• Learn the basics of correlational research.

Research Methods in Psychology

Correlational research.

What Is Correlational Research?

Correlational research is a type of non-experimental research in which the researcher measures two variables and assesses the statistical relationship (i.e., the correlation) between them with little or no effort to control extraneous variables. There are essentially two reasons that researchers interested in statistical relationships between variables would choose to conduct a correlational study rather than an experiment. The first is that they do not believe that the statistical relationship is a causal one, meaning that one variable is responsible for creating a change in a second variable. For example, a researcher might evaluate the validity of a brief extraversion test by administering it to a large group of participants along with a longer extraversion test that has already been shown to be valid. This researcher might then check to see whether participants’ scores on the brief test are strongly correlated with their scores on the longer one. Neither test score is thought to cause the other, so there is no independent variable to manipulate. In fact, the terms independent variable and dependent variable do not apply to this kind of research.

The other reason that researchers would choose to use a correlational study rather than an experiment is that the statistical relationship of interest is thought to be causal, but the researcher cannot manipulate the independent variable because it is impossible, impractical, or unethical. For example, Allen Kanner and his colleagues thought that the number of “daily hassles” (e.g., rude salespeople, heavy traffic) that people experience affects the number of physical and psychological symptoms they have (Kanner, Coyne, Schaefer, & Lazarus, 1981). But because they could not manipulate the number of daily hassles their participants experienced, they had to settle for measuring the number of daily hassles—along with the number of symptoms—using self-report questionnaires. Although the strong positive relationship they found between these two variables is consistent with their idea that hassles cause symptoms, it is also consistent with the idea that symptoms cause hassles or that some third variable (e.g., neuroticism) causes both.

A common misconception among beginning researchers is that correlational research must involve two quantitative variables, such as scores on two extraversion tests or the number of hassles and number of symptoms people have experienced. However, the defining feature of correlational research is that the two variables are measured—neither one is manipulated—and this is true regardless of whether the variables are quantitative or categorical. Imagine, for example, that a researcher administers the Rosenberg Self-Esteem Scale to 50 American college students and 50 Japanese college students. Although this “feels” like a between-subjects experiment, it is a correlational study because the researcher did not manipulate the students’ nationalities. The same is true of the study by Cacioppo and Petty comparing college faculty and factory workers in terms of their need for cognition. It is a correlational study because the researchers did not manipulate the participants’ occupations.

Consider a hypothetical study on the relationship between whether people make a daily list of things to do (a “to-do list”) and stress. Notice that it is unclear whether this is an experiment or a correlational study because it is unclear whether the independent variable was manipulated. If the researcher randomly assigned some participants to make daily to-do lists and others not to, then it is an experiment. If the researcher simply asked participants whether they made daily to-do lists, then it is a correlational study. The distinction is important because if the study was an experiment, then it could be concluded that making the daily to-do lists reduced participants’ stress. But if it was a correlational study, it could only be concluded that these variables are statistically related. Perhaps being stressed has a negative effect on people’s ability to plan ahead (the directionality problem). Or perhaps people who are more conscientious are more likely to make to-do lists and less likely to be stressed (the third-variable problem). The crucial point is that what defines a study as experimental or correlational is not the variables being studied, nor whether the variables are quantitative or categorical, nor the type of graph or statistics used to analyze the data. It is how the study is conducted.

8.1  Data Collection in Correlational Research

Again, the defining feature of correlational research is that neither variable is manipulated. It does not matter how or where the variables are measured. A researcher could have participants come to a laboratory to complete a computerized backward digit span task and a computerized risky decision-making task and then assess the relationship between participants’ scores on the two tasks. Or a researcher could go to a shopping mall to ask people about their attitudes toward the environment and their shopping habits and then assess the relationship between these two variables. Both of these studies would be correlational because no independent variable is manipulated. However, because some approaches to data collection are strongly associated with correlational research, it makes sense to discuss them here. The two we will focus on are naturalistic observation and archival data. A third, survey research, is discussed in its own chapter.

Naturalistic Observation

Naturalistic observation is an approach to data collection that involves observing people’s behavior in the environment in which it typically occurs. Thus naturalistic observation is a type of field research (as opposed to a type of laboratory research). It could involve observing shoppers in a grocery store, children on a school playground, or psychiatric inpatients in their wards. Researchers engaged in naturalistic observation usually make their observations as unobtrusively as possible so that participants are often not aware that they are being studied. Ethically, this is considered to be acceptable if the participants remain anonymous and the behavior occurs in a public setting where people would not normally have an expectation of privacy. Grocery shoppers putting items into their shopping carts, for example, are engaged in public behavior that is easily observable by store employees and other shoppers. For this reason, most researchers would consider it ethically acceptable to observe them for a study. On the other hand, one of the arguments against the ethicality of the naturalistic observation of “bathroom behavior” discussed earlier in the book is that people have a reasonable expectation of privacy even in a public restroom and that this expectation was violated.

Researchers Robert Levine and Ara Norenzayan used naturalistic observation to study differences in the “pace of life” across countries (Levine & Norenzayan, 1999). One of their measures involved observing pedestrians in a large city to see how long it took them to walk 60 feet. They found that people in some countries walked reliably faster than people in other countries. For example, people in the United States and Japan covered 60 feet in about 12 seconds on average, while people in Brazil and Romania took close to 17 seconds.

Because naturalistic observation takes place in the complex and even chaotic “real world,” there are two closely related issues that researchers must deal with before collecting data. The first is sampling. When, where, and under what conditions will the observations be made, and who exactly will be observed? Levine and Norenzayan described their sampling process as follows:

 Male and female walking speed over a distance of 60 feet was measured in at least two locations in main downtown areas in each city. Measurements were taken during main business hours on clear summer days. All locations were flat, unobstructed, had broad sidewalks, and were sufficiently uncrowded to allow pedestrians to move at potentially maximum speeds. To control for the effects of socializing, only pedestrians walking alone were used. Children, individuals with obvious physical handicaps, and window-shoppers were not timed. Thirty-five men and 35 women were timed in most cities. (p. 186)

Precise specification of the sampling process in this way makes data collection manageable for the observers, and it also provides some control over important extraneous variables. For example, by making their observations on clear summer days in all countries, Levine and Norenzayan controlled for effects of the weather on people’s walking speeds.

The second issue is measurement. What specific behaviors will be observed? In Levine and Norenzayan’s study, measurement was relatively straightforward. They simply measured out a 60-foot distance along a city sidewalk and then used a stopwatch to time participants as they walked over that distance. Often, however, the behaviors of interest are not so obvious or objective. For example, researchers Robert Kraut and Robert Johnston wanted to study bowlers’ reactions to their shots, both when they were facing the pins and then when they turned toward their companions (Kraut & Johnston, 1979). But what “reactions” should they observe? Based on previous research and their own pilot testing, Kraut and Johnston created a list of reactions that included “closed smile,” “open smile,” “laugh,” “neutral face,” “look down,” “look away,” and “face cover” (covering one’s face with one’s hands). The observers committed this list to memory and then practiced by coding the reactions of bowlers who had been videotaped. During the actual study, the observers spoke into an audio recorder, describing the reactions they observed. Among the most interesting results of this study was that bowlers rarely smiled while they still faced the pins. They were much more likely to smile after they turned toward their companions, suggesting that smiling is not purely an expression of happiness but also a form of social communication.

Naturalistic observation has revealed that bowlers tend to smile when they turn away from the pins and toward their companions, suggesting that smiling is not purely an expression of happiness but also a form of social communication.

