Using Figure 1.2 in Ch. 1 of Exploring Research, create a flowchart using Microsoft® Word or a similar program that helps you identify what research design to use for your research question.
Ch. 1 of Exploring Research The Role and Importance of Research
What you’ll Learn about in this Chapter:
· Who does research and why
· How research is defined and what some of its purposes are
· What a model of scientific inquiry is and how it guides research activities
· Some of the things that research is and some of the things that it isn’t
· What researchers do and how they do it
· The characteristics of good research
· How a method of scientific inquiry guides research activity
· The different types of research methods and examples of each
Say Hello to Research!
Walk down the hall in any building on your campus where social and behavioral science professors have their offices in such departments as psychology, education, nursing, sociology, and human development. Do you see any bearded, disheveled, white-coated men wearing rumpled pants and smoking pipes, hunched over their computers and mumbling to themselves? How about disheveled, white-coated women wearing rumpled skirts, smoking pipes, hunched over their computers, and mumbling to themselves?
Researchers hard at work? No. Stereotypes of what scientists look like and do? Yes. What you are more likely to see in the halls of your classroom building or in your adviser’s office are men and women of all ages who are hard at work. They are committed to finding the answer to just another piece of the great puzzle that helps us understand human behavior a little better than the previous generation of scientists.
Like everyone else, these people go to work in the morning, but unlike many others, these researchers have a passion for understanding what they study and for coming as close as possible to finding the “truth.” Although these truths can be elusive and sometimes even unobtainable, researchers work toward discovering them for the satisfaction of answering important questions and then using this new information to help others. Early intervention programs, treatments of psychopathology, new curricula, conflict resolution techniques, effective drug treatment programs, and even changes in policy and law have resulted from evidence collected by researchers. Although not always perfect, each little bit of evidence gained from a new study or a new idea for a study contributes to a vast legacy of knowledge for the next generation of researchers such as yourself.
You may already know and appreciate something about the world of research. The purpose of this book is to provide you with the tools you need to do even more, such as
Today, more than ever, decisions are evidence based, and what these researchers do is collect evidence that serves as a basis for informed decisions.
· develop an understanding of the research process.
· prepare yourself to conduct research of your own.
· learn how to judge the quality of research.
· learn how to read, search through, and summarize other research.
· learn the value of research activities conducted online.
· reveal the mysteries of basic statistics and show you how easily they can be used.
· measure the behaviors, traits, or attributes that interest you.
· collect the type of data that relate to your area of interest.
· use a leading statistical package (SPSS) to analyze data.
· design research studies that answer the question that you want answered.
· write the type of research proposal (and a research report) that puts you in control— one that shows you have command of the content of the research as well as the way in which the research should be done.
Sound ambitious? A bit terrifying? Exciting? Maybe those and more, but boring is one thing this research endeavor is not. This statement is especially true when you consider that the work you might be doing in this class, as well as the research proposal that you might write, could hold the key to expanding our knowledge and understanding of human behavior and, indirectly, eventually helping others.
So here you are, beginning what is probably your first course in the area of research methods and wondering about everything from what researchers do to what your topic will be for your thesis. Relax. Thousands of students have been here before you and almost all of them have left with a working knowledge of what research is, how it is done, and what distinguishes a good research project from one that is doomed. Hold on and let’s go. This trip will be exciting.
What Research Is and What It Isn’t
Perhaps it is best to begin by looking at what researchers really do. To do so, why not look at some of the best? Here are some researchers, the awards they have won, and the focus of their work. All of these people started out in a class just like the one you are in, reading a book similar to the one you are reading. Their interest in research and a particular issue continued to grow until it became their life’s work.
Research is, among other things, an intensive activity that is based on the work of others and generates new ideas to pursue and questions to answer.
The following awards were given in 2009 by the American Psychological Association in recognition of outstanding work.
