chapter 2 research meaning

Research Methods

Chapter 2 introduction.

Maybe you have already gained some experience in doing research, for example in your bachelor studies, or as part of your work.

The challenge in conducting academic research at masters level, is that it is multi-faceted.

The types of activities are:

• Finding and reviewing literature on your research topic;
• Designing a research project that will answer your research questions;
• Collecting relevant data from one or more sources;
• Analyzing the data, statistically or otherwise, and
• Writing up and presenting your findings.

Some researchers are strong on some parts but weak on others.

We do not require perfection. But we do require high quality.

Going through all stages of the research project, with the guidance of your supervisor, is a learning process.

The journey is hard at times, but in the end your thesis is considered an academic publication, and we want you to be proud of what you have achieved!

Probably the biggest challenge is, where to begin?

• What will be your topic?
• And once you have selected a topic, what are the questions that you want to answer, and how?

In the first chapter of the book, you will find several views on the nature and scope of business research.

Since a study in business administration derives its relevance from its application to real-life situations, an MBA typically falls in the grey area between applied research and basic research.

The focus of applied research is on finding solutions to problems, and on improving (y)our understanding of existing theories of management.

Applied research that makes use of existing theories, often leads to amendments or refinements of these theories. That is, the applied research feeds back to basic research.

In the early stages of your research, you will feel like you are running around in circles.

You start with an idea for a research topic. Then, after reading literature on the topic, you will revise or refine your idea. And start reading again with a clearer focus ...

A thesis research/project typically consists of two main stages.

The first stage is the research proposal .

Once the research proposal has been approved, you can start with the data collection, analysis and write-up (including conclusions and recommendations).

Stage 1, the research proposal consists of he first three chapters of the commonly used five-chapter structure :

• Chapter 1: Introduction
• An introduction to the topic.
• The research questions that you want to answer (and/or hypotheses that you want to test).
• A note on why the research is of academic and/or professional relevance.
• Chapter 2: Literature
• A review of relevant literature on the topic.
• Chapter 3: Methodology

The methodology is at the core of your research. Here, you define how you are going to do the research. What data will be collected, and how?

Your data should allow you to answer your research questions. In the research proposal, you will also provide answers to the questions when and how much . Is it feasible to conduct the research within the given time-frame (say, 3-6 months for a typical master thesis)? And do you have the resources to collect and analyze the data?

In stage 2 you collect and analyze the data, and write the conclusions.

• Chapter 4: Data Analysis and Findings
• Chapter 5: Summary, Conclusions and Recommendations

This video gives a nice overview of the elements of writing a thesis.

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2 Chapter 2: Principles of Research

Principles of research, 2.1  basic concepts.

Before we address where research questions in psychology come from—and what makes them more or less interesting—it is important to understand the kinds of questions that researchers in psychology typically ask. This requires a quick introduction to several basic concepts, many of which we will return to in more detail later in the book.

Research questions in psychology are about variables. A variable is a quantity or quality that varies across people or situations. For example, the height of the students in a psychology class is a variable because it varies from student to student. The sex of the students is also a variable as long as there are both male and female students in the class. A quantitative variable is a quantity, such as height, that is typically measured by assigning a number to each individual. Other examples of quantitative variables include people’s level of talkativeness, how depressed they are, and the number of siblings they have. A categorical variable is a quality, such as sex, and is typically measured by assigning a category label to each individual. Other examples include people’s nationality, their occupation, and whether they are receiving psychotherapy.

“Lots of Candy Could Lead to Violence”

Although researchers in psychology know that  correlation does not imply causation , many journalists do not. Many headlines suggest that a causal relationship has been demonstrated, when a careful reading of the articles shows that it has not because of the directionality and third-variable problems.

One article is about a study showing that children who ate candy every day were more likely than other children to be arrested for a violent offense later in life. But could candy really “lead to” violence, as the headline suggests? What alternative explanations can you think of for this statistical relationship? How could the headline be rewritten so that it is not misleading?

As we will see later in the book, there are various ways that researchers address the directionality and third-variable problems. The most effective, however, is to conduct an experiment. An experiment is a study in which the researcher manipulates the independent variable. For example, instead of simply measuring how much people exercise, a researcher could bring people into a laboratory and randomly assign half of them to run on a treadmill for 15 minutes and the rest to sit on a couch for 15 minutes. Although this seems like a minor addition to the research design, it is extremely important. Now if the exercisers end up in more positive moods than those who did not exercise, it cannot be because their moods affected how much they exercised (because it was the researcher who determined how much they exercised). Likewise, it cannot be because some third variable (e.g., physical health) affected both how much they exercised and what mood they were in (because, again, it was the researcher who determined how much they exercised). Thus experiments eliminate the directionality and third-variable problems and allow researchers to draw firm conclusions about causal relationships.

2.2  Generating Good Research Questions

Good research must begin with a good research question. Yet coming up with good research questions is something that novice researchers often find difficult and stressful. One reason is that this is a creative process that can appear mysterious—even magical—with experienced researchers seeming to pull interesting research questions out of thin air. However, psychological research on creativity has shown that it is neither as mysterious nor as magical as it appears. It is largely the product of ordinary thinking strategies and persistence (Weisberg, 1993). This section covers some fairly simple strategies for finding general research ideas, turning those ideas into empirically testable research questions, and finally evaluating those questions in terms of how interesting they are and how feasible they would be to answer.

Finding Inspiration

Research questions often begin as more general research ideas—usually focusing on some behaviour or psychological characteristic: talkativeness, memory for touches, depression, bungee jumping, and so on. Before looking at how to turn such ideas into empirically testable research questions, it is worth looking at where such ideas come from in the first place. Three of the most common sources of inspiration are informal observations, practical problems, and previous research.

Informal observations include direct observations of our own and others’ behaviour as well as secondhand observations from nonscientific sources such as newspapers, books, and so on. For example, you might notice that you always seem to be in the slowest moving line at the grocery store. Could it be that most people think the same thing? Or you might read in the local newspaper about people donating money and food to a local family whose house has burned down and begin to wonder about who makes such donations and why. Some of the most famous research in psychology has been inspired by informal observations. Stanley Milgram’s famous research on obedience, for example, was inspired in part by journalistic reports of the trials of accused Nazi war criminals—many of whom claimed that they were only obeying orders. This led him to wonder about the extent to which ordinary people will commit immoral acts simply because they are ordered to do so by an authority figure (Milgram, 1963).

Practical problems can also inspire research ideas, leading directly to applied research in such domains as law, health, education, and sports. Can human figure drawings help children remember details about being physically or sexually abused? How effective is psychotherapy for depression compared to drug therapy? To what extent do cell phones impair people’s driving ability? How can we teach children to read more efficiently? What is the best mental preparation for running a marathon?

Probably the most common inspiration for new research ideas, however, is previous research. Recall that science is a kind of large-scale collaboration in which many different researchers read and evaluate each other’s work and conduct new studies to build on it. Of course, experienced researchers are familiar with previous research in their area of expertise and probably have a long list of ideas. This suggests that novice researchers can find inspiration by consulting with a more experienced researcher (e.g., students can consult a faculty member). But they can also find inspiration by picking up a copy of almost any professional journal and reading the titles and abstracts. In one typical issue of Psychological Science, for example, you can find articles on the perception of shapes, anti-Semitism, police lineups, the meaning of death, second-language learning, people who seek negative emotional experiences, and many other topics. If you can narrow your interests down to a particular topic (e.g., memory) or domain (e.g., health care), you can also look through more specific journals, such as Memory Cognition or Health Psychology.

Generating Empirically Testable Research Questions

Once you have a research idea, you need to use it to generate one or more empirically testable research questions, that is, questions expressed in terms of a single variable or relationship between variables. One way to do this is to look closely at the discussion section in a recent research article on the topic. This is the last major section of the article, in which the researchers summarize their results, interpret them in the context of past research, and suggest directions for future research. These suggestions often take the form of specific research questions, which you can then try to answer with additional research. This can be a good strategy because it is likely that the suggested questions have already been identified as interesting and important by experienced researchers.

But you may also want to generate your own research questions. How can you do this? First, if you have a particular behaviour or psychological characteristic in mind, you can simply conceptualize it as a variable and ask how frequent or intense it is. How many words on average do people speak per day? How accurate are children’s memories of being touched? What percentage of people have sought professional help for depression? If the question has never been studied scientifically—which is something that you will learn in your literature review—then it might be interesting and worth pursuing.

If scientific research has already answered the question of how frequent or intense the behaviour or characteristic is, then you should consider turning it into a question about a statistical relationship between that behaviour or characteristic and some other variable. One way to do this is to ask yourself the following series of more general questions and write down all the answers you can think of.

·         What are some possible causes of the behaviour or characteristic?

·         What are some possible effects of the behaviour or characteristic?

·         What types of people might exhibit more or less of the behaviour or characteristic?

·         What types of situations might elicit more or less of the behaviour or characteristic?

In general, each answer you write down can be conceptualized as a second variable, suggesting a question about a statistical relationship. If you were interested in talkativeness, for example, it might occur to you that a possible cause of this psychological characteristic is family size. Is there a statistical relationship between family size and talkativeness? Or it might occur to you that people seem to be more talkative in same-sex groups than mixed-sex groups. Is there a difference in the average level of talkativeness of people in same-sex groups and people in mixed-sex groups? This approach should allow you to generate many different empirically testable questions about almost any behaviour or psychological characteristic.

If through this process you generate a question that has never been studied scientifically—which again is something that you will learn in your literature review—then it might be interesting and worth pursuing. But what if you find that it has been studied scientifically? Although novice researchers often want to give up and move on to a new question at this point, this is not necessarily a good strategy. For one thing, the fact that the question has been studied scientifically and the research published suggests that it is of interest to the scientific community. For another, the question can almost certainly be refined so that its answer will still contribute something new to the research literature. Again, asking yourself a series of more general questions about the statistical relationship is a good strategy.

·         Are there other ways to operationally define the variables?

·         Are there types of people for whom the statistical relationship might be stronger or weaker?

·         Are there situations in which the statistical relationship might be stronger or weaker—including situations with practical importance?

