Methods of Studying Children

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METHODS OF STUDYING CHILDREN

When a researcher decides to study children, the task usually begins by choosing a topic or behavior to study and then focusing on a basic method that will allow the information to be gathered in the most efficient and effective manner. Researchers of child development have a variety of research methods from which to choose. These methods differ in important ways. For example, in a case study, the research tends to not intrude very much into the lives of the subjects of the study, and experimental control is not a major concern of the researcher. Conversely, in an experimental or quasi-experimental study, the research is typically more intrusive, and the researchers desire a certain amount of experimental control. Understanding the strengths and weaknesses of each method plays an important role in deciding which one to use in a particular study.

The type of method the researcher chooses is driven by several factors: the hypothesis that is being tested or the research question that is being asked, the type of information that is being gathered, how the study is designed, the number of participants, and any ethical considerations that relate to the participants. No matter which method is used, it is imperative that the research be conducted according to scientifically accepted procedures.

One of the first tasks of the child development researcher is to decide on a basic method by which to collect information. Scientific inquiries generally fall into two broad categories: those conducted using qualitative methods and those conducted using quantitative methods. As the word "qualitative" implies, qualitative methods employ nonnumeric designs and attempt to study phenomena inductively, as a process, and in the place in which the phenomena occur. Conversely, the quantitative approach attempts to measure phenomena numerically and make conclusions deductively and with respect to outcomes or products. Both approaches are well represented in the study of children.

Qualitative Methods of Child Study

The major types of qualitative methods include observation, self-reports, and the case study. Researchers often choose to view behavior directly through some kind of systematic observation. There are a number of options depending upon the level of intrusion that is desired and the type of environment in which the observation is to occur. The least intrusive form of observation is called naturalistic. In conducting a naturalistic observation, the researcher observes behavior in a natural environment, such as in a home, day-care, or school setting. This can be an excellent way to observe what happens in the everyday setting. The drawback, however, is that the researcher has little control over the environment and, consequently, over any extraneous variables (factors other than the behavior being researched). Furthermore, the behavior may not be displayed very often, or at all, during the observation. To remedy this problem, the researcher may choose to set up the observation in a place where the conditions are the same for all participants. A laboratory setting or contrived classroom, for example, could be set up for this purpose. In such a setting, unfortunately, participants may not behave in the same way that they would in a normal setting. Regardless of how the observation is set up, data from observations, sometimes referred to as field notes, must be studied carefully for themes and major ideas.

The use of self-reports is another option for gathering information qualitatively. There are two forms of self-reports. The first is the interview method, in which the researcher poses questions to participants in either informal or formal settings and records the responses. The second form is the self-report instrument, in which participants respond to a questionnaire or some other type of structured instrument. Both forms have advantages and disadvantages. Structured instruments provide control over external and extraneous stimuli, permit comparisons of the responses, and aid in efficient data collection. Interviews may provide richer information and could tap aspects of the participants that go unmeasured in structured instruments, such as how the participants think and function in the natural setting. Unfortunately, the results of the open interview are difficult to use for comparison purposes among individuals or groups of individuals. The rich data gained through interviews could come at the cost of standardization, thereby ruling out comparisons across participant responses.

The third qualitative method of research is the clinical method, or case study. The case study allows the researcher to gain detailed information on one individual's development. The rich data provides an extensive picture of the developmental process of an individual. In turn this means that there is only one person in the study and that any conclusions that are drawn cannot be easily generalized to other individuals.

Quantitative Methods of Child Study

There are three types of quantitative methods of study: correlational, experimental, and quasi-experimental. To some degree each of these designs allows the researcher to identify relationships between different factors and to then specify the causes of these relationships. The initial responsibility of the researcher is to find the general design that tests the hypothesis with the maximum amount of clarity.

The correlational design is used to determine whether relationships exist between two or more variables. Ultimately the investigator wants to determine whether a change in one variable coincides with a change in a second variable. In a correlation design no variable manipulation occurs. For example, a child's behaviors are measured as they naturally occur, and a numerical index reflecting the relationship between the measures' outcomes is then computed. Usually, a correlation coefficient is used to calculate the strength and type (positive or negative) of relationship that exists. While the correlational design is extremely useful, it cannot be used to determine cause-effect relationships between variables. The primary reason for this is that variables other than the ones under study cannot be controlled, measured, or otherwise considered in the correlational design; such variables could influence the relationship between the variables under study. This kind of control is afforded only in designs in which variables can be manipulated and participants can be randomly assigned to groups.