Susan E. Carey from the psychology department at Harvard University was honored for her contributions to the field of cognitive development and developmental psychology. The work that she did early in her career focused on understanding how children learn language, and she coined the term “fast mapping” for how children can learn the meaning of a new word with very little experience with that word.
Nancy E. Adler from the University of California won the Distinguished Scientific Award for the Applications of Psychology for her work in health. Her early research focused on the health behaviors in adolescence, and she explained the incredibly interesting question of why individuals engage in health-damaging behaviors and how their understanding of risk affects their choices.
Finally, one of several Distinguished Scientific Awards for Early Career Contributions to Psychology went to Jennifer A. Richeson from Northwestern University for her work on stereotyping, prejudice, discrimination, and inter-group conflict. This focus examined the experiences and behaviors both of members of devalued groups and of members of dominant groups.
The American Educational Research Association (AERA) also gives out awards that recognize important contributions.
The 2009 E. F. Lindquist award was given to Wim J. van der Linden for his contributions to the field of testing and measurement, including optimal test design and adaptive testing. The award is named after E. F. Lindquist, who was a founder of The American College Testing Program, and is given for outstanding applied or theoretical research in the field of testing and measurement.
AERA has an extensive award program including the Distinguished Contributions to Gender Equity in Education Research Award, given to Sandra Harding from the University of California–Los Angeles in recognition of her research that helps to advance public understanding of gender and/or sexuality in the education community.
And, as with many other organizations, AERA also offers awards for researchers still early in their careers, such as the Early Career Award won by Michele Moses from the University of Colorado–Boulder and Nell Duke from Michigan State University.
What all these people have in common is that at one time or another during their professional careers, they were active participants in the process of doing research. Research is a process through which new knowledge is discovered. A theory, such as a theory of motivation, or development, or learning, for example, helps us to organize this new information into a coherent body, a set of related ideas that explain events that have occurred and predict events that may happen. Theories are an important part of science. It is at the ground-floor level, however, that the researcher works to get the ball rolling, adding a bit of new insight here and a new speculation there, until these factors come together to form a corpus of knowledge.
High-quality research is characterized by many different attributes, many of which tend to be related to one another and also tend to overlap. High-quality research
· is based on the work of others,
· can be replicated,
· is generalizable to other settings,
· is based on some logical rationale and tied to theory,
· is doable,
· generates new questions or is cyclical in nature,
· is incremental, and
· is an apolitical activity that should be undertaken for the betterment of society.
Let’s take a closer look at each of these.
First, research is an activity based on the work of others. No, this does not mean that you copy the work of others (that’s plagiarism), but you always look to the work that has already been done to provide a basis for the subject of your research and how you might conduct your own work. For example, if there have been 200 studies on gender differences in aggression, the results of those studies should not be ignored. You may not want to replicate any one of these studies, but you certainly should take methodologies that were used and the results into consideration when you plan your own research in that area.
A good example of this principle is the tremendous intellectual and scientific effort that went into the creation of the atomic bomb. Hundreds of top scientists from all over the world were organized at different locations in an intense and highly charged effort to combine their knowledge to create this horrible weapon. What was unique about this effort is that it was compressed in time; many people who would probably share each other’s work in any case did so in days rather than months because of the military and political urgency of the times. What was discovered one day literally became the basis for the next day’s experiments (see Richard Rhodes’ Pulitzer Prize–winning book, The Making of the Atomic Bomb, for the whole story).
Second, while we’re talking about other studies, research is an activity that can be replicated. If someone conducts a research study that examines the relationship between problem-solving ability and musical talent, then the methods and procedures (and results) of the experiment should be replicable with other groups for two reasons. First, one of the hallmarks of any credible scientific finding is that it can be replicated. If you can spin gold from straw, you should be able to do it every time, right? How about using a new method to teach children to read? Or developing early intervention programs that produce similar results when repeated? Second, if the results of an experiment can be replicated, they can serve as a basis for further research in the same area.