When the observations require a judgment on the part of the observers—as in Kraut and Johnston’s study—this process is often described as coding. Coding generally requires clearly defining a set of target behaviors. The observers then categorize participants individually in terms of which behavior they have engaged in and the number of times they engaged in each behavior. The observers might even record the duration of each behavior. The target behaviors must be defined in such a way that different observers code them in the same way. This is the issue of inter-rater reliability. Researchers are expected to demonstrate the inter-rater reliability of their coding procedure by having multiple raters code the same behaviors independently and then showing that the different observers are in close agreement. Kraut and Johnston, for example, video recorded a subset of their participants’ reactions and had two observers independently code them. The two observers showed that they agreed on the reactions that were exhibited 97% of the time, indicating good inter-rater reliability.

Archival Data

Another approach to correlational research is the use of archival data, which are data that have already been collected for some other purpose. An example is a study by Brett Pelham and his colleagues on “implicit egotism”—the tendency for people to prefer people, places, and things that are similar to themselves (Pelham, Carvallo, & Jones, 2005). In one study, they examined Social Security records to show that women with the names Virginia, Georgia, Louise, and Florence were especially likely to have moved to the states of Virginia, Georgia, Louisiana, and Florida, respectively.

As with naturalistic observation, measurement can be more or less straightforward when working with archival data. For example, counting the number of people named Virginia who live in various states based on Social Security records is relatively straightforward. But consider a study by Christopher Peterson and his colleagues on the relationship between optimism and health using data that had been collected many years before for a study on adult development (Peterson, Seligman, & Vaillant, 1988). In the 1940s, healthy male college students had completed an open-ended questionnaire about difficult wartime experiences. In the late 1980s, Peterson and his colleagues reviewed the men’s questionnaire responses to obtain a measure of explanatory style—their habitual ways of explaining bad events that happen to them. More pessimistic people tend to blame themselves and expect long-term negative consequences that affect many aspects of their lives, while more optimistic people tend to blame outside forces and expect limited negative consequences. To obtain a measure of explanatory style for each participant, the researchers used a procedure in which all negative events mentioned in the questionnaire responses, and any causal explanations for them, were identified and written on index cards. These were given to a separate group of raters who rated each explanation in terms of three separate dimensions of optimism-pessimism. These ratings were then averaged to produce an explanatory style score for each participant. The researchers then assessed the statistical relationship between the men’s explanatory style as college students and archival measures of their health at approximately 60 years of age. The primary result was that the more optimistic the men were as college students, the healthier they were as older men. Pearson’s r was +.25.

This is an example of content analysis—a family of systematic approaches to measurement using complex archival data. Just as naturalistic observation requires specifying the behaviors of interest and then noting them as they occur, content analysis requires specifying keywords, phrases, or ideas and then finding all occurrences of them in the data. These occurrences can then be counted, timed (e.g., the amount of time devoted to entertainment topics on the nightly news show), or analyzed in a variety of other ways.

Key Takeaways

·         Correlational research involves measuring two variables and assessing the relationship between them, with no manipulation of an independent variable.

·         Correlational research is not defined by where or how the data are collected. However, some approaches to data collection are strongly associated with correlational research. These include naturalistic observation (in which researchers observe people’s behavior in the context in which it normally occurs) and the use of archival data that were already collected for some other purpose.

8.2  Assessing Relationships among Multiple Variables

Most complex correlational research involves measuring several variables—often both categorical and quantitative—and then assessing the statistical relationships among them. For example, researchers Nathan Radcliffe and William Klein studied a sample of middle-aged adults to see how their level of optimism (measured by using a short questionnaire called the Life Orientation Test) relates to several other variables related to having a heart attack (Radcliffe & Klein, 2002). These included their health, their knowledge of heart attack risk factors, and their beliefs about their own risk of having a heart attack. They found that more optimistic participants were healthier (e.g., they exercised more and had lower blood pressure), knew about heart attack risk factors, and correctly believed their own risk to be lower than that of their peers.

This approach is often used to assess the validity of new psychological measures. For example, when John Cacioppo and Richard Petty created their Need for Cognition Scale—a measure of the extent to which people like to think and value thinking—they used it to measure the need for cognition for a large sample of college students, along with three other variables: intelligence, socially desirable responding (the tendency to give what one thinks is the “appropriate” response), and dogmatism (Caccioppo & Petty, 1982). The results of this study are summarized in Table 8.2 “Correlation Matrix Showing Correlations Among the Need for Cognition and Three Other Variables Based on Research by Cacioppo and Petty”, which is a correlation matrix showing the correlation (Pearson’s r) between every possible pair of variables in the study. For example, the correlation between the need for cognition and intelligence was +.39, the correlation between intelligence and socially desirable responding was −.02, and so on. (Only half the matrix is filled in because the other half would contain exactly the same information. Also, because the correlation between a variable and itself is always +1.00, these values are replaced with dashes throughout the matrix.) In this case, the overall pattern of correlations was consistent with the researchers’ ideas about how scores on the need for cognition should be related to these other constructs.

Table 8.2 Correlation Matrix Showing Correlations Among the Need for Cognition and Three Other Variables Based on Research by Cacioppo and Petty

When researchers study relationships among a large number of conceptually similar variables, they often use a complex statistical technique called factor analysis. In essence, factor analysis organizes the variables into a smaller number of clusters, such that they are strongly correlated within each cluster but weakly correlated between clusters. Each cluster is then interpreted as multiple measures of the same underlying construct. These underlying constructs are also called “factors.” For example, when people perform a wide variety of mental tasks, factor analysis typically organizes them into two main factors—one that researchers interpret as mathematical intelligence (arithmetic, quantitative estimation, spatial reasoning, and so on) and another that they interpret as verbal intelligence (grammar, reading comprehension, vocabulary, and so on). The Big Five personality factors have been identified through factor analyses of people’s scores on a large number of more specific traits. For example, measures of warmth, gregariousness, activity level, and positive emotions tend to be highly correlated with each other and are interpreted as representing the construct of extroversion. As a final example, researchers Peter Rentfrow and Samuel Gosling asked more than 1,700 college students to rate how much they liked 14 different popular genres of music (Rentfrow & Gosling, 2008). They then submitted these 14 variables to a factor analysis, which identified four distinct factors. The researchers called them Reflective and Complex (blues, jazz, classical, and folk), Intense and Rebellious (rock, alternative, and heavy metal), Upbeat and Conventional (country, soundtrack, religious, pop), and Energetic and Rhythmic (rap/hip-hop, soul/funk, and electronica).

Two additional points about factor analysis are worth making here. One is that factors are not categories. Factor analysis does not tell us that people are either extroverted or conscientious or that they like either “reflective and complex” music or “intense and rebellious” music. Instead, factors are constructs that operate independently of each other. So people who are high in extroversion might be high or low in conscientiousness, and people who like reflective and complex music might or might not also like intense and rebellious music. The second point is that factor analysis reveals only the underlying structure of the variables. It is up to researchers to interpret and label the factors and to explain the origin of that particular factor structure. For example, one reason that extroversion and the other Big Five operate as separate factors is that they appear to be controlled by different genes (Plomin, DeFries, McClean, & McGuffin, 2008).

8.3  Exploring Causal Relationships

Another important use of complex correlational research is to explore possible causal relationships among variables. This might seem surprising given that “correlation does not imply causation.” It is true that correlational research cannot unambiguously establish that one variable causes another. Complex correlational research, however, can often be used to rule out other plausible interpretations.

