From Existing Research

      Students planning a research project must read the existing literature in the area. After all, you don’t want to reinvent the wheel! Once you have an idea about the general area you are interested in, you should read what has been found already. No doubt, as you read the research, you will think of potentially interesting variables, populations, or methods that have not been investigated. The existing research is a great source of ideas for research topics. Understanding empirical research articles can be challenging if you are not already familiar with the topic, but the next chapter (Chapter 2) will provide help. There we will give you an overview of the parts of a research article and describe, at a conceptual level, the most common statistical analyses you will likely read about.

      Common Sense

      Psychology, more than other sciences, yields research topics based on common sense or folk wisdom. Earlier, we talked about commonsense folk wisdoms such as Absence makes the heart grow fonder and Out of sight, out of mind. Research topics can be generated from common sense, and, indeed, a lot of research has been done to test the veracity of folk wisdom.

      A New Technology

      New technology can be a source of research topics. MRI (magnetic resonance imaging), for example, has allowed researchers to investigate what is going on in the brain during various activities. This kind of research was not possible before the development of the technology. The Internet is an obvious example of new technology that has allowed researchers to collect data that they could not easily have collected previously.

      In psychology, interesting research topics are all around us. “Why do people do what they do?” is a question we have all asked ourselves. No matter what has inspired your research question, at some point you will need to think about hypotheses that you can test.

      Generating Testable Hypotheses

      To generate testable hypotheses, you must operationalize your concepts. An operational definition is a description of how a concept will be measured. We talked a bit about the Harlows’ research earlier. One of their research questions was “Is contact comfort a source of attachment in monkeys?” How did they make the concepts contact comfort and attachment measurable? Read on.

      They created what they called a surrogate “mother monkey” made of wire and a second made of soft fabric. In essence, their operational definition of high-contact comfort was the soft, cuddly “mother,” and their operational definition of low-contact comfort was the cold wire “mother.” Attachment was operationalized as the “mother” the infant clung to when stressed.

      Students often ask us how they can tell whether an operational definition is a good one or not. This is an excellent question. Just because one researcher has an operational definition of a concept does not guarantee that it is a good operational definition. We usually advise students to read the literature in the area and see what most researchers tend to do, check whether measures of reliability and validity have been taken, and go from there.

      Once you have defined your research topic and generated testable hypotheses, you then must determine which variables you are going to manipulate, which variables you will control, and which variables you will measure.

      Classifying Variables

      Research in psychology involves various kinds of variables. There are variables you want to manipulate (independent variables) to see if they affect other variables that you measure (dependent variables). Then there are variables you want to control (control variables). Researchers must determine how they will define these variables so that they can be measured and controlled. The Harlows, as we discussed earlier, in one experiment, manipulated the contact comfort of the surrogate mother monkey—this was an independent variable (high- and low-contact comfort). The attachment behavior of the infant (i.e., which surrogate the infant clung to when stressed) was the dependent variable. The size of the surrogate mother, the type of event that produced stress, and the size of the cage were control variables in that they were constant. Researchers have to consider the potentially important variables when they decide how to test their hypotheses.

      You have your hypothesis, and you have decided what variables you will measure and control. Now you must select the research design.

      Selecting an Appropriate Design

      Selecting an appropriate design is a complex task. You will need to consider all sorts of things as you make this decision. Practical factors, such as time, money, and facilities; the nature of your research question; and the kinds of variables you intend to measure must be taken into account when you select a design. The research design often dictates the analysis. You must think about how the data can be analyzed, given your measures and design. You do not want to find yourself in a position of having collected data that cannot be analyzed the way you intended.

      Once the research design has been selected, you need to figure out how to carry it out.

      Planning the Method and Carrying It Out

      The method should be carefully planned in advance. How will you select your participants? Where and when will you gather your data? How many participants will you need? What are the ethical considerations of your research? Who is responsible for reviewing the ethics of your research? Although the method should be planned in advance, you will need to allow for adjustments if something does not go as you expected. Perhaps you discover that your first couple of participants misinterpreted an instruction. How will you deal with that?

      The data have been collected. Now what?

      Analyzing Results

      The design and the nature of the measures you took will determine the appropriate analysis. In Chapter 13, we will cover the statistical analyses that students are most likely to need for their research projects. Once the data have been analyzed, it is time to interpret the findings and draw conclusions.

      Drawing Conclusions

      The next step of the research endeavor is to interpret the results and draw conclusions. This is not easy. Researchers must be careful not to go too far from their results. There is a fine line between justifiable conclusions and wild speculation. Your conclusions must include a discussion of how your results fit into the literature. How do your results support the conclusions of other researchers, and how do they disagree with others’ findings? Do they support one theory but not another?

      Sharing Your Findings

      Of course, researchers do not keep their findings