Third, good research is generalizable to other settings. This means, for example, that if adolescent boys are found to be particularly susceptible to peer pressure in one setting, then the results would probably stand up (or be generalizable) in a different but related setting. Some research has limited generalizability because it is difficult to replicate the exact conditions under which the research was carried out, but the results of most research can lend at least something to another setting.
Fourth, research is based on some logical rationale and tied to theory. Research ideas do not stand alone merely as interesting questions. Instead, research activity provides answers to questions that help fill in pieces to what can be a large and complicated puzzle. No one could be expected to understand, through one grand research project, the entire process of intellectual development in children, or the reason why adolescents form cliques, or what actually happens during a midlife crisis. All these major areas of research need to be broken into smaller elements, and all these elements need to be tied together with a common theme, which more often than not is some underlying, guiding theory.
Fifth, and by all means, research is doable! Too often, especially for the young or inexperienced scientist (such as yourself), the challenge to come up with a feasible idea is so pressing that almost anything will do as a research topic. Professors sometimes see thesis statements from students such as, “The purpose of this research is to see if the use of drugs can be reduced through exposure to television commercials.” This level of ambiguity and lack of a conceptual framework makes the statement almost useless and certainly not doable. Good research poses a question that can be answered, and then answers it in a timely fashion.
Sixth, research generates new questions or is cyclical in nature. Yes, what goes around comes around. The answers to today’s research questions provide the foundation for research questions that will be asked tomorrow. You will learn more about this process later in this chapter when a method of scientific inquiry is described.
Seventh, research is incremental. No one scientist stands alone; instead, scientists stand on the shoulders of others. Contributions that are made usually take place in small, easily definable chunks. The first study ever done on the development of language did not answer all the questions about language acquisition, nor did the most recent study put the icing on the cake. Rather, all the studies in a particular area come together to produce a body of knowledge that is shared by different researchers and provides the basis for further research. The whole, or all the knowledge about a particular area, is more than the sum of the parts, because each new research advance not only informs us but it also helps us place other findings in a different, often fruitful perspective.
Finally, at its best, research is an apolitical activity that should be undertaken for the betterment of society. I stress “at its best,” because too often various special-interest groups dictate how research funding should be spent. Finding a vaccine for acquired immunodeficiency syndrome (AIDS) should not depend on one’s attitudes toward individual lifestyles. Similarly, whether early intervention programs should be supported is independent of one’s personal or political views. And should research on cloning be abandoned because of its potential misuse? Of course not. It’s how the discovery of new knowledge is used that results in its misuse, not the new knowledge itself.
Although it should be apolitical, research should have as its ultimate goal the betterment of society. Researchers or practitioners do not withhold food from pregnant women to study the effects of malnutrition on children. To examine the stress–nutrition link, researchers do not force adults to eat particular diets that might be unhealthy. These unethical practices would not lead to a greater end, especially because there are other ways to answer such questions without resorting to possibly harmful practices.
If these attributes make for good research, what is bad research? It takes the opposite approach of all the things stated earlier and then some. In sum, bad research is the fishing trip you take looking for something important when it simply is not to be found. It is plagiarizing other people’s work, or falsifying data to prove a point, or misrepresenting information and misleading participants. Unfortunately, there are researchers whose work is characterized by these practices, but they are part of an overall minority.
Note: At the end of every major heading in each chapter of Exploring Research, we’ll have a few questions for you that we hope will help you understand the content and guide your studying.
Provide an example of how research is incremental in nature and what advantage is this to both future and past researchers?
Think of an example of how knowledge about a certain topic can lead to new questions about that, or a related, topic.
A Model of Scientific Inquiry
In the past 20 years, the public has been exposed to the trials and tribulations of the research process as described through hundreds of books by and about the everyday work of scientists around the world.
“Doing science” means following a model that begins with a question and ends with asking new questions.
Regardless of the specific content of these books, they all have one thing in common. The work was accomplished through adherence to guidelines that allowed these researchers to progress from point A to point Z while remaining confident that they were on the trail of finding (what they hoped was) an adequate answer to the questions they had posed.