An experimental design does allow cause-effect conclusions since variables can be manipulated and participants can be randomly assigned. With respect to manipulation of variables, the researcher must assign independent and dependent variables to the experiment. The independent variables are the various treatments that the participants receive (and that are manipulated by the researcher), while the dependent variable represents the responses of the participants. For example, an independent variable might represent the amount of direct reading instruction students receive, and the dependent variable might be reading achievement scores. In essence, the researcher wants the dependent variable to reflect the effect of being treated with the independent variable. Experimenter control of the independent variable (e.g., amount, duration, and type of treatment) partially affords the necessary confidence to reach cause-effect conclusions. In other words, differences in the dependent variable may then be attributed to the various treatments the participants received (in the example, differences in reading achievement scores may be attributed to the various amounts of direct reading instruction).

In order to say that the treatment has caused some effect (on the dependent variable), it is important that all the traits of the participants be about the same, especially those that could confound the study. One way to accomplish such group equality is to randomly assign participants to groups. In essence, when "chance" is the force behind who gets the various treatments, it is assumed that the groups contain participants who were more or less alike prior to receiving treatments.

The ability to gain the necessary control that allows for cause-effect conclusion is also an important shortcoming of the experimental design. Conducting research in a controlled setting may alter the natural behavior patterns of participants and therefore decrease the "ecological validity" of the results. The researcher must also stay within ethical bounds, meaning that treatments that have adverse physical or psychological effects on participants cannot be used. Finally, the requirement of random assignment may not be possible for ethical or practical reasons.

To counter the latter drawback to the experimental design, a researcher might turn to the quasi-experimental design. The quasi-experimental method permits the researcher to compare groups that have been manipulated but not randomly assigned. For example, in the above example of a study of the effect of direct reading instruction on reading achievement, suppose that homerooms have already been assigned in the school where the researcher intends to conduct the study. It may still be possible to treat different classes, but the researcher must take into account that the participants were not randomly assigned to the classes. In such a case, a quasi-experimental design could be used, but the researcher must temper any cause-effect conclusions because of the possibility that uncontrolled variables "caused" the results.

Finally, it may not be possible to manipulate variables or randomly assign participants to groups. In this case, a causal comparative design might be used. In the causal comparative method, already existing groups are studied (after the "independent variable" has already occurred) and group differences are studied on some dependent variable of interest. For example, a researcher might choose to study the intellectual development of children in orphanages compared to that of children raised in a home setting with their biological parents. The causal comparative design is often used to study treatments that would be unethical to impose on participants. Obviously, the causal-comparative design offers little of the control necessary to make cause-effect conclusions.

Longitudinal versus Cross-Sectional Studies

By the very nature of their field of study, child development researchers are concerned with change that occurs over time. This fact brings to light another research design choice that must be considered: longitudinal research versus cross-sectional research. Longitudinal studies involve studying the same group of participants over a particular time period. Cross-sectional studies involved studying groups of participants in different age groups at the same point in time. It would seem that longitudinal research would be the developmental researcher's first choice, but because of some of the disadvantages of that method, developmental researchers must sometimes use the cross-sectional method.

In a longitudinal study, a researcher performs repeated observations or testing at specified points during the participants' lives, thus allowing the observation of development. The time span involved may be anywhere from a few months to a lifetime. This design provides the best information about the continuity or discontinuity of behavior over time and allows for the individual tracking of patterns of behavior, as well as trends of development, within a similar group. The problems of this type of design can often override the benefits. It is expensive to study a large group of individuals over an extensive time span. Keeping up with these individuals can be costly and time consuming. Participants may move away from home and local communities, and therefore drop out of the study. Sometimes the participants become wise to the testing or observations and practice over repeated measures and contaminate the results. Cohort effects may also be a factor in the outcomes of longitudinal studies. Cohort effects are common characteristics or trends in development for one cohort or group that may not follow suit for another cohort. To try to alleviate some of these potential problems, researchers often study small groups of individuals; but this may make it difficult to generalize the findings to a larger group.

Cross-sectional studies are quick by nature in that a researcher does not have to follow the development of each individual. At the same time a researcher does not gain the rich data on individual development that can be garnered from longitudinal studies, since the evidence of change is inferred from differences between the age groups. The cross-sectional design is also affected by the cohort effect where age differences may show trends particular to a specific group and not true developmental changes. Thus, while the cross-sectional design solves some the problems associated with a longitudinal design (e.g., subject dropout and cost), the cross-sectional design still suffers some disadvantages (e.g., age differences do not show age change and cohort effects).

Summary

Qualitative and quantitative research methods can be used in child development studies. The decision on which method to use is typically based on the research question of interest and how researchers have previously attempted to address the question. With respect to qualitative methods, the researcher's job is to study the topic in its natural context with as little intrusion as possible. In the quantitative method, the researcher's job, after conceptualizing the study, is to define the dependent and independent variables or decide whether this kind of control is possible. In instances where variables cannot be controlled, the researcher must use appropriate methods to control for differences or use correlations to determine how the variables may be related to each other. Using representative sampling is imperative to be able to generalize the study to other populations and settings. In either approach to child development research, the ability to uncover interesting data and to replicate it helps strengthen the field as a whole.

See also:THEORIES OF DEVELOPMENT