For example, research has shown that women and men speak about the same number of words per day—but this was when talkativeness was measured in terms of the number of words spoken per day among college students in the United States and Mexico. We can still ask whether other ways of measuring talkativeness—perhaps the number of different people spoken to each day—produce the same result. Or we can ask whether studying elderly people or people from other cultures produces the same result. Again, this approach should help you generate many different research questions about almost any statistical relationship.

2.3  Evaluating Research Questions

Researchers usually generate many more research questions than they ever attempt to answer. This means they must have some way of evaluating the research questions they generate so that they can choose which ones to pursue. In this section, we consider two criteria for evaluating research questions: the interestingness of the question and the feasibility of answering it.

Interestingness

How often do people tie their shoes? Do people feel pain when you punch them in the jaw? Are women more likely to wear makeup than men? Do people prefer vanilla or chocolate ice cream? Although it would be a fairly simple matter to design a study and collect data to answer these questions, you probably would not want to because they are not interesting. We are not talking here about whether a research question is interesting to us personally but whether it is interesting to people more generally and, especially, to the scientific community. But what makes a research question interesting in this sense? Here we look at three factors that affect the interestingness of a research question: the answer is in doubt, the answer fills a gap in the research literature, and the answer has important practical implications.

First, a research question is interesting to the extent that its answer is in doubt. Obviously, questions that have been answered by scientific research are no longer interesting as the subject of new empirical research. But the fact that a question has not been answered by scientific research does not necessarily make it interesting. There has to be some reasonable chance that the answer to the question will be something that we did not already know. But how can you assess this before actually collecting data? One approach is to try to think of reasons to expect different answers to the question—especially ones that seem to conflict with common sense. If you can think of reasons to expect at least two different answers, then the question might be interesting. If you can think of reasons to expect only one answer, then it probably is not. The question of whether women are more talkative than men is interesting because there are reasons to expect both answers. The existence of the stereotype itself suggests the answer could be yes, but the fact that women’s and men’s verbal abilities are fairly similar suggests the answer could be no. The question of whether people feel pain when you punch them in the jaw is not interesting because there is absolutely no reason to think that the answer could be anything other than a resounding yes.

A second important factor to consider when deciding if a research question is interesting is whether answering it will fill a gap in the research literature. Again, this means in part that the question has not already been answered by scientific research. But it also means that the question is in some sense a natural one for people who are familiar with the research literature. For example, the question of whether human figure drawings can help children recall touch information would be likely to occur to anyone who was familiar with research on the unreliability of eyewitness memory (especially in children) and the ineffectiveness of some alternative interviewing techniques.

A final factor to consider when deciding whether a research question is interesting is whether its answer has important practical implications. Again, the question of whether human figure drawings help children recall information about being touched has important implications for how children are interviewed in physical and sexual abuse cases. The question of whether cell phone use impairs driving is interesting because it is relevant to the personal safety of everyone who travels by car and to the debate over whether cell phone use should be restricted by law.

Feasibility

A second important criterion for evaluating research questions is the feasibility of successfully answering them. There are many factors that affect feasibility, including time, money, equipment and materials, technical knowledge and skill, and access to research participants. Clearly, researchers need to take these factors into account so that they do not waste time and effort pursuing research that they cannot complete successfully.

Looking through a sample of professional journals in psychology will reveal many studies that are complicated and difficult to carry out. These include longitudinal designs in which participants are tracked over many years, neuroimaging studies in which participants’ brain activity is measured while they carry out various mental tasks, and complex non-experimental studies involving several variables and complicated statistical analyses. Keep in mind, though, that such research tends to be carried out by teams of highly trained researchers whose work is often supported in part by government and private grants. Keep in mind also that research does not have to be complicated or difficult to produce interesting and important results. Looking through a sample of professional journals will also reveal studies that are relatively simple and easy to carry out—perhaps involving a convenience sample of college students and a paper-and-pencil task.

A final point here is that it is generally good practice to use methods that have already been used successfully by other researchers. For example, if you want to manipulate people’s moods to make some of them happy, it would be a good idea to use one of the many approaches that have been used successfully by other researchers (e.g., paying them a compliment). This is good not only for the sake of feasibility—the approach is “tried and true”—but also because it provides greater continuity with previous research. This makes it easier to compare your results with those of other researchers and to understand the implications of their research for yours, and vice versa.

Key Takeaways

·         Research ideas can come from a variety of sources, including informal observations, practical problems, and previous research.

·         Research questions expressed in terms of variables and relationships between variables can be suggested by other researchers or generated by asking a series of more general questions about the behaviour or psychological characteristic of interest.

·         It is important to evaluate how interesting a research question is before designing a study and collecting data to answer it. Factors that affect interestingness are the extent to which the answer is in doubt, whether it fills a gap in the research literature, and whether it has important practical implications.

·         It is also important to evaluate how feasible a research question will be to answer. Factors that affect feasibility include time, money, technical knowledge and skill, and access to special equipment and research participants.

References from Chapter 2

Milgram, S. (1963). Behavioral study of obedience. Journal of Abnormal and Social Psychology, 67, 371–378.

Stanovich, K. E. (2010). How to think straight about psychology (9th ed.). Boston, MA: Allyn Bacon.

Weisberg, R. W. (1993). Creativity: Beyond the myth of genius. New York, NY: Freeman.

Research Methods in Psychology & Neuroscience Copyright © by Dalhousie University Introduction to Psychology and Neuroscience Team. All Rights Reserved.

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Chapter 2. Research Design

Getting started.

When I teach undergraduates qualitative research methods, the final product of the course is a “research proposal” that incorporates all they have learned and enlists the knowledge they have learned about qualitative research methods in an original design that addresses a particular research question. I highly recommend you think about designing your own research study as you progress through this textbook. Even if you don’t have a study in mind yet, it can be a helpful exercise as you progress through the course. But how to start? How can one design a research study before they even know what research looks like? This chapter will serve as a brief overview of the research design process to orient you to what will be coming in later chapters. Think of it as a “skeleton” of what you will read in more detail in later chapters. Ideally, you will read this chapter both now (in sequence) and later during your reading of the remainder of the text. Do not worry if you have questions the first time you read this chapter. Many things will become clearer as the text advances and as you gain a deeper understanding of all the components of good qualitative research. This is just a preliminary map to get you on the right road.

Research Design Steps

Before you even get started, you will need to have a broad topic of interest in mind. [1] . In my experience, students can confuse this broad topic with the actual research question, so it is important to clearly distinguish the two. And the place to start is the broad topic. It might be, as was the case with me, working-class college students. But what about working-class college students? What’s it like to be one? Why are there so few compared to others? How do colleges assist (or fail to assist) them? What interested me was something I could barely articulate at first and went something like this: “Why was it so difficult and lonely to be me?” And by extension, “Did others share this experience?”

Once you have a general topic, reflect on why this is important to you. Sometimes we connect with a topic and we don’t really know why. Even if you are not willing to share the real underlying reason you are interested in a topic, it is important that you know the deeper reasons that motivate you. Otherwise, it is quite possible that at some point during the research, you will find yourself turned around facing the wrong direction. I have seen it happen many times. The reason is that the research question is not the same thing as the general topic of interest, and if you don’t know the reasons for your interest, you are likely to design a study answering a research question that is beside the point—to you, at least. And this means you will be much less motivated to carry your research to completion.

Researcher Note

Why do you employ qualitative research methods in your area of study? What are the advantages of qualitative research methods for studying mentorship?

Qualitative research methods are a huge opportunity to increase access, equity, inclusion, and social justice. Qualitative research allows us to engage and examine the uniquenesses/nuances within minoritized and dominant identities and our experiences with these identities. Qualitative research allows us to explore a specific topic, and through that exploration, we can link history to experiences and look for patterns or offer up a unique phenomenon. There’s such beauty in being able to tell a particular story, and qualitative research is a great mode for that! For our work, we examined the relationships we typically use the term mentorship for but didn’t feel that was quite the right word. Qualitative research allowed us to pick apart what we did and how we engaged in our relationships, which then allowed us to more accurately describe what was unique about our mentorship relationships, which we ultimately named liberationships ( McAloney and Long 2021) . Qualitative research gave us the means to explore, process, and name our experiences; what a powerful tool!

How do you come up with ideas for what to study (and how to study it)? Where did you get the idea for studying mentorship?

Coming up with ideas for research, for me, is kind of like Googling a question I have, not finding enough information, and then deciding to dig a little deeper to get the answer. The idea to study mentorship actually came up in conversation with my mentorship triad. We were talking in one of our meetings about our relationship—kind of meta, huh? We discussed how we felt that mentorship was not quite the right term for the relationships we had built. One of us asked what was different about our relationships and mentorship. This all happened when I was taking an ethnography course. During the next session of class, we were discussing auto- and duoethnography, and it hit me—let’s explore our version of mentorship, which we later went on to name liberationships ( McAloney and Long 2021 ). The idea and questions came out of being curious and wanting to find an answer. As I continue to research, I see opportunities in questions I have about my work or during conversations that, in our search for answers, end up exposing gaps in the literature. If I can’t find the answer already out there, I can study it.

—Kim McAloney, PhD, College Student Services Administration Ecampus coordinator and instructor

When you have a better idea of why you are interested in what it is that interests you, you may be surprised to learn that the obvious approaches to the topic are not the only ones. For example, let’s say you think you are interested in preserving coastal wildlife. And as a social scientist, you are interested in policies and practices that affect the long-term viability of coastal wildlife, especially around fishing communities. It would be natural then to consider designing a research study around fishing communities and how they manage their ecosystems. But when you really think about it, you realize that what interests you the most is how people whose livelihoods depend on a particular resource act in ways that deplete that resource. Or, even deeper, you contemplate the puzzle, “How do people justify actions that damage their surroundings?” Now, there are many ways to design a study that gets at that broader question, and not all of them are about fishing communities, although that is certainly one way to go. Maybe you could design an interview-based study that includes and compares loggers, fishers, and desert golfers (those who golf in arid lands that require a great deal of wasteful irrigation). Or design a case study around one particular example where resources were completely used up by a community. Without knowing what it is you are really interested in, what motivates your interest in a surface phenomenon, you are unlikely to come up with the appropriate research design.

These first stages of research design are often the most difficult, but have patience . Taking the time to consider why you are going to go through a lot of trouble to get answers will prevent a lot of wasted energy in the future.