Their methods and their conclusions are not helter-skelter because of one important practice: They share the same general philosophy regarding how questions about human behavior should be answered. In addition, for scientists to be able to trust their colleagues, in the sense of having confidence in the results produced by their studies, these scientists must have something in common besides good intentions. As it turns out, what they share is a standard sequence of steps in formulating and answering a question.
When you read in a journal article that Method A is more effective than Method B for improving retention or memory, you can be pretty sure that the steps described next were followed, in one form or another. Because there is agreement about the general method used to answer the question, the results of this comparison of Method A and Method B can be applied to the next study. That study would perhaps investigate variations of Method A and how and why they work. The research efforts of developmental psychologists, gerontologists (specialists in aging), linguists, and experts in higher education all depend on the integrity of the process.
Figure 1.1 shows a set of such steps as part of a model of scientific inquiry. The goal of this model is to find the truth (whatever that means) or, in other words, to use a scientific method that results in a reasonable and sound answer to important questions that will further our understanding of human behavior.
Figure 1.1 The steps in the research process, wherein each step sets the stage for the next
An interesting and timely topic, the effects of using social media on adolescents’ social skills, will be used as an example of the different steps followed in this model.
Asking the Question
Remember the story of The Wizard of Oz? When Dorothy realized her need to get to the Emerald City, she asked Glinda, the good witch, “But where do I begin?” Glinda’s response, “Most people begin at the beginning, my dear,” is the case in almost any scientific endeavor.
Our first and most important step is asking a question (I wonder what would happen if . . . ?) or identifying a need (We have to find a way to …) that arises as the result of curiosity, and to which it becomes necessary to find an answer. For example, you might be curious about how the use of social media such as Twitter and Facebook affects relationships between children and their peers. You also might feel an urgency to find out how to use various types of media most effectively for educating children and adults about the dangers of using drugs.
Such questions are informally stated and often are intended as a source of discussion and stimulation about what direction the specific research topic should take. Where do such questions come from? They rarely come from the confines of a classroom or a laboratory. Rather, questions spring (in the fullest sense of the word) from our imagination and our own experiences, enriched by the worlds of science, art, music, and literature. It is no coincidence that many works of fiction (including science fiction) have a basis in fact. The truly creative scientist is always thinking about everything from solutions to existing questions to the next important question to ask. When Louis Pasteur said that chance favors the prepared mind, he was really saying, “Take advantage of all the experiences you can, both in and out of school.” Only then can you be well prepared to recognize the importance of certain events, which will act as a stimulus for more rigorous research activity.
Questions can be as broad as inquiring about the effects of social media on peer groups, or as specific as the relationship between the content of social media transactions and acceptance by peers. Whatever their content or depth of inquiry, questions are the first step in any scientific endeavor.
Identifying the Important Factors
Once the question has been asked, the next step is to identify the factors that have to be examined to answer the question. Such factors might range from the simplest, such as an adolescent’s age or socioeconomic status, to more complicated measures, such as the daily number of face-to-face interactions.
For example, the following list of factors have been investigated over the past 10 years by various researchers who have been interested in the effects of social media:
· age and gender of the adolescent,
· level of family education,
· access to types of social media,
· number of self-identified close friends,
· parental attitude toward social media,
· family configuration,
· family communication patterns.
And these are only ten of hundreds of factors and associated topics that could be explored. But of all the factors that could be important and that could help us to understand more about the effects of social media, which ones should be selected as a focus?
In general, you should select factors that
· have not been investigated before,
· will contribute to the understanding of the question you are asking,
· are available to investigate,
· hold some interest for you personally or professionally,
· lead to another question.
It is hard enough to define the nature of the problem you want to study (see Chapter 3) let alone generate questions that lead to more questions, but once you begin the journey of becoming a scientist, you are a member of an elite group who has the responsibility to contribute to the scientific literature not only by what you do but also by what you see that needs to be done.
