RESEARCH METHODS IN Education Course Code MajB Eds312

RESEARCH METHODS IN Education Course Code: Maj/B. Eds-312 Instructor: Dr. Ghazala Noureen Associate Professor Department of Education(Planning & Development) Lahore College for Women University, Lahore. B. Ed(Hons) Secondary Semester VI Session(2017 -21) Spring 2020

Unit. 9 Causal Comparative

What Is Causal-Comparative Research? In causal-comparative research, investigators attempt to determine the cause or consequences of differences that already exist between or among groups of individuals. As a result, it is sometimes viewed, along with correlational research, as a form of associational research, since both describe conditions that already exist. A researcher might observe, for example, that two groups of individuals differ on some variable (such as teaching style) and then attempt to determine the reason for, or the results of, this difference. The difference between the groups, however, has already occurred. Because both the effect(s) and the alleged cause(s) have already occurred, and hence are studied in retrospect, causalcomparative research is also referred to sometimes as ex post facto (from the Latin for “after the fact”) research. This is in contrast to an experimental study, in which a researcher creates a difference between or among groups and then compares their performance (on one or more dependent variables) to determine the effects of the created difference

cont In causal–comparative research the researcher attempts to determine the cause, or reason, for existing differences in the behavior or status of groups or individuals. In other words, established groups are already different on some variable, and the researcher attempts to identify the major factor that has led to this difference.

cont A researcher may hypothesize that participation in preschool education is the major factor contributing to differences in the social adjustment of first graders. To examine this hypothesis, the researcher would select a sample of first graders who had participated in preschool education and a sample of first graders who had not and would then compare the social adjustment of the two groups. If the children who participated in preschool education exhibited the higher level of social adjustment, the researcher’s hypothesis would be supported. Thus, the basic causal–comparative approach involves starting with an effect (i. e. , social adjustment) and seeking possible causes (i. e. , did preschool affect it).

Following are some examples of different types of causalcomparative research. Type 1: Exploration of effects (dependent variable) caused by membership in a given group Question: W hat differences in abilities are caused by gender? Research hypothesis: Females have a greater amount of linguistic ability than males. Type 2: Exploration of causes (independent variable) of group membership Question: What causes individuals to join a gang? Research hypothesis: Individuals who are members of gangs have more aggressive personalities than individuals who are not members of gangs. Type 3: Exploration of the consequences (dependent variable) of an intervention Question: How do students taught by the inquiry method react to propaganda? Research hypothesis: Students who were taught by the inquiry method are more critical of propaganda than are those who were taught by the lecture method.

Types of Causal Comparative There are two types of causal comparative research Retrospective causal comparative research: The basic approach, which involves starting with effects and investigating causes, is sometimes referred to as retrospective causal–comparative research. prospective causal–comparative research : The variation, which starts with causes and investigates effects, is called prospective causal–comparative research.

Causal-Comparative Research Facts Causal-Comparative Research is not manipulated by the researcher. -Does not establish cause-effect relationships. -Generally includes more than two groups and at least one dependent variable. -Independent variable in causal-comparative studies is often referred to as the grouping variable. -The independent variable has occurred or is already formed.

SIMILARITIES AND DIFFERENCES BETWEEN CAUSAL-COMPARATIVE AND CORRELATIONAL RESEARCH Causal-comparative research is sometimes confused with correlational research. Although similarities do exist, there are notable differences. Similarities. Both causal-comparative and correlational studies are examples of associational research— that is, researchers who conduct them seek to explore relationships among variables. Both attempt to explain phenomena of interest. Both seek to identify variables that are worthy of later exploration through experimental research, and both often provide guidance for subsequent experimental studies. Neither permits the manipulation of variables by the researcher, however. Both attempt to explore causation, but, in both cases, causation must be argued; the methodology alone does not permit causal statements.

Differences. Causal-comparative studies typically compare two or more groups of subjects, while correlational studies require a score on each variable for each subject. Correlational studies investigate two (or more) quantitative variables, whereas causal-comparative studies typically involve at least one categorical variable (group membership). Correlational studies often analyze data using scatterplots and/or correlation coefficients, while causalcomparative studies often compare averages or use cross break table

SIMILARITIES AND DIFFERENCES BETWEEN CAUSAL-COMPARATIVE AND EXPERIMENTAL RESEARCH Similarities. Both causal-comparative and experimental studies typically require at least one categorical variable. Both compare group performances (average scores) to determine relationships. Both typically compare separate groups of subjects. * Differences. In experimental research, the independent variable is manipulated; in causal-comparative research, no manipulation takes place. Causal-comparative studies are likely to provide much weaker evidence for causation than do experimental studies. In experimental research, the researcher can sometimes assign subjects to treatment groups; in causalcomparative research, the groups are already formed—the researcher must locate them. In experimental studies, the researcher has much greater fl exibility in formulating the structure of the design.