There are distinct reasons for pursuing particular research questions, and it is helpful to distinguish between them.  First, you may be personally motivated.  This is probably the most important and the most often overlooked.   What is it about the social world that sparks your curiosity? What bothers you? What answers do you need in order to keep living? For me, I knew I needed to get a handle on what higher education was for before I kept going at it. I needed to understand why I felt so different from my peers and whether this whole “higher education” thing was “for the likes of me” before I could complete my degree. That is the personal motivation question. Your personal motivation might also be political in nature, in that you want to change the world in a particular way. It’s all right to acknowledge this. In fact, it is better to acknowledge it than to hide it.

There are also academic and professional motivations for a particular study.  If you are an absolute beginner, these may be difficult to find. We’ll talk more about this when we discuss reviewing the literature. Simply put, you are probably not the only person in the world to have thought about this question or issue and those related to it. So how does your interest area fit into what others have studied? Perhaps there is a good study out there of fishing communities, but no one has quite asked the “justification” question. You are motivated to address this to “fill the gap” in our collective knowledge. And maybe you are really not at all sure of what interests you, but you do know that [insert your topic] interests a lot of people, so you would like to work in this area too. You want to be involved in the academic conversation. That is a professional motivation and a very important one to articulate.

Practical and strategic motivations are a third kind. Perhaps you want to encourage people to take better care of the natural resources around them. If this is also part of your motivation, you will want to design your research project in a way that might have an impact on how people behave in the future. There are many ways to do this, one of which is using qualitative research methods rather than quantitative research methods, as the findings of qualitative research are often easier to communicate to a broader audience than the results of quantitative research. You might even be able to engage the community you are studying in the collecting and analyzing of data, something taboo in quantitative research but actively embraced and encouraged by qualitative researchers. But there are other practical reasons, such as getting “done” with your research in a certain amount of time or having access (or no access) to certain information. There is nothing wrong with considering constraints and opportunities when designing your study. Or maybe one of the practical or strategic goals is about learning competence in this area so that you can demonstrate the ability to conduct interviews and focus groups with future employers. Keeping that in mind will help shape your study and prevent you from getting sidetracked using a technique that you are less invested in learning about.

STOP HERE for a moment

I recommend you write a paragraph (at least) explaining your aims and goals. Include a sentence about each of the following: personal/political goals, practical or professional/academic goals, and practical/strategic goals. Think through how all of the goals are related and can be achieved by this particular research study . If they can’t, have a rethink. Perhaps this is not the best way to go about it.

You will also want to be clear about the purpose of your study. “Wait, didn’t we just do this?” you might ask. No! Your goals are not the same as the purpose of the study, although they are related. You can think about purpose lying on a continuum from “ theory ” to “action” (figure 2.1). Sometimes you are doing research to discover new knowledge about the world, while other times you are doing a study because you want to measure an impact or make a difference in the world.

Basic research involves research that is done for the sake of “pure” knowledge—that is, knowledge that, at least at this moment in time, may not have any apparent use or application. Often, and this is very important, knowledge of this kind is later found to be extremely helpful in solving problems. So one way of thinking about basic research is that it is knowledge for which no use is yet known but will probably one day prove to be extremely useful. If you are doing basic research, you do not need to argue its usefulness, as the whole point is that we just don’t know yet what this might be.

Researchers engaged in basic research want to understand how the world operates. They are interested in investigating a phenomenon to get at the nature of reality with regard to that phenomenon. The basic researcher’s purpose is to understand and explain ( Patton 2002:215 ).

Basic research is interested in generating and testing hypotheses about how the world works. Grounded Theory is one approach to qualitative research methods that exemplifies basic research (see chapter 4). Most academic journal articles publish basic research findings. If you are working in academia (e.g., writing your dissertation), the default expectation is that you are conducting basic research.

Applied research in the social sciences is research that addresses human and social problems. Unlike basic research, the researcher has expectations that the research will help contribute to resolving a problem, if only by identifying its contours, history, or context. From my experience, most students have this as their baseline assumption about research. Why do a study if not to make things better? But this is a common mistake. Students and their committee members are often working with default assumptions here—the former thinking about applied research as their purpose, the latter thinking about basic research: “The purpose of applied research is to contribute knowledge that will help people to understand the nature of a problem in order to intervene, thereby allowing human beings to more effectively control their environment. While in basic research the source of questions is the tradition within a scholarly discipline, in applied research the source of questions is in the problems and concerns experienced by people and by policymakers” ( Patton 2002:217 ).

Applied research is less geared toward theory in two ways. First, its questions do not derive from previous literature. For this reason, applied research studies have much more limited literature reviews than those found in basic research (although they make up for this by having much more “background” about the problem). Second, it does not generate theory in the same way as basic research does. The findings of an applied research project may not be generalizable beyond the boundaries of this particular problem or context. The findings are more limited. They are useful now but may be less useful later. This is why basic research remains the default “gold standard” of academic research.

Evaluation research is research that is designed to evaluate or test the effectiveness of specific solutions and programs addressing specific social problems. We already know the problems, and someone has already come up with solutions. There might be a program, say, for first-generation college students on your campus. Does this program work? Are first-generation students who participate in the program more likely to graduate than those who do not? These are the types of questions addressed by evaluation research. There are two types of research within this broader frame; however, one more action-oriented than the next. In summative evaluation , an overall judgment about the effectiveness of a program or policy is made. Should we continue our first-gen program? Is it a good model for other campuses? Because the purpose of such summative evaluation is to measure success and to determine whether this success is scalable (capable of being generalized beyond the specific case), quantitative data is more often used than qualitative data. In our example, we might have “outcomes” data for thousands of students, and we might run various tests to determine if the better outcomes of those in the program are statistically significant so that we can generalize the findings and recommend similar programs elsewhere. Qualitative data in the form of focus groups or interviews can then be used for illustrative purposes, providing more depth to the quantitative analyses. In contrast, formative evaluation attempts to improve a program or policy (to help “form” or shape its effectiveness). Formative evaluations rely more heavily on qualitative data—case studies, interviews, focus groups. The findings are meant not to generalize beyond the particular but to improve this program. If you are a student seeking to improve your qualitative research skills and you do not care about generating basic research, formative evaluation studies might be an attractive option for you to pursue, as there are always local programs that need evaluation and suggestions for improvement. Again, be very clear about your purpose when talking through your research proposal with your committee.

Action research takes a further step beyond evaluation, even formative evaluation, to being part of the solution itself. This is about as far from basic research as one could get and definitely falls beyond the scope of “science,” as conventionally defined. The distinction between action and research is blurry, the research methods are often in constant flux, and the only “findings” are specific to the problem or case at hand and often are findings about the process of intervention itself. Rather than evaluate a program as a whole, action research often seeks to change and improve some particular aspect that may not be working—maybe there is not enough diversity in an organization or maybe women’s voices are muted during meetings and the organization wonders why and would like to change this. In a further step, participatory action research , those women would become part of the research team, attempting to amplify their voices in the organization through participation in the action research. As action research employs methods that involve people in the process, focus groups are quite common.

If you are working on a thesis or dissertation, chances are your committee will expect you to be contributing to fundamental knowledge and theory ( basic research ). If your interests lie more toward the action end of the continuum, however, it is helpful to talk to your committee about this before you get started. Knowing your purpose in advance will help avoid misunderstandings during the later stages of the research process!

The Research Question

Once you have written your paragraph and clarified your purpose and truly know that this study is the best study for you to be doing right now , you are ready to write and refine your actual research question. Know that research questions are often moving targets in qualitative research, that they can be refined up to the very end of data collection and analysis. But you do have to have a working research question at all stages. This is your “anchor” when you get lost in the data. What are you addressing? What are you looking at and why? Your research question guides you through the thicket. It is common to have a whole host of questions about a phenomenon or case, both at the outset and throughout the study, but you should be able to pare it down to no more than two or three sentences when asked. These sentences should both clarify the intent of the research and explain why this is an important question to answer. More on refining your research question can be found in chapter 4.

Chances are, you will have already done some prior reading before coming up with your interest and your questions, but you may not have conducted a systematic literature review. This is the next crucial stage to be completed before venturing further. You don’t want to start collecting data and then realize that someone has already beaten you to the punch. A review of the literature that is already out there will let you know (1) if others have already done the study you are envisioning; (2) if others have done similar studies, which can help you out; and (3) what ideas or concepts are out there that can help you frame your study and make sense of your findings. More on literature reviews can be found in chapter 9.

In addition to reviewing the literature for similar studies to what you are proposing, it can be extremely helpful to find a study that inspires you. This may have absolutely nothing to do with the topic you are interested in but is written so beautifully or organized so interestingly or otherwise speaks to you in such a way that you want to post it somewhere to remind you of what you want to be doing. You might not understand this in the early stages—why would you find a study that has nothing to do with the one you are doing helpful? But trust me, when you are deep into analysis and writing, having an inspirational model in view can help you push through. If you are motivated to do something that might change the world, you probably have read something somewhere that inspired you. Go back to that original inspiration and read it carefully and see how they managed to convey the passion that you so appreciate.

At this stage, you are still just getting started. There are a lot of things to do before setting forth to collect data! You’ll want to consider and choose a research tradition and a set of data-collection techniques that both help you answer your research question and match all your aims and goals. For example, if you really want to help migrant workers speak for themselves, you might draw on feminist theory and participatory action research models. Chapters 3 and 4 will provide you with more information on epistemologies and approaches.

Next, you have to clarify your “units of analysis.” What is the level at which you are focusing your study? Often, the unit in qualitative research methods is individual people, or “human subjects.” But your units of analysis could just as well be organizations (colleges, hospitals) or programs or even whole nations. Think about what it is you want to be saying at the end of your study—are the insights you are hoping to make about people or about organizations or about something else entirely? A unit of analysis can even be a historical period! Every unit of analysis will call for a different kind of data collection and analysis and will produce different kinds of “findings” at the conclusion of your study. [2]

Regardless of what unit of analysis you select, you will probably have to consider the “human subjects” involved in your research. [3] Who are they? What interactions will you have with them—that is, what kind of data will you be collecting? Before answering these questions, define your population of interest and your research setting. Use your research question to help guide you.