Formulating a Hypothesis
When asked what she thought a hypothesis was, a 9-year-old girl said it best: “An educated guess.” A hypothesis results when the questions are transformed into statements that express the relationships between variables such as an “if . . . then” statement.
For example, if the question is, “What effects does using Facebook have on the development of friendships?” then the hypothesis could be, adolescents who use Facebook as their primary means of maintaining social contact have fewer close friends. Several characteristics make some hypotheses better than others, and we will talk about those in Chapter 2.
For now, you should realize that a hypothesis is an objective extension of the question that was originally posed. Although all questions might not be answerable because of the way in which they are posed—which is fine for the question stage—a good hypothesis poses a question in a testable form. Good questions lead to good hypotheses, which in turn lead to good studies.
Collecting Relevant Information
Hypotheses should posit a clear relationship between different factors, such as a correlation between number of followers on Twitter and quality of social skills. That is the purpose of the hypothesis. Once a hypothesis is formulated, the next step is the collection of information or empirical data that will confirm or refute the hypothesis. So, if you are interested in whether or not participating in social media has an impact on adolescent’s social skills, the kinds of data that will allow the hypothesis to be tested must be collected.
For example, you might collect two types of data to test the hypothesis mentioned in the previous paragraph. The first might be the number of friends an adolescent might have. The second might be the quality of those relationships.
An important point about testing hypotheses is that you set out to test them, not to prove them. As a good scientist, you should be intent on collecting data that reveal as much of the truth about the world as is possible and letting the chips fall where they may, whether you agree or disagree with the outcomes. Setting out to prove a hypothesis can place scientists in the unattractive position of biasing the methods for collecting data or the way in which study results are interpreted. If bias occurs, then the entire sequence of steps can fall apart. Besides, there’s really no being “wrong” in science. Not having a hypothesis supported means only that there are additional questions to ask or that those which were asked should be reformulated. That is the beauty of good science—there is always another question to ask on the same topic—one that can shed just a bit more light. And who knows? That bit more light might be the tipping point or just the amount needed to uncover an entirely new and significant finding.
Testing the Hypothesis
Is it enough simply to collect data that relate to the phenomena being studied? Not quite. What if you have finished collecting data and find that adolescents who spend more than 10 hours a week involved in social media have 50% fewer qualitatively “good” relationships with peers than those who spend less than 10 hours? What would your conclusion be?
On one hand, you could say the adolescents who used social media more than 10 hours per week were one-half as sociable as other adolescents or had one-half the quality of relationships of the children who used social media less than 10 hours per week. On the other hand, you might argue that the difference between the two groups of adolescents is too large enough for you to reach any conclusion. You might conclude that in order for a statement about social media use and quality of friendships, you would have to have much greater differences in the quality of relationships.
Say hello to inferential statistics (see Chapter 8 for more), a set of tools that allows researchers to separate the effects of an isolated factor (such as time spent on Facebook) from differences between groups that might be owing to some other factor or to nothing other than chance. Yes, luck, fate, destiny, the wheels of fortune, or whatever you want to call what you cannot control, sometimes can be responsible for differences between groups.
For example, what if some of the adolescents participating in your study went to some kind of social function where there was a particularly strong emphasis on social media methods of communicating such as texting. Or, what if one of the adolescents just was afraid to truthfully report how much time he or she spent on Facebook during study time?
The job of all the tools that researchers have at their disposal (and the ones you will learn about throughout Exploring Research) is to help you separate the effects of the factors being studied (such as amount of time spent on Facebook) from other unrelated factors (such as the number of years a family has lived at its current address). What these tools allow researchers to do is assign a probability level to an outcome so that you can decide whether what you see is really due to what you think it is due to or something else which you leave for the next study.
