Naturalistic observation permits researchers to observe patterns of behavior in everyday settings, such as whether a particular event or behavior typically precedes another. Such observations can help researchers determine which behaviors are important to study in the first place. For example, a scientist who studies bullying by observing children’s play may notice that some victims act aggressively before a bullying encounter (Kamper-DeMarco & Ostrov, 2017). The scientist may then decide to examine aggression in victims not only after a bullying incident but also beforehand. Naturalistic observation is a useful way of studying events and behaviors that are common. Some behaviors and events, however, are uncommon or are difficult to observe, such as physical aggression among adults, requiring a researcher to observe for very long periods of time to obtain data on the behavior of interest. For this reason, many researchers make structured observations.
Structured observation entails observing and recording behaviors displayed in a controlled environment, a situation constructed by the experimenter. For example, children might be observed in a laboratory setting as they play with another child or complete a puzzle-solving task. The challenges of identifying and categorizing which behaviors to record are similar to those involved in naturalistic observation. However, the laboratory environment permits researchers to exert more control over the situation than is possible in natural settings. In addition to cataloguing observable behaviors, some researchers use technology to measure biological functions such as heart rate, brain waves, and blood pressure. One challenge to conducting structured observations is that people do not always behave in laboratory settings as they do in real life.
Self-Report Measures
Interviews and questionnaires are known as self-report measures because the person under study answers questions about his or her experiences, attitudes, opinions, beliefs, and behavior. Interviews can take place in person, over the phone, or over the Internet.
The interviewer is asking this young boy about his own experiences, opinions, and behavior. Interviews and questionnaires are known as self-report measures.
Per-Anders Petterson/Corbis News/ Getty Images
One type of interview is the open-ended interview, in which a trained interviewer uses a conversational style that encourages the participant, or the person under study, to expand his or her responses. Interviewers may vary the order of questions, probe, and ask additional questions based on responses. The scientist begins with a question and then follows up with prompts to obtain a better view of the person’s reasoning (Ginsburg, 1997). An example of this is the Piagetian Clinical Interview, which requires specialized training to administer. Consider this dialogue between Piaget and a 6-year-old child:
You know what a dream is?
When you are asleep and you see something
Where does it come from?
The sky
Can you see it?
No! Yes, when you’re asleep
Could I see it if I was there?
No.
Why not?
Because it is in front of us. … When you are asleep you dream and you see them, but when you aren’t asleep you don’t see them.
(Piaget, 1929, p. 93)
Open-ended interviews permit participants to explain their thoughts thoroughly and in their own words. They also enable researchers to gather a large amount of information quickly. Open-ended interviews are very flexible as well. However, their flexibility poses a challenge: When questions are phrased differently for each person, responses may not capture real differences in how people think about a given topic and instead may reflect differences in how the questions were posed and followed up by the interviewer.
A structured interview poses the same set of questions to each participant in the same way. On one hand, structured interviews are less flexible than open-ended interviews. On the other hand, because all participants receive the same set of questions, differences in responses are more likely to reflect true differences among participants and not merely differences in the manner of interviewing. For example, Evans, Milanak, Medeiros, and Ross (2002) used a structured interview to examine American children’s beliefs about magic. Children between the ages of 3 and 8 were asked the following set of questions: What is magic? Who can do magic?
Is it possible to have special powers? Who has special powers?
Does someone have to learn to do magic? Where have you seen magic? (p. 49)
After compiling and analyzing the children’s responses as well as administering several cognitive tasks, the researchers concluded that even older children, who have the ability to think logically and perform concrete operations, may display magical beliefs.
To collect data from large samples of people, scientists may compile and use questionnaires, also called surveys, made up of sets of questions, typically multiple choice. Questionnaires can be administered in person, online, or by telephone, email, or postal mail. Questionnaires are popular data collection methods because they are easy to use and enable scientists to collect information from many people quickly and inexpensively. Scientists who conduct research on sensitive topics, such as sexual interest and experience, often use questionnaires because they can easily be administered anonymously, protecting participants’ privacy. For example, the Monitoring the Future Study is an annual survey of 50,000 eighth-, tenth-, and twelfth-grade students that collects information about their behaviors, attitudes, and values concerning drug and alcohol use (Miech et al., 2017). The survey permits scientists to gather an enormous amount of data, yet its anonymity protects the adolescents from the consequences of sharing personal information that they might not otherwise reveal.
Despite their ease of use, self-report measures are not without challenges. Sometimes people give socially desirable answers: They respond in ways they would like themselves to be perceived or believe researchers desire. A college student completing a survey about cheating, for example, might sometimes look at nearby students’ papers during examinations, but she might choose survey answers that do not reflect this behavior. Her answers might instead match the person she aspires to be or the behaviors she believes the world values—that is, someone who does not cheat on exams. Self-report data, then, may not always reflect people’s true attitudes and behavior. Some argue that we are not always fully aware of our feelings and therefore cannot always provide useful insight into our own thoughts and behavior with the use of self-report measures (Newell & Shanks, 2014).
Physiological Measures
Physiological measures are increasingly used in developmental research because cognition, emotion, and behavior have physiological indicators. For example, when speaking in public, such as when you give a class presentation, do you feel your heart beat more rapidly or your palms grow sweaty? Increases in heart rate and perspiration are physiological measures of anxiety that might be measured by researchers. Other researchers might measure cortisol, a hormone triggered by the experience of stress (Simons, Cillessen, & de Weerth, 2017).
Some researchers measure eye movements or pupil dilation as indicators of attention and interest. For example, researchers who tracked participants’ eye movements as they viewed Facebook feeds learned that people are naturally attracted to social