Let’s use an example from a real study. In Geographies of Campus Inequality , Benson and Lee ( 2020 ) list three related research questions: “(1) What are the different ways that first-generation students organize their social, extracurricular, and academic activities at selective and highly selective colleges? (2) how do first-generation students sort themselves and get sorted into these different types of campus lives; and (3) how do these different patterns of campus engagement prepare first-generation students for their post-college lives?” (3).

Note that we are jumping into this a bit late, after Benson and Lee have described previous studies (the literature review) and what is known about first-generation college students and what is not known. They want to know about differences within this group, and they are interested in ones attending certain kinds of colleges because those colleges will be sites where academic and extracurricular pressures compete. That is the context for their three related research questions. What is the population of interest here? First-generation college students . What is the research setting? Selective and highly selective colleges . But a host of questions remain. Which students in the real world, which colleges? What about gender, race, and other identity markers? Will the students be asked questions? Are the students still in college, or will they be asked about what college was like for them? Will they be observed? Will they be shadowed? Will they be surveyed? Will they be asked to keep diaries of their time in college? How many students? How many colleges? For how long will they be observed?

Recommendation

Take a moment and write down suggestions for Benson and Lee before continuing on to what they actually did.

Have you written down your own suggestions? Good. Now let’s compare those with what they actually did. Benson and Lee drew on two sources of data: in-depth interviews with sixty-four first-generation students and survey data from a preexisting national survey of students at twenty-eight selective colleges. Let’s ignore the survey for our purposes here and focus on those interviews. The interviews were conducted between 2014 and 2016 at a single selective college, “Hilltop” (a pseudonym ). They employed a “purposive” sampling strategy to ensure an equal number of male-identifying and female-identifying students as well as equal numbers of White, Black, and Latinx students. Each student was interviewed once. Hilltop is a selective liberal arts college in the northeast that enrolls about three thousand students.

How did your suggestions match up to those actually used by the researchers in this study? It is possible your suggestions were too ambitious? Beginning qualitative researchers can often make that mistake. You want a research design that is both effective (it matches your question and goals) and doable. You will never be able to collect data from your entire population of interest (unless your research question is really so narrow to be relevant to very few people!), so you will need to come up with a good sample. Define the criteria for this sample, as Benson and Lee did when deciding to interview an equal number of students by gender and race categories. Define the criteria for your sample setting too. Hilltop is typical for selective colleges. That was a research choice made by Benson and Lee. For more on sampling and sampling choices, see chapter 5.

Benson and Lee chose to employ interviews. If you also would like to include interviews, you have to think about what will be asked in them. Most interview-based research involves an interview guide, a set of questions or question areas that will be asked of each participant. The research question helps you create a relevant interview guide. You want to ask questions whose answers will provide insight into your research question. Again, your research question is the anchor you will continually come back to as you plan for and conduct your study. It may be that once you begin interviewing, you find that people are telling you something totally unexpected, and this makes you rethink your research question. That is fine. Then you have a new anchor. But you always have an anchor. More on interviewing can be found in chapter 11.

Let’s imagine Benson and Lee also observed college students as they went about doing the things college students do, both in the classroom and in the clubs and social activities in which they participate. They would have needed a plan for this. Would they sit in on classes? Which ones and how many? Would they attend club meetings and sports events? Which ones and how many? Would they participate themselves? How would they record their observations? More on observation techniques can be found in both chapters 13 and 14.

At this point, the design is almost complete. You know why you are doing this study, you have a clear research question to guide you, you have identified your population of interest and research setting, and you have a reasonable sample of each. You also have put together a plan for data collection, which might include drafting an interview guide or making plans for observations. And so you know exactly what you will be doing for the next several months (or years!). To put the project into action, there are a few more things necessary before actually going into the field.

First, you will need to make sure you have any necessary supplies, including recording technology. These days, many researchers use their phones to record interviews. Second, you will need to draft a few documents for your participants. These include informed consent forms and recruiting materials, such as posters or email texts, that explain what this study is in clear language. Third, you will draft a research protocol to submit to your institutional review board (IRB) ; this research protocol will include the interview guide (if you are using one), the consent form template, and all examples of recruiting material. Depending on your institution and the details of your study design, it may take weeks or even, in some unfortunate cases, months before you secure IRB approval. Make sure you plan on this time in your project timeline. While you wait, you can continue to review the literature and possibly begin drafting a section on the literature review for your eventual presentation/publication. More on IRB procedures can be found in chapter 8 and more general ethical considerations in chapter 7.

Once you have approval, you can begin!

Research Design Checklist

Before data collection begins, do the following:

• Write a paragraph explaining your aims and goals (personal/political, practical/strategic, professional/academic).
• Define your research question; write two to three sentences that clarify the intent of the research and why this is an important question to answer.
• Review the literature for similar studies that address your research question or similar research questions; think laterally about some literature that might be helpful or illuminating but is not exactly about the same topic.
• Find a written study that inspires you—it may or may not be on the research question you have chosen.
• Consider and choose a research tradition and set of data-collection techniques that (1) help answer your research question and (2) match your aims and goals.
• Define your population of interest and your research setting.
• Define the criteria for your sample (How many? Why these? How will you find them, gain access, and acquire consent?).
• If you are conducting interviews, draft an interview guide.
•  If you are making observations, create a plan for observations (sites, times, recording, access).
• Acquire any necessary technology (recording devices/software).
• Draft consent forms that clearly identify the research focus and selection process.
• Create recruiting materials (posters, email, texts).
• Apply for IRB approval (proposal plus consent form plus recruiting materials).
• Block out time for collecting data.
• At the end of the chapter, you will find a " Research Design Checklist " that summarizes the main recommendations made here ↵
• For example, if your focus is society and culture , you might collect data through observation or a case study. If your focus is individual lived experience , you are probably going to be interviewing some people. And if your focus is language and communication , you will probably be analyzing text (written or visual). ( Marshall and Rossman 2016:16 ). ↵
• You may not have any "live" human subjects. There are qualitative research methods that do not require interactions with live human beings - see chapter 16 , "Archival and Historical Sources." But for the most part, you are probably reading this textbook because you are interested in doing research with people. The rest of the chapter will assume this is the case. ↵

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

A methodological tradition of inquiry and research design that focuses on an individual case (e.g., setting, institution, or sometimes an individual) in order to explore its complexity, history, and interactive parts.  As an approach, it is particularly useful for obtaining a deep appreciation of an issue, event, or phenomenon of interest in its particular context.

The controlling force in research; can be understood as lying on a continuum from basic research (knowledge production) to action research (effecting change).

In its most basic sense, a theory is a story we tell about how the world works that can be tested with empirical evidence.  In qualitative research, we use the term in a variety of ways, many of which are different from how they are used by quantitative researchers.  Although some qualitative research can be described as “testing theory,” it is more common to “build theory” from the data using inductive reasoning , as done in Grounded Theory .  There are so-called “grand theories” that seek to integrate a whole series of findings and stories into an overarching paradigm about how the world works, and much smaller theories or concepts about particular processes and relationships.  Theory can even be used to explain particular methodological perspectives or approaches, as in Institutional Ethnography , which is both a way of doing research and a theory about how the world works.

Research that is interested in generating and testing hypotheses about how the world works.

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

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

Research that contributes knowledge that will help people to understand the nature of a problem in order to intervene, thereby allowing human beings to more effectively control their environment.

Research that is designed to evaluate or test the effectiveness of specific solutions and programs addressing specific social problems.  There are two kinds: summative and formative .

Research in which an overall judgment about the effectiveness of a program or policy is made, often for the purpose of generalizing to other cases or programs.  Generally uses qualitative research as a supplement to primary quantitative data analyses.  Contrast formative evaluation research .

Research designed to improve a program or policy (to help “form” or shape its effectiveness); relies heavily on qualitative research methods.  Contrast summative evaluation research

Research carried out at a particular organizational or community site with the intention of affecting change; often involves research subjects as participants of the study.  See also participatory action research .

Research in which both researchers and participants work together to understand a problematic situation and change it for the better.

The level of the focus of analysis (e.g., individual people, organizations, programs, neighborhoods).

The large group of interest to the researcher.  Although it will likely be impossible to design a study that incorporates or reaches all members of the population of interest, this should be clearly defined at the outset of a study so that a reasonable sample of the population can be taken.  For example, if one is studying working-class college students, the sample may include twenty such students attending a particular college, while the population is “working-class college students.”  In quantitative research, clearly defining the general population of interest is a necessary step in generalizing results from a sample.  In qualitative research, defining the population is conceptually important for clarity.

A fictional name assigned to give anonymity to a person, group, or place.  Pseudonyms are important ways of protecting the identity of research participants while still providing a “human element” in the presentation of qualitative data.  There are ethical considerations to be made in selecting pseudonyms; some researchers allow research participants to choose their own.

A requirement for research involving human participants; the documentation of informed consent.  In some cases, oral consent or assent may be sufficient, but the default standard is a single-page easy-to-understand form that both the researcher and the participant sign and date.   Under federal guidelines, all researchers "shall seek such consent only under circumstances that provide the prospective subject or the representative sufficient opportunity to consider whether or not to participate and that minimize the possibility of coercion or undue influence. The information that is given to the subject or the representative shall be in language understandable to the subject or the representative.  No informed consent, whether oral or written, may include any exculpatory language through which the subject or the representative is made to waive or appear to waive any of the subject's rights or releases or appears to release the investigator, the sponsor, the institution, or its agents from liability for negligence" (21 CFR 50.20).  Your IRB office will be able to provide a template for use in your study .

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

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

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2 Chapter 2 (Introducing Research)

Joining a Conversation

Typically, when students are taught about citing sources, it is in the context of the need to avoid plagiarism. While that is a valuable and worthwhile goal in its own right, it shifts the focus past one of the original motives for source citation. The goal of referencing sources was originally to situate thoughts in a conversation and to provide support for ideas. If I learned about ethics from Kant, then I cite Kant so that people would know whose understanding shaped my thinking. More than that, if they liked what I had to say, they could read more from Kant to explore those ideas. Of course, if they disliked what I had to say, I could also refer them to Kant’s arguments and use them to back up my own thinking.