Working with the Hypothesis
Once you have collected the required data and have tested the hypothesis, as a good scientist you can sit down, put up your feet, look intellectual, and examine the results. The results may confirm or refute the hypothesis. In either case, it is off to the races. If the data confirm your hypothesis, then the importance of the factors that were hypothesized to be related and conceptually important were borne out and you can go on your merry way while the next scientific experiment is being planned. If the hypothesis is not confirmed, it may very well be a time for learning something that was not known previously. In the example used earlier, it may mean that involvement in social media has no impact on social skills or social relationships. Although the researcher might be a bit disappointed that the initial hunch (formally called a hypothesis) was not supported, the results of a well-run study always provide valuable information, regardless of the outcome.
Reconsidering the Theory
Finally, it is time to take stock and relate all these research efforts to what guides our work in the first place: theory. Earlier in this chapter, a theory was defined as a set of statements that predict things that will occur in the future and explain things that have occurred in the past. But the very nature of theories is that they can be modified according to the results of research based on the same assumptions on which the theory is based.
For example, a particular approach to understanding the development of children and adults is known as social learning theory, which places special importance on the role of modeling and vicarious, or indirect, learning. According to this theory, exposure to aggressive behavior would lead to aggressive behavior once the environment contains the same kinds of cues and motivation that were present when the initial aggressive model (such as particularly unkind Facebook postings) was observed.
If the hypothesis that observing such models increases lack of civility is confirmed, then another building block, or piece of evidence, has been added to the house called social learning theory. Good scientists are always trying to see what type of brick (new information) fits where, or if it fits at all. In this way, new knowledge can change or modify the way the theory appears and what it has to say about human behavior. Consequently, new questions might be generated from the theory that will help contribute further to the way in which the house is structured.
Asking New Questions
In any case, the last step in this simple model of scientific inquiry is to ask a new question. It might be a simple variation on a theme (Do males use social media in a different way than females?) or a refinement of the original question (How might the use of social media differentially affect the social relationships of males and females?). Whether or not the hypothesis is supported, good research leaves you farther along the trail to answering the original question. You just might be at a different place than you thought or intended to be.
Hypothesis plays a very important role in scientific research, with one of them being the objective testing of a particular question that a scientist might want to ask. What are some of the factors that might get in the way of the scientist remaining objective and what impact might that have on a fair test of the hypothesis of interest? What is the danger of not being aware of these biases?
Different Types of Research
By now, you have a good idea what research is and how the research process works. Now it is time to turn your attention to a description and examples of different types of research methods and the type of questions posed by them.
The types of research methods that will be discussed differ primarily on three dimensions: (1) the nature of the question asked, (2) the method used to answer it, and (3) the degree of precision the method brings to answering the question. One way in which these methods do not necessarily differ, however, is in the content or the focus of the research.
In other words, if you are interested in the effects of the use of social media on adolescents’ friendships, your research may be experimental, where you artificially restrict access to social media and look at friendship outcomes, or nonexperimental, where you survey a group of adolescents to determine the frequency of use of social media tools.
A summary of the two general categories of research methods (nonexperimental versus experimental), which will be discussed in this volume, is shown in Table 1.1. This table illustrates the purpose of each category, the time frame that each encompasses, the degree of control the different method has over competing factors, “code” words that appear in research articles that can tip you off as to the type of research being conducted, and an example of each. Chapters 9–12 discuss in greater detail each of these research methods.
Table 1.1 Summary of research methods covered in exploring research.
|Types of Research|
|Purpose||Describe the characteristics of an existing phenomenon||Relate events that have occurred in the past to current events||Examine the relationships between variables||To examine human behavior and the social, cultural, and political contexts within which it occurs||To test for true cause-and-effect relationships||To test for causal relationships without having full control|
|Time frame||Current||Past||Current or past (correlation) Future (prediction)||Current or past||Current||Current or past|
|Degree of control over factors or precision||None or low||None or low||Low to medium||Moderate to high||High||Moderate to high|
|Code words to look for in research articles||Describe Interview Review literature||Past Describe||Relationship Related to Associated with Predicts||Case study Evaluation Ethnography Historical Research Survey||Function of Cause of Comparison Between Effects of||Function of Cause of Comparison between Effects of|
|Example||A survey of dating practices of adolescent girls||An analysis of Freud’s use of hypnosis as it relates to current psychotherapy practices||An investigation that focuses on the relationship between the number of hours of television watching and grade-point average||A case study analysis of the effectiveness of policies for educating all children||The effect of a preschool language program on the language skills of inner-city children||Gender differences in spatial and verbal abilities|
There is one very important point to keep in mind when discussing different methods used in research. As often as not, as research becomes more sophisticated and researchers (like you in the future) become better trained, there will be increased reliance on mixed methods models, where both experimental and nonexperimental methods are combined. Some researchers feel that this type of approach lacks clarity and precision, but others feel it is the best way to look at a phenomenon of interest from a variety of perspectives and thereby be more informative.