The primary way of doing this is through the statistical control of potential third variables. Instead of controlling these variables by random assignment or by holding them constant as in an experiment, the researcher measures them and includes them in the statistical analysis. Consider some research by Paul Piff and his colleagues, who hypothesized that being lower in socioeconomic status (SES) causes people to be more generous (Piff, Kraus, Côté, Hayden Cheng, & Keltner, 2011). They measured their participants’ SES and had them play the “dictator game.” They told participants that each would be paired with another participant in a different room. (In reality, there was no other participant.) Then they gave each participant 10 points (which could later be converted to money) to split with the “partner” in whatever way he or she decided. Because the participants were the “dictators,” they could even keep all 10 points for themselves if they wanted to.

As these researchers expected, participants who were lower in SES tended to give away more of their points than participants who were higher in SES. This is consistent with the idea that being lower in SES causes people to be more generous. But there are also plausible third variables that could explain this relationship. It could be, for example, that people who are lower in SES tend to be more religious and that it is their greater religiosity that causes them to be more generous. Or it could be that people who are lower in SES tend to come from ethnic groups that emphasize generosity more than other ethnic groups. The researchers dealt with these potential third variables, however, by measuring them and including them in their statistical analyses. They found that neither religiosity nor ethnicity was correlated with generosity and were therefore able to rule them out as third variables. This does not prove that SES causes greater generosity because there could still be other third variables that the researchers did not measure. But by ruling out some of the most plausible third variables, the researchers made a stronger case for SES as the cause of the greater generosity.

Many studies of this type use a statistical technique called multiple regression. This involves measuring several independent variables (X1, X2, X3,…Xi), all of which are possible causes of a single dependent variable (Y). The result of a multiple regression analysis is an equation that expresses the dependent variable as an additive combination of the independent variables. This regression equation has the following general form:

b1X1+ b2X2+ b3X3+ … + biXi= Y.

The quantities b1, b2, and so on are regression weights that indicate how large a contribution an independent variable makes, on average, to the dependent variable. Specifically, they indicate how much the dependent variable changes for each one-unit change in the independent variable.

The advantage of multiple regression is that it can show whether an independent variable makes a contribution to a dependent variable over and above the contributions made by other independent variables. As a hypothetical example, imagine that a researcher wants to know how the independent variables of income and health relate to the dependent variable of happiness. This is tricky because income and health are themselves related to each other. Thus if people with greater incomes tend to be happier, then perhaps this is only because they tend to be healthier. Likewise, if people who are healthier tend to be happier, perhaps this is only because they tend to make more money. But a multiple regression analysis including both income and happiness as independent variables would show whether each one makes a contribution to happiness when the other is taken into account. Research like this, by the way, has shown both income and health make extremely small contributions to happiness except in the case of severe poverty or illness (Diener, 2000).

The examples discussed in this section only scratch the surface of how researchers use complex correlational research to explore possible causal relationships among variables. It is important to keep in mind, however, that purely correlational approaches cannot unambiguously establish that one variable causes another. The best they can do is show patterns of relationships that are consistent with some causal interpretations and inconsistent with others.

·         Researchers often use complex correlational research to explore relationships among several variables in the same study.

·         Complex correlational research can be used to explore possible causal relationships among variables using techniques such as multiple regression. Such designs can show patterns of relationships that are consistent with some causal interpretations and inconsistent with others, but they cannot unambiguously establish that one variable causes another.

References from Chapter 8

Cacioppo, J. T., & Petty, R. E. (1982). The need for cognition. Journal of Personality and Social Psychology, 42, 116–131.

Diener, E. (2000). Subjective well-being: The science of happiness, and a proposal for a national index. American Psychologist, 55, 34–43.

Kanner, A. D., Coyne, J. C., Schaefer, C., & Lazarus, R. S. (1981). Comparison of two modes of stress measurement: Daily hassles and uplifts versus major life events. Journal of Behavioral Medicine, 4, 1–39.

Kraut, R. E., & Johnston, R. E. (1979). Social and emotional messages of smiling: An ethological approach. Journal of Personality and Social Psychology, 37, 1539–1553.

Levine, R. V., & Norenzayan, A. (1999). The pace of life in 31 countries. Journal of Cross-Cultural Psychology, 30, 178–205.

MacDonald, T. K., & Martineau, A. M. (2002). Self-esteem, mood, and intentions to use condoms: When does low self-esteem lead to risky health behaviors? Journal of Experimental Social Psychology, 38, 299–306.

Pelham, B. W., Carvallo, M., & Jones, J. T. (2005). Implicit egotism. Current Directions in Psychological Science, 14, 106–110.

Peterson, C., Seligman, M. E. P., & Vaillant, G. E. (1988). Pessimistic explanatory style is a risk factor for physical illness: A thirty-five year longitudinal study. Journal of Personality and Social Psychology, 55, 23–27.

Piff, P. K., Kraus, M. W., Côté, S., Hayden Cheng, B., & Keltner, D. (2011). Having less, giving more: The influence of social class on prosocial behavior. Journal of Personality and Social Psychology, 99, 771–784.

Plomin, R., DeFries, J. C., McClearn, G. E., & McGuffin, P. (2008). Behavioral genetics (5th ed.). New York, NY: Worth.

Radcliffe, N. M., & Klein, W. M. P. (2002). Dispositional, unrealistic, and comparative optimism: Differential relations with knowledge and processing of risk information and beliefs about personal risk. Personality and Social Psychology Bulletin, 28, 836–846.

Rentfrow, P. J., & Gosling, S. D. (2008). The do re mi’s of everyday life: The structure and personality correlates of music preferences. Journal of Personality and Social Psychology, 84, 1236–1256.    

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Chapter 8: Case study

Darshini Ayton

Learning outcomes

Upon completion of this chapter, you should be able to:

• Identify the key terms and concepts used in qualitative case study research.
• Discuss the advantages and disadvantages of qualitative case study research.

What is a case study?

The key concept in a case study is context .

In qualitative research, case studies provide in-depth accounts of events, relationships, experiences or processes. Stemming from the fields of evaluation, political science and law, the aim of a qualitative case study is to explore a phenomenon within the context of the case 1 and to answer how and why research questions. 2 The contextual conditions are relevant to the phenomenon under study and the contextual factors tend to lie with the case. 1 From the outset it is important (a) to determine who or what is your case – this can be a person, program, organisation or group, or a process – and (b) to articulate the phenomenon of interest.

An example of why context is important in understanding the phenomenon of interest is a study of health promotion action by local churches in Victoria, Australia. 3 The phenomenon under study was health promotion action, with 10 churches comprising the cases, which were mapped across the framework of health promotion approaches. 4 The contextual factors included church denomination (Baptist, Church of Christ, Uniting, Anglican, Catholic and Salvation Army), size (small, medium and large), location (rural and metropolitan), partnerships with external organisations (government, local schools and social welfare organisations) and theological orientation (traditional, modern or postmodern), to understand the phenomenon of health promotion action. Data collection took 12 months and involved interviews with 37 church leaders, 10 focus groups with volunteers, 17 instances of participant observation of church activities, including church services, youth events, food banks and community meals, and 12 documentary analyses of church websites, newsletters and annual reports. The case studies identified and illustrated how and why three different expressions of church – traditional, new modern and emerging – led to different levels and types of health promotion activities.

Three prominent qualitative case study methodologists, Robert Stake, Robert Yin and Sharan Merriams, have articulated different approaches to case studies and their underpinning philosophical and paradigmatic assumptions. Table 8 outlines these approaches, based on work by Yazan, 5 whose expanded table covers characteristics of case studies, data collection and analysis.