For example, you should not take my word for it that oranges contain Vitamin C. I could not cut up an orange and extract the Vitamin C, and I’m only vaguely aware of its chemical formula. However, you don’t have to. The FDA and the CDC both support this idea, and they can provide the documentation. For that matter, I can also find formal articles that provide more information. One of the purposes of a college education is to introduce students to the larger body of knowledge that exists. For example, a student studying marketing is in no small part trying to gain access to the information that others have learned—over time—about what makes for effective marketing techniques. Chemistry students are not required to derive the periodic table on their own once every four years.

In short, college classes (and college essays) are often about joining a broader conversation on a subject. Learning, in general, is about opening one’s mind to the idea that the person doing the learning is not the beginning nor the end of all knowledge.

Remember that most college-level assignments often exist so that a teacher can evaluate a student’s knowledge. This means that displaying more of that knowledge and explaining more of the reasoning that goes into a claim typically does more to fulfill the goals of an assignment. The difference between an essay and a multiple choice test is that an essay typically gives students more room to demonstrate a thought process in action. It is a way of having students “show their work,” and so essays that jump to the end without that work are setting themselves up for failure.

Learning, Not Listing

Aristotle once claimed “It is the mark of an educated mind to be able to entertain a thought without accepting it.” Many students are familiar with the idea of search . The internet makes it tremendously easy to search for information—and misinformation. It takes a few seconds to find millions of results on almost any topic. However, that is not research. Where, after all, is the re in all of that? The Cambridge Dictionary offers the following definition:

Research (verb): to study a subject in detail, especially in order to discover new information or reach a new understanding.

Nothing about that implies a casual effort to type a couple of words into search engine and assuming that a result on the first screen is probably good enough. Nor does that imply that a weighted or biased search question, like “why is animal testing bad” will get worthwhile results.  Instead, research requires that the researcher searches, learns a little, and then searches again . Additionally, the level of detail matters. Research often involves knowing enough to understand the deeper levels of the subject.

For example, if someone is researching the efficacy of animal testing, they might encounter a claim that mice share a certain percentage of their DNA with human beings. Even this is problematic, because measuring DNA by percentage isn’t as simple as it sounds. However, estimates range from 85% to 97.5%, with the latter number being the one that refers to the active or “working” DNA. Unfortunately, the casual reader still knows nothing of value about using mice for human research. Why? Because the casual reader doesn’t know if the testing being done involves the 97.5% or the 2.5%, or even if the test is one where it can be separated.

To put it bluntly, Abraham Lincoln once had a trip to the theater that started 97.5% the same as his other trips to the theater.

In order for casual readers to make sense of this single factoid, they need to know more about DNA and about the nature of the tests being performed on the animals. They probably need to understand biology at least a little. They certainly need to understand math at a high enough level to understand basic statistics. All of this, of course, assumes that the student has also decided that the source itself is worthy of trust. In other words, an activist website found through a search engine that proclaims “mice are almost identical to humans” or “mice lack 300 million base pairs that humans have”. Neither source is lying. Just neither source helps the reader understand what is being talked about (if the sources themselves even understand).

Before a student can write a decent paper, the student needs to have decent information. Finding that information requires research, not search. Often, student writers (and other rhetors) mistakenly begin with a presupposed position that they then try to force into the confines of their rhetoric.  Argumentation requires an investigation into an issue before any claim is proffered for discussion.  The ‘thesis statement’ comes last; in many ways it is the product of extensive investigation and learning. A student should be equally open to and skeptical of all sources.

Skepticism in Research

Skepticism is not doubting everyone who disagrees with you. True skepticism is doubting all claims equally and requiring every claim to be held to the same burden of proof (not just the claims we disagree with). By far, the biggest misconception novice writers struggle with is the idea that it is okay to use a low-quality source (like a blog, or a news article, or an activist organization) because they got “just facts” from that source.

The assumption seems to be that all presentations of fact are equally presented, or that sources don’t lie. However, even leaving aside that many times people do lie in their own interests, which facts are presented and how they are presented changes immensely. There’s no such thing as “just facts.” The presentation of facts matters, as does how they are gathered. Source evaluation is a fundamental aspect of advanced academic writing.

“Lies” of Omission and Inclusion:  One of the simplest ways to misrepresent information is simply to exclude material that could weaken the stance that is favored by the author. This tactic is frequently called stacking the deck , and it is obviously dishonest. However, there is a related problem known as observational bias , wherein the author might not have a single negative intention whatsoever. Instead, xe simply only pays attention to the evidence that supports xir cause, because it’s what’s relevant to xir.

• Arguments in favor of nuclear energy as a “clean” fuel source frequently leave out the problem of what to do with the spent fuel rods (i.e. radioactive waste). Similarly, arguments against nuclear energy frequently count only dramatic failures of older plants and not the safe operation of numerous modern plants; another version is to highlight the health risks of nuclear energy without providing the context of health risks caused by equivalent fuel sources (e.g. coal or natural gas).
• Those who rely on personal observation in support of the idea that Zoomers are lazy might count only the times they see younger people playing games or relaxing, ignoring the number of times they see people that same age working jobs or—more accurately—the times they don’t see people that age because they are too busy helping around the house or doing homework.

A source that simply lists ideas without providing evidence or justifying how the evidence supports its conclusions is likely not a source that meets the rigor needed for an academic argument. While later chapters will go into the subject in greater detail, these guidelines suggest that in general, news media are not ideal sources. Neither are activist webpages, nor are blogs or government outlets. As later chapters will explore, all of these “sources” are not in fact sources of information. Inevitably, these documents to not create information, they simply report it. Instead, finding the original studies (performed by experts, typically controlled for bias, and reviewed by other experts before being published) is a much better alternative.

Examining Sources Using the Toulmin Model

On most issues, contradictory evidence exists and the researcher must review the options in a way that establishes one piece of evidence as more verifiable, or as otherwise preferable, to the other.  In essence, researchers must be able to compare arguments to one another.

Stephen Toulmin introduced a model of analyzing arguments that broke arguments down into three essential components and three additional factors. His model provides a widely-used and accessible means of both studying and drafting arguments.

The Toulmin model can be complicated with three other components, as well: backing, rebuttals, and qualifiers. Backing represents support of the data (e.g. ‘the thermostat has always been reliable in the past’ or ‘these studies have been replicated dozens of times with many different populations’). Rebuttals, on the other hand, admit limits to the argument (e.g. ‘unless the thermostat is broken’ or ‘if you care about your long-term health’). Finally, qualifiers indicate how certain someone is about the argument (e.g. ‘it is definitely too cold in here’ is different than ‘it might be too cold in here’; likewise, ‘you might want to stop smoking’ is a lot less forceful than ‘you absolutely should stop smoking’).

At a minimum, an argument (either one made by the student or by a source being evaluated) should have all three of the primary components, even if they are incorporated together. However, most developed arguments (even short answers on tests or simple blog posts) should have all six elements in place. If they are missing, it is up to the reader to go looking for what is missing and to try to figure out why it might have been left out.

Here is an example of an underdeveloped argument that is simply phrased like an absolute claim of fact. It is a poor argument, in that it offers none of the rationale behind what it says—it just insists that it is correct:

“Other countries hate the United States for a reason.”

What other countries? What reason? Is it just one reason, or is it one reason per country?

By contrast, here is an argument that has at least some minimal development:

“In the eyes of many (Qualifier), the United States has earned the hatred of other countries (Claim). The U.S. involvement in Iranian politics alone has earned the country criticism (Data). By helping to overthrow a democratically elected leader in favor of a monarch in 1953, the U.S. acted in a manner that seemed hypocritical and self-interested (Backing). While many countries do act in favor of their own interests (Rebuttal), the U.S. publicly championing democracy while covertly acting against it serves to justify criticism of the country (Warrant).”

Is there room to disagree with this argument? Yes. However, this argument provides its rationale, it offers at least some sort of evidence for its claims, and it provides a place to begin engagement. A researcher who wishes to know more about this argument can go looking into the history of U.S.-Iran relations, for example.

When reviewing a source, or making their own arguments, researchers should consider the following questions. Is there evidence that can be verified and examined by others (in the same spirit as the scientific method)? More specifically:

• What is the claim?
• What data backs up this claim?
• What assumptions do I have to make to consider this evidence to be adequate support?

The various pieces of data which support claims in the Toulmin model are often called into question.  Studies are refuted, statistics countered with rival numbers, and their applicability to the claim in question is often murky.  Evidence—whether offered as matters of fact or as subjective considerations—does not exist in a vacuum.  Data are themselves claims.  If the supporting data are accepted as true, the argument has a generally accepted conclusion.  Such pieces of ‘evidence’ are contentions .

Although Toulmin distinguishes between qualifiers and rebuttal conditions, such a distinction is difficult to maintain in practice.  The important consideration—the one acknowledged by both terms—is that unconditional or absolute claims are difficult to support.  Specific fields have their own ways of hedging their bets.  Science has its error bar (Sagan) and the terminology of probability.  Statistics and polling have a margin of error.  Ethnography has its confrontation of personal bias.  When a rhetor expresses the limitations of a given claim, when the unconditional becomes conditional, claims become more than categorical propositions or thesis statements.  They become arguments.

Example 1:  Here is a minimalistic overview of one claim on the topic of traffic cameras.

• Claim = Traffic cameras increase minor accidents
• Evidence = David Kidwell and Alex Richards of The Chicago Tribune performed a study that was later cited by ABC News.
• Assumptions = This study was conducted honestly and reasonably represents the reality of accidents around these cameras (i.e. I can trust the agenda and the methods of the Chicago Tribune staff).

Example 2 : And here is a second claim on the same subject.

• Claim = The types of accidents by traffic cameras tend to be less severe
• Evidence = The Insurance Institute for Highway Safety examined national trends and compared medical reports, police reports, and various bills, posting the results on their website.
• Assumptions = If the IIHS has a bias, it would be toward fewer accidents, or at least less severe accidents (because this means they have to pay less money out).

As an Essay Fragment : According to some, traffic cameras actually increase accidents. A study conducted by the Chicago Tribune found that rear-end collisions increased when traffic cameras were installed, meaning that they make things worse, not better (Kidwell and Richards). However, the Insurance Institute for Highway Safety points out that while there are sometimes increases in minor collisions, the number of crashes resulting in injuries actually decreases.

