Experimental Research Studies

If researchers want to be able to claim a cause and effect about their variables – they need to do an experimental study. The Mueller and Oppenheimer (2014) study is an example of such a study.  Because these researchers manipulated the conditions by assigning students to computer or hand notes, they can make some causal claims about note-taking and test scores. Keep in mind, however, that any claim made about an experiment might not be generalizable to other contexts, meaning we can’t be sure how far we can take a causal claim from one context and apply it to another.

In order to assess whether you understand the note-taking study (or any other research), you should ask yourself the following:

• What was the question being addressed by the investigator(s)?
• How did the procedures enable the question to be addressed?
• What were the results and conclusions regarding the question?

This research study used the scientific method. It was systematic and it asked an empirical question – Does the method of note-taking play a role in retention of lecture content? You can ask many different kinds of questions with experiments, but they all have the same basic design features. Let’s take a look at the features. Firstly, researchers always systematically change one variable, and then measure the impact of those changes on another variable. A variable is just something we can vary or measure in some way. The variable that is under the experimenters’ control is called the independent variable. In the case of the Study 1 of the note-taking experiments, the independent variable was the note-taking method. There were two conditions (options) – handwriting and laptop. The researchers (not the participants) decide on the options. This is what we mean by manipulating a variable. Experiments investigate whether the independent variable causes a change in the dependent variable. In this example, the participants’ learning is the dependent variable, because it depends on how the they took their notes (independent variable). The independent variable is often thought of as the “cause” and the dependent variable – “the effect” (see Figure 3.2). Mueller and Oppenheimer were able to conclude that group differences in learning were caused by how they took their notes.

Did the results of the note-taking study surprise you at first? If they did, you might have felt a little skeptical about it before reading the further analyses.  You might have thought, “Doesn’t learning depend on a lot of different factors—including a person’s attention and desire to learn, time spent studying, their prior knowledge,  or life circumstances? What if some people were bored by the lectures and didn’t pay attention? Wouldn’t people who are having a bad day perform worse on the quizzes? You are absolutely right and you are thinking like a psychologist! All of these factors (and many more) can easily affect a person’s performance on quiz questions. So, how can we take all of these different variables into account? A second feature of experiments that helps to compensate for these individual differences across people, is that they all use random assignment. In other words, participants cannot pick which group they are in, the experimenter assigns them to a particular condition or group randomly. This might be based on the flip of a coin, the roll of a die, or the generation of a random number by a computer. Random assignment makes it so the groups are relatively similar on all characteristics, except the one that the experimenter wants to manipulate. In Mueller and Oppenheimer’s study, there should be equal numbers of people with strong attention skills and  equal numbers of people who were having a bad day in each group.

The researchers manipulated whether or not students took notes using their computer or by hand (independent variables) and measured the outcome (dependent variable). Another aspect of experiments is that the dependent variable must be quantifiable, in other words, it must be measurable in some way using numbers. In the note-taking experiments  the researchers gave students a 40-question quiz to measure their retention of the lecture material.  Then, they compared scores on the quiz among the note-taking groups (conditions) using statistics.

(insert better graph here)

Psychologists use statistics in quantitative studies to assess whether group differences in the dependent variable are meaningful and reliable, or merely due to chance. In experimental research, there is a tremendous amount of control over the variables of interest. This is a powerful approach. However, psychology experiments are often conducted in artificial settings, like labs, and complex phenomena are reduced to simple numbers. It is sometimes difficult to know whether experimental findings would apply in real-world settings. This is one of the reasons why it is important that psychology as a discipline includes multiple types of research methods to build knowledge about the mind and behavior.

Quasi-Experimental Designs

Keeping with the note-taking study for just a bit longer, how could the effect be tested in a more real-world setting? If you said “test it in a real classroom” you’re thinking like a psychologist again! If this study was done, the researchers *could* manipulate note-taking by randomly assigning students in a classroom to note-taking conditions (and thus design a true experiment), but as soon as they did that they would remove some of “reality” because students typically choose their own method of note-taking. If they simply asked or observed which method students use, and then gave the quiz, they would not  use random assignment for their pen or laptop groups.

Here’s the part that tends to get confusing: although the researcher is not using random assignment, there IS an independent variable. We not longer think of it as being “manipulated” or “controlled” but as the variable that groups are assigned on. So instead of using random assignment to divide up the note-taking groups, we use the independent variable grouping that already exists to create the groups. The research design still has an independent variable (note-taking method), and a dependent variable (learning).  The study design used here is known as a quasi-experiment.

Let’s look at another example to illustrate quasi-experiment. Imagine a professor teaches two class sections of the same course: one in the morning and one in the afternoon. You want to know whether students in the morning earn the same grades as those in the afternoon.  To judge this, you’re going to look at the final grades in each section. Letter grades can easily be turned into numbers (for quantitative research). Here, the independent variable is the class time and the dependent variable is the students’ grades. In an experimental design, you would randomly assign students to one of the two class sections and then compare the students’ final grades. However, in real life, researchers can’t randomly force students to take one class over another. Instead, the researchers would just have to study the classes as they stand (quasi-experimental design). Students’ choice of class rime may seem random, but it’s most likely not. Some students know that they learn better at certain times of day, or their other courses determine their availability. Maybe the morning class is very early (like 8:00 am) which most college students do not like. But, since some schools allow Honors students (who typically have better grades than other students) to register first, the afternoon class could have more honors students than the morning class and this might affect the average grades in the class. So, even though a quasi-experimental design is similar to an experimental design (i.e., it has independent and dependent variables), because there’s no random assignment you cannot reasonably draw the same conclusions that you would with an experimental design. However, quasi-experiments are still very useful in providing information about different groups of people, based on various aspects of their identity, or their demographics.