Table 8.1. Comparison of case study terms used by three key methodologists

Table 8.1 is derived from ‘Three Approaches to Case Study Methods in Education: Yin, Merriam, and Stake ‘  by Bedrettin Yazan,  licensed under CC BY-NC-SA 4.0. 5

There are several forms of qualitative case studies. 1,2

Discovery-led case studies, which:

• describe what is happening in the setting
• explore the key issues affecting people within the setting
• compare settings, to learn from the similarities and differences between them.

Theory-led case studies, which:

• explain the causes of events, processes or relationships within a setting
• illustrate how a particular theory applies to a real-life setting
• experiment with changes in the setting to test specific factors or variables.

Single and collective case studies, where: 2, 9

• the researcher wants to understand a unique phenomenon in detail– known as an intrinsic case study
• the researcher is seeking insight and understanding of a particular situation or phenomenon, known as an illustrative case study or instrumental case study.

In both intrinsic, instrumental and illustrative case studies, the exploration might take place within a single case. In contrast, a collective case study includes multiple individual cases, and the exploration occurs both within and between cases. Collective case studies may include comparative cases, whereby cases are sampled to provide points of comparison for either context or the phenomenon. Embedded case studies are increasingly common within multi-site, randomised controlled trials, where each of the study sites is considered a case.

Multiple forms of data collection and methods of analysis (e.g. thematic, content, framework and constant comparative analyses) can be employed, since case studies are characterised by the depth of knowledge they provide and their nuanced approaches to understanding phenomena within context. 2,5 This approach enables triangulation between data sources (interviews, focus groups, participant observations), researchers and theory. Refer to Chapter 19 for information about triangulation.

Advantages and disadvantages of qualitative case studies

Advantages of using a case study approach include the ability to explore the subtleties and intricacies of complex social situations, and the use of multiple data collection methods and data from multiple sources within the case, which enables rigour through triangulation. Collective case studies enable comparison and contrasting within and across cases.

However, it can be challenging to define the boundaries of the case and to gain appropriate access to the case for the ‘deep dive’ form of analysis. Participant observation, which is a common form of data collection, can lead to observer bias. Data collection can take a long time and may require lengthy times, resources and funding to conduct the study. 9

Table 8.2 provides an example of a single case study and of a collective case study.

Table 8.2. Examples of qualitative case studies

Qualitative case studies provide a study design with diverse methods to examine the contextual factors relevant to understanding the why and how of a phenomenon within a case. The design incorporates single case studies and collective cases, which can also be embedded within randomised controlled trials as a form of process evaluation.

• Creswell J, Hanson W, Clark Plano V et al.. Qualitative research designs: selection and implementation. Couns Psychol  2007;35(2):236-264. doi:10.1177/0011000006287390
• Crowe S, Cresswell K, Robertson A, et al. The case study approach. BMC Med Res Methodol . 2011;11:100. doi:10.1186/1471-2288-11-100
• Ayton D, Manderson L, Smith BJ et al. Health promotion in local churches in Victoria: an exploratory study. Health Soc Care Community . 2016;24(6):728-738. doi:10.1111/hsc.12258
• Keleher H, Murphy C. Understanding Health: A Determinants Approach . Oxford University Press; 2004.
• Yazan B. Three approaches to case study methods in education: Yin, Merriam, and Stake. The Qualitative Report . 2015;20(2):134-152. doi:10.46743/2160-3715/2015.2102
• Stake RE. The A rt of C ase S tudy R esearch . SAGE Publications; 1995.
• Yin RK. Case S tudy R esearch: Design and M ethods . SAGE Publications; 2002.
• Merriam SB. Qualitative R esearch and C ase S tudy A pplications in E ducation . Jossey-Boss; 1998.
• Kekeya J. Qualitative case study research design: the commonalities and differences between collective, intrinsic and instrumental case studies. Contemporary PNG Studies . 2021;36:28-37.
• Nayback-Beebe AM, Yoder LH. The lived experiences of a male survivor of intimate partner violence: a qualitative case study. Medsurg Nurs . 2012;21(2):89-95; quiz 96.
• Clack L, Zingg W, Saint S et al. Implementing infection prevention practices across European hospitals: an in-depth qualitative assessment. BMJ Qual Saf . 2018;27(10):771-780. doi:10.1136/bmjqs-2017-007675

Qualitative Research – a practical guide for health and social care researchers and practitioners Copyright © 2023 by Darshini Ayton is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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Chapter 8: Research designs using mixed methods

2014, Doing Research in the Real World, 3rd edn

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Academic research and writing

A concise introduction

Chapter 8 – Primer

A well-thought-out interpretation of the topic is a prerequisite for the successful execution of a research project. Especially in academic settings, research candidates have not only the duty, but also the right to develop an interpretation of their topics. In some cases, the thesis advisor might assist the interpretation process. In other cases, research candidates have to derive an interpretation on their own. An ideal interpretation process starts with a negative and a positive interpretation of the topic and thereby the identification of possible aims. Once possible aims and their implications are known, the research candidate has to select one aim or a combination of aims. There are five possible aims: description, causal connection, intention, function, and comparison. The interpretation of a topic can be of an abstract (theoretical) or problem-based (applied) nature. Within the process of a problem-based interpretation, the empirical environment has to be considered. The identified aim predetermines the nature of possible research questions to be investigated.

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Chapter Eight: Research Concepts

We live in an age of immediate answers. Although we have not achieved parity in access to technology worldwide, information has never been easier to uncover. This is, of course, a double-edged sword: the proliferation of ideas due to the technological revolution enables new kinds of learning, but also has fundamentally changed the way we think and interact.

One of my friends refers to his iPhone as “The Wonder Killer”: because he has such quick access to answers through the miniature computer he carries everywhere, the experience of sustained curiosity is now very rare in his life. All kinds of questions are easily answered by googling—“Who was that guy in Back to the Future Part II ?” “Do spiders hibernate?”—or a brief crawl through Wikipedia—“How has globalization impacted Bhutan’s economy?” “What life experiences influenced Frida Kahlo’s painting?” But the answers to these questions, though easily discovered, paint a very one-dimensional portrait of human knowledge.

Take a look at this brief TED video from Adam Savage of MythBusters . For scientists and writers alike, the spirit of curiosity at once motivates individual learning and also the growth and progress of our collective knowledge. Your innate ability to be curious puts you in the league of the most brilliant and prolific scholars—people who were driven by questions, seeking to interrogate the world around them.

In this section, I add my voice to the chorus of writing teachers whose rallying cry is a renewed investment in curiosity 1 . Hopefully, you too will embrace inquisitive fascination by rejecting easy answers and using writing as a means of discovery.

Chapter Vocabulary

Inquiry-based research.

It’s possible that you’ve already written research papers by this point in your academic career. If your experience has been like mine was, writing these papers went one of two ways:

The teacher assigns a specific topic for you to research, and sometimes even a specific thesis for you to prove.

The teacher provides more freedom, allowing students to choose a topic at their own discretion or from a set of options.

In both situations, my teacher expected me to figure out what I wanted to argue, then find research to back me up. I was expected to have a fully formed stance on an issue, then use my sources to explain and support that stance. Not until graduate school did I encounter inquiry-based research , which inverts this sequence.

Put simply, inquiry-based research refers to research and research writing that is motivated by

Consider the difference this can make: if research is about learning , then an inquiry-based perspective is essential. If you only seek out the ideas that agree with you, you will never learn.