Basic Characteristics of Causalcomparative research In short it the basic Characteristics of Causal-comparative research can be concluded: Causal comparative research attempts to determine reasons, or causes, for the existing condition Causal comparative studies are also called ex post facto because the investigator has no control over the exogenous variable. Whatever happened occurred before the researcher arrived. -Causal-comparative research is sometimes treated as a type of descriptive research since it describes conditions that already exist. -Causal-comparative studies attempt to identify cause-effect relationships; correlational studies do not

-Causal-comparative studies involve comparison, correlational studies involve relationship. -Causal-comparative studies typically involve two (or more) groups and one independent variable, whereas correlational studies typically involve two or more variables and one group -In causal-comparative the researcher attempts to determine the cause, or reason, for preexisting differences in groups of individual. Involves comparison of two or more groups on a single endogenous variables. -Retrospective causal-comparative studies are far more common in educational research

-The basic approach is sometimes referred to as retrospective causalcomparative research (since it starts with effects and investigates causes) -The basic causal-comparative approach involves starting with an effect and seeking possible causes. The characteristic that differentiates these groups is the exogenous variable. -The variation as prospective causal-comparative research (since it starts with causes and investigates effects) We can never know with certainty that the two groups were exactly equal before the difference occurred.

Steps for conducting a Causalcomparative research STEP ONE- PROBLEM FORMULATION; The first step in formulating a problem in causal- comparative research is usually to identify and defi ne the particular phenomena of interest and then to consider possible causes for, or consequences of, these phenomena. Suppose, for example, that a researcher is interested in student creativity. What causes creativity? Why are a few students highly creative while most are not? Why do some students who initially appear to be creative seem to lose this characteristic? Why do others who at one time are not creative later become so? And so forth.

STEP TWO -Review of literature Before trying to predict the causal relationships, the researcher needs to study all the related or similar literature and relevant studies, which may help in further analysis, prediction and conclusion of the causal relationship between the variables under study. Reviewing published literature on a specific topic of interest is specially important when conducting Caucal-comparative research as such a review can assist a researcher in determining which extraneous variable may exist in the situations that they are considering studying.

STEP THREE- Develop a Research hypothesis The third step of the research is to propose the possible solutions or alternatives that might have led to the effect. They need to list out the assumptions which will be the basis of the hypothesis and procedure of the research. Hypothesis developed for Causal-comparative research to identify the independent and dependent variable Causal-comparative hypothesis should describe the expected impact of the independent variable on the dependent variable.

STEP FOUR-Select participants Once the researcher has formulated the problem statement, the next step is to select the sample of individuals to be studied. The most important task here is to define carefully the characteristic to be studied and then to select groups that differ in this characteristic. The researcher also needs to think about whether the group are reasonably homogeneous except independent variable. For example, are students who are creative in science similar to students who are creative in art with respect to causation? This is a very important question to ask. If creativity has different “causes” in different fields, the search for causation is only confused by combining students from such fields. Do ethnic, age, or gender differences produce differences in creativity? The success of a causal-comparative study depends in large degree on how carefully the comparison groups are defined.

STEP FIVE- Select instruments Causal-comparative research requires that researcher selects instruments that are reliable and allow researchers to draw valid conclusions( Link to reliability and validity). They also need to select the scale or construct instrument for collecting the required information / data. After a researcher has selected a reliable and valid instrument, data for the study can be selected.

Step 6: Design The basic causal-comparative design involves selecting two or more groups that differ on a particular variable of interest and comparing them on another variable or variables. No manipulation is involved. The groups differ in one of two ways: One group either possesses a characteristic (often called a criterion ) that the other does not, or the groups differ on known characteristics.

Data Collection Data collection for casual comparative is different from researches. Questionnaires, achievement tests, personality inventory, attitude scale and observational checklist can be used to collect data. All the approaches which are previously discussed in survey research can be used to collect data.