• “According to…not better (Kidwell and Richards).” This uses a parenthetical source citation to provide a “link” to the evidence and to invite readers to examine both the data and the warrants.
• “However, the…decreases.” This uses a signal statement to introduce the source of the evidence first, often because the source has so much credibility the author is hoping to impress the reader.

Note that this is not a particularly powerful fragment–it is simply the  minimum level of rigor that a student should offer (or look for) in an academic essay or in an academic source.

Academic arguments typically make concessions.  These concessions help define the scope of the argument and the range of the inquiry.  In Section 1, I mentioned a relatively straightforward value claim: “Plan X is bad.”  Argumentation engages such value claims and defines their scope and limits.  Who is plan X bad for?  By what standards?  Why then is anyone in favor of plan X?  A more practical approach could be “If you favor Y, then Plan X is bad.”  This is a concession, of sorts—Plan X is only bad if you favor Y.  The argument admits that if you do not, then Plan X might not be all that bad, after all.

Such a concession, worded in such a way, has added merit.  It functions as what Aristotle would have called an artistic proof, although maybe not an enthymeme.  It establishes a bond between the rhetor and the audience through the shared favoring of Y; it nurtures consubtantiality—the basis of what Burke calls identification.  Clearly, concessions can be made in a way that both prevents some counterarguments from applying and still furthers a rhetorical point.

Such phrasing is practical, and only truly cynical interrogators would consider it sinister.  An inversion of this approach is possible.  “Unless you favor Y, Plan X is bad.”  So long as Y is sufficiently negative in the minds of the audience, the rhetor loses no actual impact here.  Here, connecting Y to X might require substantiation on the part of the rhetor, because the concession has become, itself, a justification of why X is bad (it is related to or involves Y).  The additional rhetorical power—gained through positive and negative associations—often compensates for such additional effort.

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Chapter 2: Research Methods in Psychology

Chapter 2 learning objectives:.

• Explain the steps of the scientific method
• Differentiate between theories and hypotheses
• Differentiate between descriptive, experimental, and correlational research
• Explain the strengths and weaknesses of case studies, naturalistic observation, and surveys
• Explain what a correlation coefficient tells us about the relationship between variables
• Describe why correlation does not mean causation
• Describe the experimental process, including ways to control for bias
• Identify and differentiate between independent and dependent variables
• Differentiate between random sampling and random assignment

Chapter 2 Sections:

The Scientific Process

Introduction to Research Methods

Descriptive Research

Correlational Research

Experiments

Putting it All Together: Psychological Research

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What D oes Synthesis and Analysis Mean?

Synthesis: the combination of ideas to

• show commonalities or patterns

Analysis: a detailed examination

• of elements, ideas, or the structure of something
• can be a basis for discussion or interpretation

Synthesis and Analysis: combine and examine ideas to

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• form a unified point for a theory, discussion, or interpretation
• develop an informed evaluation of the idea by presenting several different viewpoints and/or ideas
• Article Spreadsheet Example (Article Organization Matrix) Use this spreadsheet to help you organize your articles as you research your topic.

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CHAPTER 2 REVIEW OF RELATED LITERATURE AND STUDIES

Related Papers

Ana Liza Sigue

Motoky Hayakawa

Rene E Ofreneo

... Rene E. Ofreneo University of the Philippines School of Labor and Industrial Relations ... Erickson, Christopher L.; Kuruvilla, Sarosh ; Ofreneo, Rene E.; and Ortiz, Maria Asuncion , "Recent Developments in Employment Relations in the Philippines" (2001). ...

Lucita Lazo

This book begins by looking at the status of women in Filipino society and their place in the general socio-economic situation. It continues with sections on education and training in the Philippines and work and training. The next section reviews the constraints to women’s participation in training. In the summary the author gives a general overview of the situation of women and opportunities for work and training in the Philippines and offers some practical suggestions for the enhancement of women’s training and development.

EducationInvestor Global

Tony Mitchener

Rosalyn Eder

In this article, I examine the role of CHED and the Technical Panels (TPs) in the “production” of the globally competitive Filipina/o worker. For this paper, I draw on relevant literature on the topic and take nurse education, which is rooted in the colonial system established during the US-American occupation, as an example of how CHED and the TPs could be more linked to labor migration. I use the colonial difference - a space that offers critical insights and interpretation - to illustrate how coloniality remains hidden under the cloak of modernity. Link to the article: http://dx.doi.org/10.1080/00131946.2016.1214913

Asia Pacific Journal of Management and Sustainable Development ISSN 2782-8557(Print)

Ryan O Tayco , Pio Supat

This study aims to determine the employability of the Negros Oriental State University graduates from 2016 to 2020. Employability is measured using different dimensions-from the graduates' side including the perspectives of the employers. A total of 1, 056 NORSU graduates and 68 employers locally and abroad answered the questionnaire through online and offline survey methods. Basic statistics were used and simple linear regression was also used to estimate the relationship between manifestations of respondents in NORSU VMGOs and the job performance as perceived by the employers. Most of the respondents in the study are presently employed and work locally. Many of them stay and accept the job because of the salaries and benefits they received, a career challenge, and related to the course they have taken in college. The study shows that the curriculum used and competencies learned by the NORSU graduates are relevant to their job. Competencies such as communication skills, human relations skills, critical thinking skills, and problem-solving skills are found to be useful by the respondents. It is found that the manifestation of the respondents is very high and homogenous. The same can be said with job performance as perceived by employers in terms of attitudes and values, skills and competencies, and knowledge. Furthermore, job performance and the manifestation of NORSU VMGOs have a significant relationship. That is, those respondents who have higher job performance in terms of attitude and values, skills and competencies, and knowledge have higher manifestations of NORSU VMGOs.

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Economics 145                                                                                                                 Prof. Yang

In Chapter 1, we covered the basic concepts of research in economics first by reviewing key terms in research and the roles of theory and data in the study of economics. We noted that the study of economics proceeds within the framework of scientific methods and we engaged in a general discussion of scientific method before moving on to a discussion of various terms and concepts within the scientific method. Clearly, learning about the scientific method and the basic concepts of the scientific method is essential to carry out research in economics. However, our discussion was general in nature and, basically, conceptual. While interesting, this kind of learning about the scientific method, and its basic concepts of research in general terms, offers little help in actually starting and successfully completing an economic research project. Thus, given the understanding of basic concepts of research, what we need to learn now are the specifics of to start our research, and to do it.

When students take a research methods course, they usually learn about research procedures in general terms. When they attempt to apply what they have learned in the research methods course to a real research project, they arguably find that they are not adequately prepared to start and complete a meaningful project.

This outcome is at least in part due to our way of teaching students mainly by feeding information without requiring a deeper understanding the subject. This is also partly due to the fact that undergraduate economic education is organized largely by subject-matter packages. Economics undergraduate students typically take intermediate level micro and macro economic theories, several upper division field-specific courses, depending on their interests, as well as one or two quantitative economics courses. More often than not, economics students do not have an opportunity to take a research methods course. Students in upper division field-specific economics courses seldom have the opportunity to conduct any serious and meaningful research, except for the rare occasions to do an honor’s thesis with individualized assistance from faculty members. Consequently, with or without a research methods course, undergraduate students typically do not learn the subject well enough to apply their conceptual knowledge to finding answers in the context of applied and quantitative research. There is a crying need for a practical guide to conducting applied quantitative economic research. Meeting this need is the main motivation to write this book.

The procedures and steps to follow in research are well-known, and I present below a set of standard procedures for conducting applied quantitative economic research. At each step, I will explain you do, you do it, and finally you do it. But merely listing and describing each step at a time is not enough. What I am striving to accomplish is to integrate research problems, theory, and the analysis of data, and to show how and why decisions are being made throughout the research process. To assure comprehension, I will present discussions on research procedures by working with specific examples.

Research is an orderly and systematic procedure, and this procedure may be presented sequentially from the first step of problem definition through the final step of the writing-up of the final report. However, it is also essential to understand that the research process is essentially in the sense that each preceding and succeeding step feeds on each other.

The five major steps in any typical applied and quantitative economic research process are as follows:

1. Statement of Research Problem
2. Survey of Related Literature
3. Theoretical Model: Formulation of Hypothesis
4. Analysis of Data: Testing of Hypothesis
5. Write-up of Research Report

Research Problem

John Dewey

In starting research one obviously must first decide what problem to investigate. Clearly, therefore, a clear definition and statement of the research problem is the most important part of any research activity. When a research topic is given by your professor or supervisor there is no problem to choosing it. But the responsibility to choose research problem is yours, it becomes more daunting and difficult task. In this case, it will be first something your are interested. It is appropriate to choose a topic within a field which the student is familiar. But even if the student identifies a potential topic he or she is interested in and reasonably familiar with, it is still a difficult task to define and state the problem clearly and adequately. It takes a fair amount of mental struggle to understand the research issue thoroughly; and it takes at least an equal amount of effort to be able to write a succinct problem statement. The importance of a succinct problem statement cannot be too emphasized. Inadequate and incomplete delineation of the research problem results in wasting precious time in gathering materials, and may also result in activities not directly related to the research problem.

A research problem may be disciplinary, subject-matter, or problem-solving oriented and, indeed, combination of the three.

Finally, the requirements of a good research problem include , , and .

B. The research problem has to be specific so that it can be addressed given the constraints of time and budget. Broad and general research problems are neither meaningful nor manageable. If one wishes to study the Pacific Ocean, it is a too broad and wide topic. Research has to focus on a specific aspect of the Pacific Ocean.

C. Finally, the research problem has be "manageable" because it has to be finished within the assigned time and budget constraint.

To define the research problem adequately, however, requires substantial knowledge of the problem itself. One way of obtaining this knowledge is to read background materials. Text-books or, better, a recent review article on the topic are often useful as starting points, since they give a balanced summary of present knowledge, and also provide useful references. But as you study these books and articles by other investigators, you need to evaluate these previous works in light of your own research problem. As you read, you must always ask yourself what you are trying to find out. If you cannot state clearly what it is you want to find out, it is obvious that you are going to waste a lot of time before you settle on the specific research problem.