Nonexperimental research examines the relationship between variables, without any attention to cause-and-effect relationships.
Nonexperimental research includes a variety of different methods that describe relationships between variables. The important distinction between nonexperimental methods and the others you will learn about later is that nonexperimental research methods do not set out, nor can they test, any causal relationships between variables. For example, if you wanted to survey the social media–using behavior of adolescents, you could do so by having them maintain a diary in which they record what tools they use and for how long.
This descriptive study provides information about the content of their online behaviors but tells you little about why they may do what they do. In this type of a research endeavor, you are not trying to understand the motivation for using what online tools are used nor are you trying to manipulate their use or content of the communication or any other outcome. This is nonexperimental in nature because no cause-and-effect relationships of any type are being hypothesized or investigated.
Nonexperimental research methods that will be covered in this volume are descriptive, correlational, and qualitative. Descriptive and correlational methods will be covered in Chapter 9, and qualitative methods will be discussed in Chapter 10. The following is a brief overview of each.
Descriptive research focuses on events that occur in the present.
Descriptive research describes the characteristics of an existing phenomenon. The every 10-year U.S. Census is an example of descriptive research as is any survey that assesses the current status of anything from the number of faucets in a house to the number of adults over 60 years of age who have grandchildren.
What can be done with this information? First, it provides a broad picture of a phenomenon you might be interested in exploring. For example, if you are interested in learning more about the reading process in children, you might want to consult The Reading Report Card (at http://nces.ed.gov/nationsreportcard/reading/). This annual publication summarizes information about the reading achievement of children ages 9, 13, and 17 years. Or you might want to consult a publication of the Centers for Disease Control and Prevention, the Morbidity and Mortality Weekly Report (at http://www.cdc.gov/mmwr/), to determine the current incidence of measles cases in the Midwest, or the Bureau of Labor Statistics (at http://www.bls.gov/) to determine the current unemployment rate and the number of working single parents who have children under age 5 (about 60%). If you want to know it, there is a place to find it. Descriptive research demands this type of information.
In another example, Eleanor Hanna, Hsiao-ye Yi, Mary Dufour, and Christine Whitmore (2001) examined the relationship of early smoking to alcohol use, depression, and drug use in adolescence. They used descriptive statistics and other statistical techniques to find that in comparison with those who never smoked, or those who simply experimented, early smokers were those most likely to use alcohol and other drugs as well as have school problems and early sexual experiences culminating in pregnancy.
Descriptive research can stand on its own, but it can also serve as a basis for other types of research in that a group’s characteristics often need to be described before the meaningfulness of any differences can be addressed. And almost always descriptive data is collected but as the first step of many on the way to a more complex study. Want to describe an outcome? Learn about descriptive techniques.
Descriptive and historical research provide a picture of events that are currently happening or have occurred in the past. Researchers often want to go beyond mere description and begin discussing the relationship that certain events might have to one another. The most likely type of research to answer questions about the relationship among variables or events is called correlational research.
Correlational research examines the relationship between variables.
What correlational research does, which neither descriptive nor historical research does, is to provide some indication as to how two or more things are related to one another or, in effect, what they share or have in common, or how well a specific outcome might be predicted by one or more pieces of information.