Even in the event that the investigation yields the same answers, their differences are crucial. The example in the table above demonstrates confirmation bias , or as we called it in Chapter Four, “projection.” (You might be familiar with this phenomenon from politicized social media spheres which tailor content to the user; 2 you may have also identified it as the force behind many axes of prejudice, racialized police violence, and discrimination.) When we only look for answers that agree with our preexisting ideas, we are more likely to ignore other important ideas, voices, and possibilities. Most importantly, confirmation bias inhibits genuine learning, which relies on challenging, expanding, and complicating our current knowledge and worldviews

Consequently, inquiry-based research is time-consuming and intensive: instead of only dealing with evidence that supports a certain answer or perspective, it requires the reasoner to encounter a great diversity of evidence and answers, which can be difficult to sift through.

You don’t have to—shouldn’t, in fact—have a thesis set in stone before starting research. In lieu of a thesis guiding your process, a research question or path of inquiry will motivate your research and writing. You might have a hypothesis or a working thesis, but you must be tremendously flexible: be prepared to pivot, qualify, nuance, or entirely change your answer as you proceed.

In order to pursue your research question, you will need to encounter a lot of sources. Not all of the sources you encounter will make it into your paper, which is a new practice for some students. (When I engage in inquiry-based research, I would approximate that one in every twelve sources I encounter makes an appearance in my final draft. The other eleven may be interesting or educational, but might not have a place in my discussion.) This is a time-consuming process, but it leads to more significant learning, more complex thinking, and more interesting and effective rhetoric.

Ongoing Conversation 3

Imagine yourself arriving at a party or some other social gathering. You walk up to a circle of people chatting casually about Star Wars . It’s clear they have been on about it for a while. Some of them you know, some of them you’ve heard of but never met, and some of them are total strangers—but they all seem to have very strong opinions about the film franchise. You want to jump into the conversation, so when someone posits, “Jar Jar Binks was the worst character of the prequels, and maybe even the whole canon,” you blurt out, “Yeah, Jar Jar was not good. He was bad. He was the worst character of the prequels. He might even be the worst of the whole canon.” The circle of people turn to stare at you, confused why you just parroted back what the last person said; all of you feel awkward that you derailed the discussion.

Even writing that example makes me socially anxious. Let’s try option B instead: as you arrive to the group, you listen attentively. You gradually catch the flow and rhythm of the conversation, noticing its unique focus and language. After hearing a number of people speak regarding Jar Jar, you bring together their ideas along with your ideas and experiences. You ease yourself in to the conversation by saying, “I agree with Stan: Jar Jar is a poorly written character. However, he does accomplish George Lucas’s goals of creating comic relief for young audiences, who were a target demographic for the prequels.” A few people nod in agreement; a few people are clearly put out by this interpretation. The conversation continues, and as it grows later, you walk away from the discussion (which is still in full force without you) having made a small but meaningful contribution—a ripple, but a unique and valuable ripple.

This dynamic is much like the world of research writing. Your writing is part of an ongoing conversation : an exchange of ideas on a certain topic which began long before you and will continue after you. If you were to simply parrot back everyone’s ideas to them, you would not advance the conversation and it would probably feel awkward. But by synthesizing many different sources with your unique life experiences, from your unique vantage point (or, “interpretive position” viz. Chapter Four), you can mobilize research and research writing to develop compelling, incisive, and complex insights. You just need to get started by feeling out the conversation and finding your place.

Developing a Topic

Finding a conversation that you’re excited about and genuinely interested in is the first and most important step. As you develop a topic, keep in mind that pursuing your curiosities and passions will make your research process less arduous, more relevant, and more pleasant. Such an approach will also naturally improve the quality of your writing: the interest you have for a topic will come across in the construction of your sentences and willingness to pursue multiple lines of thought about a topic. An author’s boredom results in a boring paper, and an author’s enthusiasm translates to enthusiastic writing.

Depending on the parameters your teacher has set, your research topic might need to (a) present a specific viewpoint, (b) focus on a specific topic, or (c) focus on a certain theme or set of ideas. It’s also possible that your teacher will allow complete autonomy for one or all of your research assignments. Be sure you review any materials your instructor provides and ask clarifying questions to make sure your topic fits the guidelines of their assignment.

To generate ideas, I recommend completing some of the activities included later in this chapter. I find it most productive to identify areas of interest, then develop questions of all sizes and types. Eventually, you will zero in on a question or combination of questions as your path of inquiry.

What makes for a good research question or path of inquiry? Of course, the answer to this question will depend on your rhetorical situation. However, there are some common characteristics of a good research question in any situation:

• It is answerable, but is not easily answerable . 4 Engaging and fruitful research questions require complex, informed answers. However, they shouldn’t be so subjective, intricate, or expansive that they simply cannot be answered in the scope of your rhetorical situation. 5
• It is specific . By establishing parameters on your scope, you can be sure your research is directed and relevant. More discussion of scope and focus continues below, and you can try the exercise titled “Focus: Expanding and Contracting Scope” later in the chapter to learn more.
• It matters to someone . Research questions and the rhetoric they inform are valuable only because they have stakes : even if it’s a small demographic, the answers to your research question should impact someone.
• It allows you to say something new or unique . As discussed earlier in this chapter, inquiry-based research should encourage you to articulate a unique standpoint by synthesizing many different voices, interpreted from your individual perspective, with your life experiences and ideas. What you say doesn’t have to be groundbreaking, but it shouldn’t just reiterate ideas, arguments, histories, or perspectives.

It is difficult to find a question that hits all these marks on your first try. As you proceed through research, pre-writing, drafting, and revising, you should refine and adjust your question(s). Just like any other part of writing, developing a path of inquiry is iterative: you’ve got to take a lot of chances and work your way toward different results. The activity titled “Focus: Expanding and Contracting Scope” in this section can help you complicate and develop your question along a variety of axes.

To hear a different voice on developing research questions, check out this short video from Wilfrid Laurier University.

In order to find the best version of your research question, you should develop “working questions”—questions of all sizes and types that are pertinent to your subject. As you can see below, you can start with a handful of simple working questions that will eventually lead to a viable research question.

As you hone your path of inquiry, you may need to zoom in or out in terms of scope: depending on your rhetorical situation, you will need different degrees of focus. Just like narration, research writing benefits from a careful consideration of scope. Often, a narrower scope is easier to work with than a broader scope—you will be able to write more and write better if your question asks for more complex thinking.

Consider the diagram above. As you build a working knowledge of your topic (get the feel for the conversation that began before you arrived at the party), you might complicate or narrow your working questions. Gradually, try to articulate a research question (or combination of questions). Remember to be flexible as you research though: you might need to pivot, adjust, refocus, or replace your research question as you learn more. Consider this imaginary case study as an example of this process.

Ahmed began his project by identifying the following areas of interest: racism in the U.S.; technology in medicine and health care; and independent film-making. After doing some free-writing and preliminary research on each, he decided he wanted to learn more about racially motivated police violence. He developed working questions:

Are police officers likely to make judgments about citizens based on their race?

Have police forces instituted policies to avoid racism?

Who is most vulnerable to police violence?

Why does it seem like police officers target people of color?

Who is responsible for overseeing the police?

He realized that he needed to narrow his focus to develop a more viable path of inquiry, eventually ending up with the research question,

Over the last thirty years, what populations are most likely to experience police violence in the U.S.?

However, after completing more research, Ahmed discovered that his answers came pretty readily: young Black men are significantly more vulnerable to be victims of police violence. He realized that he’s not really saying anything new, so he had to tweak his path of inquiry.

Ahmed did some more free-writing and dug around to find a source that disagreed with him or added a new layer to his answers. He discovered eventually that there are a handful of police organizations that have made genuine efforts to confront racism in their practices. Despite the widespread and normalized violence enacted against people of color, these groups were working against racial violence. He reoriented his research question to be,

Have antiracist police trainings and strategies been effective in reducing individual or institutional racism over the last thirty years?