The problem or problem area to research depends on your interest, experience, and career goals. But once you have a research problem or problem area, a decision must be made to focus on one or two specific aspects of the problem. To accomplish this, one has to be familiar with the area; to actually know quite bit about it, fact. How does one gain enough knowledge to embark on serious research? If you are familiar with the subject matter, it is largely a matter of intuition and insight for you to come up with the specific problem. If not, you have to read background materials to gain this knowledge. Suppose, for instance, that you are interested in studying the reasons for the continual increase over time in health care expenditure in the U.S. Searching through the literature, you will find that Chapter 4, "The Economics of Health Care" in the and two symposia articles on health economics and health care reform in (Summer 1992 and Summer 1994) provide adequate background.

As you gain knowledge on the chosen topic, it is also helpful to decide what specific research problems and issues you are interested in. Specifically, are you interested in establishing a comparison? To find a cause or an effect? With the cause-effect relationship in the health care expenditure in mind, one can choose to study the roles of third-party payment mechanism through insurance, of technology, or of government. How about measuring the magnitude of some interesting and important issue, such as measuring the welfare cost of national health care insurance? There are many more interesting questions and issues to be investigated within the general rubric of health care expenditure in the U.S.

The formulation of the statement of the problem usually requires the following two steps.

1. Overview of the problem
2. Narrowing down to specific aspect(s) of the problem

One good way to start the problem statement is to present the problem in an overview. The reason why researchers usually start with presenting the problem in the context of an overview is to present the problem in perspective. This way, the reader is introduced to terminology, definitions, and the relationship under consideration, as well as the relationship of the topic to related questions and fields.

An example of good overview is quoted below. [See Craig S. Hakkio’s article entitled "Is Purchasing Power Parity a Useful Guide to the Dollar?" in pp. 37-51]

(PPP) is a measure of the dollar’s equilibrium value - the exchange rate toward which the dollar moves over time. Because the value of the dollar is currently below its PPP value, academic and business economists

use the concept of purchasing power parity to advocates argue that the dollar is undervalued and therefore likely to rise.

Other economists acknowledge that PPP may help forecast the value of the dollar over the long run but doubt its usefulness as a short-term guide. They often cite the 1970s, when the dollar frequently strayed from its PPP value and sometimes took years to return. They also note that economic and political forces regularly buffet the dollar, keeping its value away from equilibrium. Thus, even though the dollar is currently below its PPP value, these economists maintain there is no guarantee it will rise in value in the near term.

The research problem in Hakkio’s paper is to evaluate the purchasing power parity as a guide to future direction of the US dollar. In his overview of the problem, Hakkio first defines the term "purchasing power parity" and presents two alternative views to the use of PPP as a guide to the future direction of the US dollar. According to one view, namely the purchasing power parity view, the dollar is likely to rise because current value of the dollar is below its PPP value. According to other view, however, there is no guarantee that the dollar value will rise soon, because the PPP view is known to hold only in the long run. What he skillfully accomplished in the two short paragraphs are: 1) to clearly define the problem, 2) to define the key term, and 3) to present two alternative views on the future direction of the dollar.

After having presented an overview of the problem, the researcher usually focuses in one or two specific issues or aspects of the problem. In the case of Hakkio’s paper, however, he moves directly on to the objective statement because there is no further need to narrow it down. His objective statement and a general outline of his paper is presented in the third paragraph of his paper and is quoted below:

"This article argues that PPP is a useful guide to the dollar in the long run

and - to a lesser extent - in the short run. The first section of the article defines

the concept and discusses why most economists believe it is a useful long-run guide. The second section shows the dollar generally moves toward its PPP

the measure says little about whether the dollar will rise in the near term."

Suppose a student proposes to write a research paper with the title "Trade Deficit", "Budget Deficit", "Exchange Rate", or "U.S. Banking". One can tell immediately see that each of these subjects is too broad and general to be a meaningful research topic. How does one go about narrowing down these broad and general topics to a manageable research problem? To learn how to do that, we need to learn to reduce the topic to manageable size by limiting it by time, space, or geographically a certain aspect of the problem.

With the trade deficit as an example, one may limit it to "U.S. Trade Deficit" or, more specifically, to "U.S.-Japan Trade deficit". Similarly, it may limited to a specific time period as "Persistent U.S. Trade Deficit During 1980s". Indeed, it might be a combination of two aspects, like "U.S.-Japan Trade Deficit during the 1980s". Or one might decide to focus on one particular aspect, such as the major determinants of the U.S. trade deficit or the effect of U.S. trade deficits on the exchange value of the U.S. dollar..

With the budget deficit in mind, one might similarly limit it to "U.S. budget Deficits" or to the well known issue of the twin deficits between the "U.S. Budget Deficits and Trade Deficits". Or perhaps one might decide to limit the topic to the impact of a reduction in U.S. budget deficit on the value of the U.S. dollar..

With the U.S. banking in mind, one may ask whether or not U.S. Banking is declining". If the answer is positive, one can further examine why U.S. banking is not declining

To illustrate further, consider health care expenditure in the United States over the past several decades. We see from the data that U.S. health case expenditure has steadily increased and that it has increased faster than other categories of expenditure. One can raise a number of important and meaningful questions with respect to heath care spending vis a vis other categories of expenditures. One can ask: Why are health care expenditures in the U.S. increasing over time? Or why has health care expenditure in the U.S. increased substantially faster than other expenditure categories? With this general question in mind, one may pose a more specific question like: Why has the share of health care expenditure of total U.S. consumer expenditure increased during the 1960-95 period? To answer this question adequately, one has to examine the major determinants of health care expenditure in the U.S. Relating to this question, one might pursue the financing side of health care expenditure. To restrain this rapid growth, many health care reform proposals deal with the question of how to finance health care expenditure.

For the last illustration of narrowing down to specific aspect of the research problem, let us take up the recent surge in gasoline prices in California. One can raise a number of important and useful questions about this topic. First, why did gasoline price increase so dramatically in the first part of 1996 compared with those in the previous five years? Is it due to higher gasoline taxes or is it due to the "rigging" of gasoline price by big oil companies? Would the proposed sale of the navy petroleum reserve announced by President Clinton help lower gasoline prices or is it merely a political ploy? A second question might be: Why, in recent years, are gasoline prices in California substantially higher than in the rest of U.S.? What, if any, is the role of environmental costs in California’s recent gasoline price hike?

When you have finally defined the research problem adequately, the next task is to state the problem clearly. We often say that it is necessary to state the research problem Success depends largely on one’s ability in organization and in technical writing. Since the writing aspect of research activity is not the primary focus of this chapter, one may refer to publications devoted to this aspect. Two good resources which many students find useful are: by John S. Harris and Reed H. Blake (Nelson-Hall) and by William Strunk Jr. and E.B. White. (Macmillan)

 

Review of Related Literature

Almost all research topics have been studied by other researchers. Nothing under the sun is new, as one verse in the Old Testament says. As you consider some problem or research issue, you can be almost assured that somebody else has studied the problem previously. Therefore, the obvious fact is: The more one knows about what was studied earlier, the better the researcher can approach and solve the problem. What then is the purpose of this review? Obviously, it is to assist you in attacking the problem you choose to study. As you review previous research done in related areas, directly and indirectly, you will be better prepared to handle the problem.

The benefits of a review of related literature are many and a few of them are listed here:

How should one go about preparing "Review of Related Literature". While there is no one way of doing this, following the several steps listed below will be helpful.

Before you begin a review of related literature, you first need to find out what has been done on the topic you are interested in. How does one find out what has been done on a particular topic? There are several ways to do this. An increasingly popular method to do a literature search is to tap into two popular electronic data bases. The first one is the compact disc search This handy and economical search software consists of one compact disc and user manual. It has a complete list of all the articles and working papers listed in the , an official publication of the American Economic Association. To use it, however, requires access to an EconLit compact disc and a personal computer with a compact disc drive. The second electronic source is one of several search procedures available on Internet.

When using electronic search procedures, it is important to type in two or three key words to facilitate your search. If the word chosen for your search is broad and general, these search procedures will give you literately few hundreds citations and sorting through so many is not efficient. Thus, when you search previous studies directly or indirectly related to your chosen topic, type only in two or three few key words directly related to your topic.

After your electronic search procedure has produced the necessary citations, you often need to select only those citations which have a direct bearing on your topic. It is a survey of literature, and only the researcher can make the determination of the degree of relatedness.

If you do not have access to an electronic search, you have to rely on manual search procedures through the library. You can go to library and find current and old issues of the This publication lists articles published by journal and by field. It would be advisable to start from a current issue and see if one can find articles and other publications on the topic. Then go to older issues and do the same by writing down citations of all related works.

Having identified all important previous studies which have a direct or indirect bearing on your topic, the next step of writing the review of related literature is to make a plan of how you want to organize your literature review. Without a plan, the literature survey easily becomes "Smith did this; Jones did that" by merely listing what they have done. In making a literature review plan, good advice is always to be mindful of the research problem itself. Without a clear understanding of the research issue and problem, one cannot make a plan for a good literature survey. Any serious attempt to understand the different aspects of each previous work requires substantial effort before one can see clearly how seemingly unrelated work fit together. Only then one can develop a good plan. In organizing your related literature, it is useful first to identify one or two major, or classic, studies. Then you can see the contributions of other works in relation to what was already done or not done in the major works. There may be situations where, in some cases, it is difficult to classify previous works by "major or minor" categories, because the contributions of each work are similar. In this case, it would be reasonable to review previous works by commenting only on the different aspects or focus of these works. One way or another, understanding the main research problem and the contributions of previous works is essential before one can make a plan for literature survey. Finally, it is always a good idea to see how each prior study is related to the problem you are focusing on. The importance of the literature cannot be emphasized too much.

Remember what you are doing is a review of literature. This means that you are presenting your own discussion of existing literature. Because of this, it is to avoid direct quotation. Paraphrasing or restating in your own words is the way to do it. What you are doing is evaluating prior work to shed light on your study.

 

"Science is built with facts as a house is built with stones, but a collection of facts is no more science than a heap of stones is a house." -Jules Henri Poincare

"A person "can stare stupidly at phenomena; but in the absence of imagination they will not connect themselves together in any rational way". -C.S. Peirce

 

After the researcher has chosen a problem and has ascertained what investigations have already been done on it, the next step is to conceptualize the problem.