Correlational research uses a numerical index called the correlation coefficient (see Chapter 9 for a complete discussion) as a measure of the strength of this relationship. Most correlational studies report such an index when available.
If you were interested in finding out the relationship between the number of hours that first-year students spend studying and their grade-point averages, then you would be doing correlational research, because you are interested in the relationship between these two variables. If you were interested in finding out the best set of predictors of success in graduate school, you would be doing a type of correlational research that includes prediction.
For example, in a study of culture, obesity stereotypes, self-esteem, and the “thin ideal,” Klaczynski, Goold, and Mudry (2004) examined the relationships among negative stereotypes of obesity, and other variables such as perceptions of the causes of obesity and of control over weight and self-esteem. They found a negative correlation between beliefs in control over one’s weight and self-esteem.
One of the most important points about correlational research is that while it examines relationships between variables, it in no way implies that one causes changes in the other. In other words, correlation and prediction examine associations but not causal relationships, wherein a change in one factor directly influences a change in another.
For example, it is a well-established fact that as the crime rate in a community increases, so does the level of ice cream consumption! What’s going on? Certainly, no rational person would conclude that the two are causally related such that if ice cream were banned, no more crimes would occur. Rather, another variable, temperature, better explains the increased ice cream consumption and the increased crime rate (both rise when it gets warm). It might seem ridiculous that people would identify causality just because events are related, but you do not have to read far in the daily newspaper to discover that politicians can reach just such unwise conclusions.
Qualitative research studies phenomena within the social and cultural context in which they occur.
Qualitative research methods (see Chapter 10) are placed in this general category of nonexperimental methods because they do not directly test for cause and effect and, for the most part, follow an entirely different paradigm than the experimental model.
The general purpose of qualitative research methods is to examine human behavior in the social, cultural, and political contexts in which they occur. This is done through a variety of tools, such as interviews, historical methods, case studies, and ethnography, and it usually results in qualitative (or nonnumerical) primary data. In other words, the qualitative researcher is more (but not only) interested in the contents of an interviewee’s speech than in the number of times (frequency) a particular comment is made.
Qualitative research is relatively new to the social and behavioral sciences and, to a large extent, its increasing popularity is due to a degree of dissatisfaction with other available research methods. Some scientists feel that the traditional experimental model is too restrictive and narrow, preventing underlying and important factors and relationships from being revealed. What’s so valuable about this set of tools is that it allows you to answer a whole new set of questions in a whole new way.
Experimental research examines the cause-and-effect relationship between variables.
You already know that correlational research can help to establish the presence of a relationship among variables, but it does not provide any reason to believe that variables are causally related to one another. How does one find out if characteristics, behaviors, or events are related in such a way that the relationship is a causal one? Two types of research can answer that question: true experimental research and quasi-experimental research.
True experimental research examines direct cause-and-effect relationships.
True Experimental Research
In the true experimental research method, participants are assigned to groups based on some criterion, often called the treatment variable or treatment condition. For example, let us say that you are interested in comparing the effects of two different techniques for reducing obsessive-compulsive behavior in adults. The first technique includes behavioral therapy, and the second one does not. Once adults are assigned to groups and the programs are completed, you will want to look for any differences between the two groups with regard to the effects of the therapy on the frequency of obsessive-compulsive behaviors. Because the nature of the groups is determined by the researcher, the researcher has complete control over the factors to which the adults are exposed.
This is the ideal model for establishing a cause-and-effect relationship because the researcher has clearly defined the possible cause (if indeed it results in some effect) and can keep very close tabs on what is happening. Most important, however, the researcher has complete control over the treatment.
In a quasi-experimental study, the researcher does not have such a high degree of control because people have already been indirectly assigned to those groups (e.g., social class, type of abuse, gender, and type of injury) for which you are testing the effects.
The distinction between experimental and other methods of research boils down to a matter of control. True experimental research designs (discussed in Chapter 11) isolate and control all the factors that could be responsible for any effects except the one of most interest.