Writing a Proposal

Bigger research projects often require additional steps in preparation and process. Before beginning an extended meditation on a topic—before rushing into a long-term or large-scale research project—it’s possible that your teacher will ask you to write a research proposal. The most effective way to make sure your proposal is on the right track is to identify its rhetorical purpose. Are you trying to process ideas? Compile and review initial research? Demonstrate that you’re pursuing a viable path of inquiry? Explain the stakes of your subject?

Although every rhetorical audience will value different parts of the proposal, there are a handful of issues you should try to tackle in any proposal.

• Your subject . Introduce your topic with a general introduction to your topic—not too general, but enough to give the reader a sense of grounding.

Too general: Education is something that happens in every facet of our lives. Better: Access to education is a major concern for people living in a democratic society.

• Your occasion . When you developed your research question, you chose an issue that matters to someone, meaning that it is timely and important. To establish the significance of your topic, explain what’s prompting your writing and why it matters.

Since Betsy Devos’ nomination for U.S. Secretary of Education, the discussion surrounding school choice has gained significant momentum. Socioeconomic inequality in this country has produced great discrepancies in the quality of education that young people experience, and it is clear that something must be done.

• Your stakes and stakeholders . Although you may have alluded to why your question matters when introducing your occasion, you might take a sentence or two to elaborate on its significance. What effect will the answer(s) you find have, and on whom?

Because educational inequality relates to other forms of injustice, efforts to create fairness in the quality of schools will influence U.S. racial politics, gender equality, and socioeconomic stratification. For better or for worse, school reform of any kind will impact greater social structures and institutions that color our daily lives as students, parents, and community members.

• Your research question or path of inquiry . After introducing your subject, occasion, and stakes, allow the question guiding your research to step in.

Some people believe that school choice programs are the answer. But is it likely that people of all socioeconomic backgrounds can experience parity in education through current school voucher proposals?

• Your position as a working thesis . Articulate your position as a (hypo)thesis—a potential answer to your question or an idea of where your research might take you. This is an answer which you should continue to adjust along the way; writing it in the proposal does not set your answer(s) in stone.

In my research, I will examine whether school choice programs have the potential to create more equitable schooling experiences for all students. Even though proponents of school choice use the language of freedom and equality to justify school vouchers, recent propositions for school choice would likely exacerbate inequality in education and access.

• The difficulties you anticipate in the research and writing process and how you plan to address them . In your proposal, you are trying to demonstrate that your path of inquiry is viable; therefore, it is important to show that you’re thinking through the challenges you might face along the way. Consider what elements of researching and writing will be difficult, and how you will approach those difficulties.

There are a vast number of resources on school choice, but I anticipate encountering some difficulty in pursuing my guiding question. For example, many people discussing this topic are entrenched in their current viewpoints. Similarly, this issue is very politicized, dividing people mostly along party lines. I also need to do more preliminary research: I’m not certain if there have been school choice experiments conducted on any significant scale, in the U.S. or elsewhere. Finally, it is difficult to evaluate complex social phenomena of inequality without also considering race, gender, disability status, nationality, etc.; I’ll need to focus on socioeconomic status, but I cannot treat it as a discrete issue.

• Optional, depending on your rhetorical situation: A working list of sources consulted in your preliminary research . I ask my students to include a handful of sources they have encountered as they identified their topic and path of inquiry: this shows that they are working toward understanding their place in an ongoing conversation.

Works Cited

Worsnop, Richard L. “School Choice: Would It Strengthen or Weaken Public Education in America?” CQ Researcher , vol. 1, 10 May 1991, pp. 253-276.

Zornick, George. “Bernie Sanders Just Introduced His Free College Tuition Plan.” The Nation [Article] , The Nation Company LLC, 3 April 2017.

Combining these examples, we can see our proposal come together in a couple of paragraphs:

School Vouchers: Bureaucratizing Inequality

Access to education is a major concern for people living in a democratic society. Since Betsy Devos’ nomination for U.S. Secretary of Education, the discussion surrounding school choice has gained significant momentum. Socioeconomic inequality in this country has produced great discrepancies in the quality of education that young people experience, and it is clear that something must be done. Because educational inequality relates to other forms of injustice, efforts to create fairness in the quality of schools will influence U.S. racial politics, gender equality, and socioeconomic stratification. For better or for worse, school reform of any kind will impact greater social structures and institutions that color our daily lives as students, parents, and community members. Some people believe that school choice programs are the answer. But is it likely that people of all socioeconomic backgrounds can experience parity in education through current school voucher proposals?

Zornick, George. “Bernie Sanders Just Introduced His Free College Tuition Plan.” The Nation , The Nation Company LLC, 3 April 2017, Bernie Sanders Just Introduced His Free College Tuition Plan [The Nation article]

As you develop your own proposal, I encourage you to follow these steps, answering the questions listed above. However, in order to create a more cohesive proposal, be sure to revise for fluency: your proposal shouldn’t read like a list of answers, but like a short essay outlining your interests and expectations.

Idea Generation: Curiosity Catalogue 6 and Collaborative Inquiry

This exercise encourages you to collaborate with other classmates to develop a topic, working questions, a path of inquiry, and a baseline of communal knowledge. You should complete Part One independently, then gather with a small group of two or three other students for Part Two, and a different small group of two or three other students for Part Three: Small Group. (If you are working on this exercise as a full class, complete Part One, Part Two, and Part Three: Gallery Walk.) Before you get started, divide three large sheets of paper (11×17 is best) into columns like this:

Create a catalogue of topics you are personally curious about—things that you want to learn more about. These don’t have to be revolutionary things right away; it’s more important that they’re meaningful to you. First, choose three of the following broad topic headings:

On your first sheet of three-column paper, write those three topic headings.

Next, underneath each topic heading, write bulleted lists of as many subtopics or related ideas that come to mind that interest you. (Try not to censor yourself here—the idea is to generate a large number of bullet points. To some extent, this is an exercise in free association: what are the first things that come to mind when you think of each topic?) Spend ten to fifteen minutes on your lists. Then, take a five-minute break away from your lists and clear your head; return to your lists for three more minutes to make any additions that you didn’t think of at first.

Read over your lists, making note especially of items that surprised you. Choose the three items from the full page that most interest you. You can choose one from each column, three from the same, or any combination of lists, so long as you have three items that you care about.

Begin to develop a working knowledge by collaborating with

classmates to consider the topic from several perspectives beyond your own.

Review the knowledge your groupmates compiled on your sheet. Have they offered anything that surprises you—stuff you didn’t know already, conflicting perspectives, or connections to other ideas or topics?

Part Three: Small Group

Begin to develop working and research questions by collaborating with your classmates to explore different curiosities. (This part of the exercise is designed for a small group of three or four total students, including you, different from the group in Part Two. If you are completing this part of the exercise with your whole class, skip to Part Three: Gallery Walk.)

Sit in a circle with your groupmates; each student should pass their three-column paper one position clockwise. For five minutes, each student will free-write questions about each topic. No question is too big or small, too simple or complex. Try to generate as many questions as you possibly can. Then, rotate your papers another step—repeat until you have your original sheet of paper back.

Review the questions your groupmates compiled on your sheet. Have they offered anything that surprises you—issues you haven’t thought of, relationships between questions, recurring themes or patterns of interest, or foci that might yield interesting answers?

Part Three: Gallery Walk

Begin to develop working and research questions by collaborating with your classmates to explore different curiosities. (This part of the exercise is designed for an entire class of students of about twenty to twenty-five students, including you. If you are completing this part of the exercise a small group of three to four total students, including you, return to Part Three: Small Group.)