1. is Conceptual Framework and do we need one?

The conceptual or theoretical framework is the process of conceptualizing the problem by reasoning, recognizing, and synthesizing the problem. It is an abstract process in which the researcher identifies the central versus the peripheral, or the primary versus the secondary components of the problem, and understands how these components fit together.

The economic world is incredibly complex. The economist’s task of explaining the behavior of people, institutions and their interactions is, therefore, a very difficult task. To understand why and how it works, we need, as in all other fields of science, to abstract from reality. Abstraction requires ignoring many details in order to focus on the most important elements in order to understand the functioning of a complex phenomenon. Theorizing is a combined effort of abstracting (from details) and connecting (the essential components), and . As Pierce said, one can stupidly stare at the facts and data. Only with theory, one can begin to attempt to understand it. The process of arriving at a logical structure for organizing and analyzing the problem is, in fact, a deliberate simplification (abstraction) of the factual relationship to explain how those relationships work. So the theory is an of the mechanism behind observed phenomena.

A couple of examples: 1) road map; 2) ocean waves on the surface as facts. Undercurrent and forces below. Focusing on waves make you dizzy with no understanding of why and how’s of pattern of ocean waves. 3) gasoline price and shift in the demand and supply.

Therefore, the first role of conceptualization is to provide a logical structure for organizing and analyzing the problem. The second role of conceptualization is to lead to a hypothesis, which in turn leads to the testing of the hypothesis. Hypotheses are the results of the conceptualization of the problem. One definition: An hypothesis is a tentative assertion that is subject to testing. "As a tentative assertion, it can take the form of a simple proposition of an expected outcome or an assertion of a relationship, or relationships, between or among forces, variables, or events". [Eldridge, p. 136]

:

2) to Star and Develop the Conceptual Framework

How does one get started on the conceptual framework? Source materials for developing the conceptual framework for your research come from existing theories. You will recall that the research process is in the sense that the knowledge obtained in each stage feed on each other from the problem statement, the survey of related literature, and the conceptual framework.

From the review of related literature, one must first existing theory or theories on the problem. Second, when there are competing theories, one has to a particular theory suitable to the problem. Third, and finally, one has to the chosen theory to solve the problem.

To illustrate how to start and develop a conceptual framework, it is best to work with a specific topic. Suppose we are interested in the relationship between transit fares in Sacramento, California and the revenue that the transit system takes in. Specifically, let our question be whether or not a hike in fares, say from a current $1.25 to $1.50, would increase revenue.

In organizing and analyzing our problem to answer that question, we will develop a conceptual framework or, as the economist calls it, build a model. From our knowledge from the micro-economics principles course, we learned that total fare collection (total revenue) is equal to the average fare times the number of rides. In an equational form, this relationship can be stated as:

Equation (1) helps us organize our thinking about the two key variables, namely the fare and number of rides, in the determination of the total revenue. The fare is under the control of and is set by the Sacramento Regional Transit Authority. However, the number rides depends on the fare. The problem is to know how the number of rides will be affected by proposed fare hike by the Transit Authority. Or, more broadly, the question is what determines the number of rides. The economist’s way of answering this question is to view the number of rides as depending on the consumer’s decision to choose between taking transit and alternative transportation modes. The choice of transportation mode is basically an economic decision based on the relative cost and convenience of alternative means of transportation. Once viewed this way, one can see that this is the demand for regional transit.

From the theory of demand, we know that the number of rides, or using the economist’s term, the quantity of transit rides demanded, depends first on fare and the cost of alternative mode of transportation, as well as consumer income. Formally, we can write:

The next step is then to combine the equations (1) and (2) to have the model of total revenue from fare collection. Combining equations (1) and (2) yields:

Total Subway Revenue = fare x quantity of transit ride demanded

We now have a complete theoretical model of transit revenue with the key determining factors. However, one may note that the model specified above is a simplified description of the process involved when compared with real world complexities. It is obvious that important explanatory variables such as parking in downtown, the frequency and quality of service of regional transit and so forth, have been omitted. So the natural question is what is the "right" degree of abstraction. But there is no such thing as one right level of abstraction for all analytical purposes. The proper degree of abstraction obviously depends on the objective of the analysis at hand.

Once the theoretical model is specified, we need to evaluate the model qualitatively. An increase in the fare is expected to do two things. First, an increase in fare, holding constant all factors other than fare, tends to increase revenue. But second, as the theory of demand tells us, an increase in transit fare is expected to reduce the number of transit rides demanded, holding constant other factors, namely taxi cab fare, cost of owning automobile driving, and consumer income. The prediction of a negative relationship between the subway ride demanded and subway fare would make sense intuitively. But to really understand and an increase in the transit fare usually leads to a reduction in the transit rides demanded, one has to go beyond principles of economics and dig into microeconomics at intermediate level. There we will learn that there are income and substitution effects associated with an increase in subway fare, and that the combined income and substitution effects cause transit rides demanded to fall as a result of the increase in its fare. [See for instance, Nicholson’s Chapter 4, 1994]. Since these two effects work in opposite directions, it is not a priori clear whether the increase in fare will lead to an increase in total revenue or not. There are three possibilities: Total revenue may increase, remain the same, or decrease, all depending on the price elasticity of demand of ridership.

What does the theory of demand tells us about expected impact of an increase in cost of two alternative means of transportation? Theory tells us that an increase in taxi fare and cost of automobile driving, given the transit fare, will raise transit rides demanded because transit ride will become relatively cheaper (through the substitution effect). But how about the effect of an increase in consumer income on transit rides demanded? The theory of demand tells us that whether or not an increase in consumer income will raise or reduce transit rides demanded depends on whether consumers perceive transit rides as an inferior good or as a luxury good.

Now we realize that the theory of demand will provide answers only . That is, the number of transit rides demanded will rise or fall, if such and such conditions are satisfied. But theory of demand will not and cannot provide answers, which is necessary to answer our initial question of whether or not a hike in transit fare would increase transit revenue. What the theory does is to conceptualize the problem to provide a logical structure for organizing and analyzing the problem, and it can predict the direction of change of a change in determining factors only . What we need is a quantitative and empirical answer. The next section is devoted to the discussion of the formulation of an empirical model and its estimation with real-world data, as well as testing of hypotheses.

Empirical analysis covers a wide range of activity of measurement, estimation, and verification of phenomena under consideration. Since it covers a broad range of activity, it is difficult to present discussion of general rules to follow in conducting empirical analysis. But it seems reasonable to classify various empirical analysis into two types of empirical analysis: descriptive empirical analysis and cause-effect analysis which involves estimation and the testing of hypothesis. First, we will present discussions of how to conduct a descriptive empirical analysis with an example.

A descriptive empirical analysis is based on data analysis usually consisting of descriptive statistics and other quantitative measures in analyzing a particular issue(s) or question(s). It does not involve the statistical estimation of relationship and the testing of the hypothesis, as is done in the case of analysis of an assumed cause-effect relationship.

A descriptive empirical analysis may also involve and of the extent and degree of a certain phenomenon

To illustrate how to conduct a descriptive empirical analysis, consider a well-known macroeconomic issue of the trade-off between inflation and unemployment. Some background on this issue may be useful. During the 1950s and 1960s, many empirical studies examined inflation and unemployment data for numerous countries and time periods; and in many cases finding a negative relationship between unemployment and inflation. This negative empirical relationship between unemployment and inflation is known as the In the following decades, however, this relationship between unemployment and inflation failed to hold. In the latter part of the 1960s and early 1970s some economists, notably Milton Friedman and Edmund Phelps, question the logic of the Phillips curve. They argued on theoretical ground that we should not expect a stable relationship between inflation and unemployment. Rather, a stable negative relationship should exist between inflation and the unemployment rate.

Incorporating the negative relationship between unanticipated inflation and cyclical unemployment, we may write

- = )

where h refers to a positive number that measures the strength of the relationship between unanticipated inflation and cyclical unemployment. The latter is defined as the difference between the actual unemployment rate (u) and the natural rate of unemployment (u ). The above equation states that given the expected inflation rate, unanticipated inflation will be positive when the cyclical unemployment rate is negative, negative when cyclical unemployment is positive, and zero when cyclical unemployment is zero.

With the concept of a trade-off between the unemployment rate and the inflation rate, policy makers try to gauge the amount of slack in the economy in formulating monetary policy. When the economy’s resources are not pushed beyond capacity levels, inflation tends to remain under control. But when the economy’s resources are pushed to or beyond the capacity level, then inflation is expected to surge. In assessing the capacity in the labor markets, the natural rate of unemployment (NRU) is a key concept. The natural rate of unemployment is defined as that rate of unemployment at which there is no tendency for inflation to change.

With the above background in mind, let us now consider how Stuart Weiner at the Federal Reserve Bank of Kansas examined the relationship between unemployment and inflation in recent papers. First, he defined the concept of the natural rate of unemployment and provided general background information about the relationship between inflation and unemployment, as expected. He then presented two line graphs with data on the U.S. actual unemployment rate and natural unemployment rate for the 1959-1994 period. Since both unemployment rates are measured in percentages on the vertical axis, the vertical difference between them may be considered as the cyclical unemployment rate. In the second graph, Weiner first identified the four episodes of sustained increases in inflation during the period by shaded areas, and then superimposed a line graph of the cyclical unemployment rate.

Using the second graph, he then analyzed whether or not the increases in inflation were accompanied by the actual unemployment rate going below the natural unemployment rate. Examining the graph, he found that "at no times has the actual unemployment rate gone below the natural rate without the economy ultimately experiencing a rise in inflation".

In the discussion of policy implications of his findings, he made several observations. First, he noted that the lead time between a move below the natural rate and the eventual increase in inflation varies. Second, evaluating changes in the demographics and labor market conditions, he made several comments about why he believes that the natural unemployment rate would not be declining from the then currently estimated rate of 6.25%.

 

Regression analysis of Sacramento Regional transit demand

"Even the best scientific research is useless unless it is communicated to others" Ghebremdhin and Tweeten, 1988, p. 44

1. Introduction
2. Review of Literature
3. Theoretical Model
4. Empirical Analysis
5. Summary and Conclusions
6. Footnotes
7. Tables
8. Appendix
9. References