Control Procedures Lack of randomization and manipulation are sources of weakness in a causal –comparative study. In other study designs, random assignment of participants to groups is probably the best way to try to ensure equality of groups, but random assignment is not possible in causal–comparative studies because the groups are naturally formed before the start of the study. There are three control techniques: matching, comparing homogeneous groups or subgroups, and analysis of covariance

Matching is a technique for equating groups on one or more variables. If researchers identify a variable likely to influence performance on the dependent variable, they may control for that variable by pairwise matching of participants. In other words, for each participant in one group, the researcher finds a participant in the other group with the same or very similar score on the control variable. If a participant in either group does not have a suitable match, the participant is eliminated from the study. Thus, the resulting matched groups are identical or very similar with respect to the identified extraneous variable.

Example If a researcher matched participants in each group on IQ, a participant in one group with an IQ of 140 would be matched with a participant with an IQ at or near 140 in the other group. A major problem with pair-wise matching is that invariably some participants have no match and must therefore be eliminated from the study. The problem becomes even more serious when the researcher attempts to match participants on two or more variables simultaneously.

Comparing Homogeneous Groups or Subgroups Another way to control extraneous variables is to compare groups that are homogeneous with respect to the extraneous variable. In the study about preschool attendance and first-grade achievement, the decision to compare children only from wellto-do families is an attempt to control extraneous variables by comparing homogeneous groups. If, in another situation, IQ were an identified extraneous variable, the researcher could limit groups only to participants with IQs between 85 and 115 (i. e. , average IQ). This procedure may lower the number of participants in the study and also limit the generalizability of the findings because the sample of participants includes such a limited range of IQ.

Analysis of Covariance Analysis of covariance is a statistical technique used to adjust initial group differences on variables used in causal–comparative and experimental studies. In essence, analysis of covariance adjusts scores on a dependent variable for initial differences on some other variable related to performance on the dependent variable. For example, suppose we planned a study to compare two methods, X and Y , of teaching fifth graders to solve math problems. When we gave the two groups a test of math ability prior to introducing the new teaching methods, we found that the group to be taught by Method Y scored much higher than the group to be taught by Method X. This difference suggests that the Method Y group will be superior to the Method X group at the end of the study just because members of the group began with higher math ability than members of the other group. Analysis of covariance statistically adjusts the scores of the Method Y group to remove the initial advantage so that at the end of the study the results can be fairly compared, as if the two groups started equally.

Data Analysis and Interpretation Analysis of data in causal–comparative studies involves a variety of descriptive and inferential statistics. The descriptive statistics most commonly used in causal–comparative studies are the mean, which indicates the average performance of a group on a measure of some variable, and the standard deviation, which indicates how spread out a set of scores is—that is, whether the scores are relatively close together and clustered around the mean or widely spread out around the mean.

Threats to Internal Validity in Causal. Comparative Research Two weaknesses in causal-comparative research are lack of randomization and inability to manipulate an independent variable. As we have mentioned, random assignment of subjects to groups is not possible in causalcomparative research since the groups are already formed. Manipulation of the independent variable is not possible because the groups have already been exposed to the independent variable.

The major threat to the internal validity of a causal comparative study is the possibility of a subject characteristics threat. Because the researcher has had no say in either the selection or formation of the comparison groups, there is always the likelihood that the groups are not equivalent on one or more important variables other than the identified group membership variable. A group of girls, for example, might be older than a comparison group of boys.

Type of study The likelihood of the threats to internal validity depends on the type of study being considered. In nonintervention studies, the main additional concerns are loss of subjects, location, instrumentation, and sometimes history and maturation. If the persons who are lost to data collection are different from those who remain (as is often probable) and if more are lost from one group than the other(s), internal validity is threatened. If unequal numbers are lost, an effort should be made to determine the probable reasons.

Location: A location threat is possible if the data are collected under different conditions for different groups. Similarly, if different data collectors are used with different groups, an instrumentation threat is introduced. Fortunately, it is usually relatively easy to ensure that variations in location and data collectors do not exist. Data Collector: The possibility of data collector bias can also be threat to internal validity because of individual differences. Instrument decay may occur in observational studies and with repeated administration of the same test to the same group(s). This issue also affect the internal validity of the study.

Strengths of Causal-comparative Research It is less time consuming as well as economical. It gives a chance to the researcher to analyse on basis of his personal opinion and then come out with the best possible conclusion. We can manipulate all variable especially if subjects of population is human being. Many ethical issued are involved. So, casual comparative is the best option.

Weaknesses of causal Comparative The independent variables cannot be manipulated. Subjects cannot be randomly, or otherwise, assigned to treatment groups. 2. Causes are often multiple and complex rather than single and simple.