Review the questions your classmates compiled on your sheet. Have they offered anything that surprises you—issues you haven’t thought of, relationships between questions, recurring themes or patterns of interest, or foci that might yield interesting answers?

After completing all three parts of this exercise, try to articulate a viable and interesting research question that speaks to your curiosity. Make sure its scope is appropriate to your rhetorical situation; you can use the exercise “Focus: Expanding and Contracting Scope” later in this chapter to help expand or narrow your scope.

If you’re still struggling to find a topic, try some of other idea generation activities that follow this, or check in with your school’s Writing Center, your teacher, or your peers.

Idea Generation: Mind-Mapping

By organizing and exploring your current knowledge, you might find an area of interest for your research project. A mind-map, also known as a “web” or “cluster,” is a graphic representation of your thought processes. Since this form allows for digressions, free association, and wandering, it allows for organic thinking and knowledge-building.

Once you’ve finished your mind-map, review the idea or clusters of ideas that seem to demand your attention. Did any of your bubbles or connections surprise you? Do you see any patterns? Which were most engaging to meditate on? From these topics and subtopics, try to articulate a viable and interesting research question that speaks to your curiosity. Make sure its scope is appropriate to your rhetorical situation; you can use the exercise “Focus: Expanding and Contracting Scope” later in this chapter to help expand or narrow your scope.

Idea Generation: Internet Stumbling

In addition to its status as an ever-expanding repository of knowledge, and in addition to its contributions to global human connection, the Internet is also an exceptional free association machine. Through the magic of hyperlinks and social media, random chance can set us in the right direction to develop a research topic. Spend fifteen to twenty minutes clicking around on the Internet, using one of the following media for guidance, and jot down every potential topic that piques your interest.

• Wikipedia : Go to the Wikipedia homepage and check out the “featured article” of the day, or choose “Random Article” from the sidebar on the far left. Click any of the hyperlinks in the article to redirect to a different page. Bounce from article to article, keeping track of the titles of pages and sections catch your eye.
• StumbleUpon : Set up a free account from this interest randomizer. You can customize what kinds of pages, topics, and media you want to see.
• An Instagram, Facebook, reddit, or Twitter feed : Flow through one or more social media feeds, using links, geotags, user handles, and hashtags to encounter a variety of posts.

After stumbling, review the list you’ve made of potentially interesting topics. Are you already familiar with any of them? Which surprised you? Are there any relationships or intersections worth exploring further? From these topics and subtopics, try to articulate a viable and interesting research question that speaks to your curiosity. Make sure its scope is appropriate to your rhetorical situation; you can use the exercise “Focus: Expanding and Contracting Scope” later in this chapter to help expand or narrow your scope.

Focus: Expanding and Contracting Scope

At this point, you have hopefully identified some topic or path of inquiry for your research project. In order to experiment with scope, try complicating your research question(s) along the different dimensions in the following table. A completed table is included as an example after the blank one.

Model Texts by Student Authors

Pirates & anarchy 7.

(Research proposal – see the annotated bibliography here and final essay here)

My inquiry has to do with piracy and its relationship with anarchist culture. There seem to be two tipping points to the life cycles of piratical and anarchist cultures. First, there is the societal inequality and/or economic stagnation that cause groups to lose faith in established power structures (Samatar 1377). This disenfranchisement leads to groups’ choosing to take self-guided action, to meet needs not satisfied. It is a bid for freedom. The other shift appears to be when the actions of the group become predatory upon vulnerable groups. What begins as notions of self-sufficiency become violent victimizations of other segments of society (Wilson ix).

The current guiding questions that I am following are these: What societal breakdowns lead to groups subscribing to anarchist philosophies? Are pirates and anarchists synonymous? Do the successes and/or failures of pirate organizations create any lasting change in the societies from which they spring?

Piracy has been around for a very long time and has taken on many forms. One of these incarnations was the seafaring sort terrorizing ships during the golden age of piracy in the seventeenth century. Another example was the Somali pirates preying on the African coast in the early 2000s. Information pirates in cyberspace and anarchist protestors in political activism are current forms. The relevance of why individuals turn to piracy is important to explore.

Political polarization continues to freeze up the government, rendering them ineffectual. Worse, elected officials appear more concerned with ideology and campaign funding than the plight of the common man, leaving their own constituents’ needs abandoned. Citizens may turn to extreme political philosophies such as anarchy as a way to take piratical action to counteract economic disparity. A pervasive sense of powerlessness and underrepresentation may lead to the splintering of societal structure, even rebellion. Of import is understanding whether acts of piracy lead to societal erosion via this loss of faith and turn to violence, shrugging off accountability to the system as a countermeasure to what is seen as government’s inability to provide a free and fair system. This may be seen as empowering. It may also signal a breakdown of centralized government.

There are several difficulties I anticipate. Dedicating time in an efficient manner is the main concern with managing this project. This topic will require a lot of exploration in research. At the same time, writing and revising need their fair share of dedication. I’m looking to find that balance so each aspect of the process gets its due. I will handle this by utilizing the strategy of setting a timer for research and then for writing. A little of both will get done each day, with greater allotments of time given to writing as I go along.

Also of concern is narrowing this topic further. The phenomenon of piracy is so interesting to me, especially in the context of history. However, considering how this topic may be relevant in the current shifting political landscape, it seems important to dwell on the now as well as the past. Much has been written already on piracy, so I’ll be going into the research looking for a more focused place where I can contribute to the subject matter. I’m going to set up a couple of writing center appointments to get some guidance as I go along.

Finally, I want to be watchful of wandering. Many side paths are open to inspection with this topic. Not only will this waste time, but it will also weaken my argument. Once I tighten up the thesis, I want to make sure my research and writing stay focused.

Teacher Takeaways

“The proposal introduces the subject well and identifies guiding questions (and some context) clearly. However, the questions are not yet specific or complex enough to act as the essay’s central research question; the main components (pirates and anarchy) are still too general. Choosing a type of piracy (and perhaps a location), for instance, would lend context and definition to “anarchy” as it is considered here. Then the stakes may be clearly determined. Everything rides on greater specificity. That said, the author has done well to convert an interest into a compelling and unique line of inquiry — an important first step.”– Professor Fiscaletti

Samatar, Abdi Ismail, Lindberg, Mark, and Mahayni, Basil. “The Dialectics of Piracy in Somalia: The Rich Versus the Poor.” Third World Quarterly , vol. 31, no. 8, 2010, pp. 1377-1394. EBSCOhost , doi: 10.1080/01436597.2010.538238 .

Wilson, Peter Lamborn. Preface. The Devil ’ s Anarchy: The Sea Robberies of the Most Famous Pirate Claes G. Compaen and The Very Remarkable Travels of Jan Erasmus Reyning , Buccaneer by Stephen Snelders, Autonomedia , 2005, pp. vii-xi.

A Case of Hysterics 8

The concept of female Hysteria was a medical recognition dating back to the 13th century that has been diagnosed by physicians quite liberally until recent times. The diagnosis and treatment of Hysteria were routine for hundreds of years in Western Europe, as well as the United States. Symptoms that indicated Hysteria were broad and all encompassing: nervousness, sexual desire, faintness, insomnia, irritability, loss of appetite, depression, heaviness in abdomen, etc. These symptoms were said to be caused by a “wandering womb,” described as a kind of living creature that sought to disrupt biological processes, disrupt breathing, and cause disease.

