Child Development From Infancy to Adolescence. Laura E. Levine
environments on children’s willingness to lie about their misbehavior.
Natural or “quasi” experiment: Research in which the members of the groups are selected because they represent different naturally occurring “treatment” conditions.
Children from both types of schools listened to a researcher play with a toy while they had their back turned to her. She then said she needed to leave the room for a while and told the child not to turn around to look at the toy while she was gone. When she returned, she asked the child if he or she had looked at the toy in her absence. Although the majority of the children from both types of schools peeked, many more of the children from the schools that used physical punishment denied what they had done. In other words, they lied about the fact that they had peeked. The researchers concluded that the punitive school environment gave children the motivation to lie as a way to protect themselves from punishment.
Similar to experiments conducted in a laboratory, researchers in this study controlled as many variables as possible with the exception of the variable they were interested in studying. Both schools were located in the same city and enrolled students from similar socioeconomic backgrounds. Students from the two schools also scored at a similar level on some standardized tests of cognitive ability. The relevant variable that differed between them was the discipline practices of the school they attended, so this was the independent variable in this study. The likelihood that they would lie about their misbehavior was the dependent variable measured at the end of the experiment.
One drawback in a natural experiment is that it is more difficult to rule out other factors that may affect the results. In a true experiment, some teachers would be randomly assigned to use physical punishment and a comparable group of teachers would be assigned to use nonphysical punishment. Clearly this research could only be done as a natural experiment because no teacher would agree to hit a child when that teacher did not believe in using physical punishment in a classroom. However, because this was a natural experiment, it is possible that teachers who were drawn to the school that used physical punishment differed from those who went to the other school in other ways that may have affected the students’ behavior. It is possible that it is the teacher’s personality or some other difference in the school environment that is responsible for the outcome rather than the use of physical punishment.
Correlational Designs
In a correlational research design, a researcher examines the relationship between two or more naturally occurring variables, such as self-esteem and children’s academic achievement. When we look at correlations, we are interested in two characteristics: the strength of the relationship and the direction of the relationship. Figure 2.8 will help you visualize these aspects of correlations as we describe them. We talk first about the direction of the relationship. Correlations can be positive or negative. In a positive correlation, the value of one variable increases as the value of the second variable increases. For example, lifetime earnings are positively correlated with the number of years in school. As years completed in school go up, so do lifetime earnings. In a negative correlation, as the value of one variable increases, the value of the second variable decreases. For example, the more often people brush their teeth, the lower their rate of tooth decay.
Correlational research design: Research that measures the strength and direction of the relationship between two or more variables that are not created by the experimenter.
The second characteristic of correlations is the strength of the relationship between the two variables. This can range from a correlation of +1.0 (a perfect positive correlation) to a correlation of –1.0 (a perfect negative correlation). At either of these extremes, a change of one unit of measurement in one of the variables is accompanied by a change of one unit of measurement in the second variable, so if we knew someone’s score on one variable, we could perfectly predict her score on the second variable. As a correlation moves from +1 or –1 toward 0, the relationship between the variables gets weaker and weaker. Look at Figure 2.8 for an illustration of a weak correlation versus a strong correlation. An increase in the value of one of the variables is now associated with a range of values for the second variable. For instance, the correlation between people’s shoe size and their IQ is probably close to zero so if you know someone’s shoe size there would be such a large range of possible IQs associated with it that you would not be able to predict what that person’s IQ would be. Many correlations in developmental research are in the moderate range of ±.15 to ±.40.
Figure 2.8 Examples of correlations.
Source: Adapted from Columbia University, 2015.
Let’s think about how you can use information from correlational data. If you read an article in your local newspaper that said, “Study finds that mothers who talk to their children a great deal have children with high self-esteem,” could we correctly conclude that frequent conversations with children will build their self-esteem? We could not. Because the researchers could not control how much mothers in this study talked to their children, this is clearly correlational research. Correlational research tells us that there is a relationship between two variables (in this case, mothers’ conversations and children’s self-esteem), but a third variable that wasn’t even measured might be responsible for the relationship we observed. For instance, it may be that the mothers who talked a lot to their children were also ones who gave their children a lot of praise and positive feedback. In this case, it would be the nature of what they said rather than the amount of conversation that affected the children’s self-esteem. For this reason, we must use caution when interpreting correlational findings because the fact that two things occur together does not mean that one of them necessarily caused the other.
In Chapter 1, you were advised to be a careful consumer of information about development. If you know that when there is a correlation between two variables it is not the same thing as saying that one causes the other, it will make you a better consumer of information you might hear on television or read on the Internet.
TRUE/FALSE VIDEO
T/F #10
Even if research consistently finds that children whose mothers talk to them a great deal have high self-esteem, we should not conclude that frequent conversations with parents build self-esteem in children. True
Developmental Research Designs
Each of the methods we’ve described can test scientific hypotheses, but each can also be used within research designs that look at development. Three developmental research designs are longitudinal, cross-sectional, and sequential.
A longitudinal design follows one group of individuals across time and looks at the same or similar measures at each point of testing. The biggest advantage of a longitudinal study is that it gives us the clearest picture of how the variables we are interested in change as a function of age. However, it takes a good deal of time and money to conduct multiple waves of data collection for a large group of individuals. Many researchers do not have the resources necessary to conduct this type of research. Also, because participants need to be tested or measured repeatedly over the course of the study, it is inevitable that some will drop out, and that may compromise the representative nature of the original sample. For example, children from low-income families tend to change schools more frequently than children from more affluent families. If you are doing your research in a school, over time it is likely that more students from low-income families will move away during the course of the study, so by the end of the study, those left in your sample may be of a higher socioeconomic status than your original group. If this happens,