The number of diagnosed cases of hysteria slowed as medical advancements proceeded, and in the early 1960s (coinciding with the popularization of feminism) the “disease” ceased to be considered a true medical disorder. In modern medicine, however, the treatment and diagnosis of female medical issues continues to be vague and potentially harmful due to lack of knowledge. Does the concept of female hysteria have continuity today?

Although the vocabulary has changed, it is clear that the practice of ignoring serious medical ailments based on sex remains prominent in the world of medicine. It is not uncommon for a physician to diagnose a woman with chronic stress or psychosomatic issues, and then later discover a disease like lupus, fibromyalgia, or polycystic ovarian syndrome, all of which are still commonly dismissed because it is likely the patient is experiencing the chronic pain in their heads. Because of sexism in the medical field, many women are receiving subpar healthcare. In my research, I will examine the past culture of Hysteria as well as the current state of misdiagnoses of women’s health issues and how this reinforces gender norms in today’s society; this will demonstrate the need for eliminating bias and sexism in medicine.

In my research process, I imagine I will encounter difficulties in finding detailed scientific research in the misdiagnoses of women’s health, despite having found multiple accounts on non-scientific platforms. I also anticipate a possible attitude of mistrust coming from the audience because of this topic; it is common nature to trust doctors blindly, as well as the norm in our culture to assume women are irrational and excessive. Finally, it will be difficult to attribute sexism and bias simply to the idea of misidentification of ailments. While this is common, sexism has also contributed to, plainly, a lack of research and knowledge of female healthcare. Therefore, willful ignorance plays a role in the imbalance between male and female medicine as well. I will mention this concept briefly in my essay, but continue to focus on the idea of frequent female misdiagnosis and how this perpetuates preconceived notions of feminine temperament in society.

“The author takes the time to give historical context, and that is important for building the analogy referenced in the research question. However, the question itself, and the following discussion, lack some precision. What does ‘continuity’ mean here? What ‘notions of feminine temperament’ will be examined? Are they a cause or an effect of misdiagnosis? The author may already have a (hypo)thesis in mind, but the terms of the question must first be clarified. Still, the context and the discussion of gender theory and medicine indicate a researcher who is eager to synthesize information and join a larger discussion.”– Professor Fiscaletti

Wage Transparency and the Gender Divide 9

Discussing salaries with neighbors and especially colleagues is often an unthinkable offense against social mores in the United States. Pay secrecy has long been the norm in most of Western society, but it comes with an information imbalance during any salary negotiations. Lately, wage transparency has gained some legal foothold at the national level as a tool to combat gender wage disparity for equal work. Is pay transparency an effective tool to close the gender pay gap, or will it only succeed in making colleagues uncomfortable?

States have been successively passing local laws to reinforce prior national legislation protecting employees’ rights to share salary information, and recent hacks have made information public involuntarily. In some situations, like in Norway, wage transparency has been the law for years. Norway also has the third smallest wage gap in the world. Compensation also has an impact on self-esteem and performance, so the wage gap could be causing a systematic decrease in self-worth for women in the workforce relative to their male counterparts. I plan to research whether increased wage transparency would cause a decrease in the gender pay gap.

There are many readily available statistics on the wage gap, although it may be difficult to avoid politically polarized sources. I’m not sure how available analytical studies of pay transparency will be, although sites like Glassdoor have published some admittedly self-serving studies. It will be difficult, although interesting, to assess the issue of pay transparency and the wage gap, as they are both complex sociological issues.

“This student has chosen an interesting and focused topic for their inquiry-based research paper. I appreciate their anticipation of difficulties, too. Although I expect their understanding of the issue will evolve as they learn more about it, I would still encourage this author to spend some more time in this proposal hypothesizing about the connection between gender discrimination and pay secrecy; it’s not 100% clear to me how those important topics are related to each other. This is germane to my other major concern—that the student doesn’t appear to have done any research at this point. A couple of preliminary sources may provide guidance as the student wrestles with complex ideas.”– Professor Dawson

EmpoWORD: A Student-Centered Anthology and Handbook for College Writers Copyright © 2018 by Shane Abrams is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License , except where otherwise noted.

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• Chapter 8: Attitudes on Space Issues

Table of Contents

• Introduction
• Chapter 1: Patterns Underlying Public Views About Science
• Chapter 2: Climate Change and Energy Issues
• Chapter 3: Support for Government Funding
• Chapter 4: Evolution and Perceptions of Scientific Consensus
• Chapter 5: Public Views About Biomedical Issues
• Chapter 6: Public Opinion About Food
• Chapter 7: Opinion About the Use of Animals in Research
• About This Report
• Appendix A: About the General Public Survey

This chapter looks at the underpinnings of two attitudes related to space exploration. When it comes to government investment in the International Space Station, public views are influenced primarily by political factors and education. This pattern is in keeping with public views about government funding for science and engineering, more generally. When it comes to views about the place of astronauts in the future of the U.S. space program, men and women tend to diverge but there is little difference by education or political factors.

U.S. Investment in the Space Station

The Pew Research survey asked: “Do you think the space station has been a good investment for this country, or don’t you think so?”

Some 64% of the public say investment in the space station has been a good investment, 29% say it has not.

Gender, Age, Race and Ethnicity

Majorities of men and women, whites, blacks and Hispanics, and all age groups say the space station has been a good investment for the country. Younger adults, ages 18 to 49, are more likely than those ages 50 and older to say the space station has been a good investment. There are no differences on this question by gender or race and ethnicity.

Education and Knowledge

Those who have attended college or hold a college degree are more likely to say the space station has been a good investment for the country. Those with a postgraduate degree hold views that are about the same as those without such training, however. And those with a college degree in a scientific field do not differ significantly from those with degrees in other fields on this issue.

Those with more knowledge about science are more likely than those with less science knowledge to say the space station was a good investment.

Party and Ideology

There are no differences between party groups on opinion about the space station. But, liberals express more positive views than moderates or conservatives about the country’s investment in the space station.

Multivariate Analyses

A multivariate logistic regression finds that education is a significant predictor of views about investment in the space station with those holding a postgraduate degree (+0.13) as well as those holding a college degree (+0.13) more likely than those with a high school diploma or less schooling to say the space station has been a good investment for the country. Liberals are significantly more likely than moderates to hold a positive assessment of the country’s investment in the space station (a predicted difference in probabilities of 11 percentage points). Age differences in views about this issue approach but do not reach statistical significance at the 0.05 level. There are no significant differences by gender, party affiliation, race or ethnicity.

Human Astronauts and the U.S. Space Program

The Pew Research survey asked a question about the role of astronauts in the future as part of space exploration: “The cost of sending human astronauts to space is considerably greater than the cost of using robotic machines for space exploration. As you think about the future of the U.S. space program, do you think it is essential or not essential to include the use of human astronauts in space?”

A majority of the public (59%) says astronauts are essential to include in the future of the U.S. space program, while 39% say astronauts are not essential.

Men are more likely than women to say human astronauts are essential for the future of the U.S. space program (66% vs. 52%, respectively).There are no differences in views about this issue by age, race or ethnicity.

Views about this issue are roughly the same among education groups.

There are no differences among party or ideological groups on views about the role of astronauts in the future U.S. space program.

A multivariate logistic analysis finds just a few significant predictors of views on this issue. Men are more inclined than are women to say astronauts are essential in the future of the U.S. space program, controlling for other factors (11 percentage point difference in predicted probability). And Democrats and those who lean to the Democratic Party are more likely than those with no party affiliation or leaning to say that astronauts are essential going forward (14 percentage point difference in predicted probability). There are no significant differences between Republicans and independents who lean to the GOP and their Democratic counterparts, however.

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