Education Research Methodology and Statistics

Subject: Sciences
Pages: 3
Words: 642
Reading time:
3 min
Study level: Bachelor

Causal-comparative study

This is the method that reveals the casual relationship existing between variables. It relates the subject in question to already available data provided by the management. The approach of this study involves analyzing the effect of the problem and then determining the cause of the problem or of that effect. Therefore, the approach of causal comparative study begins with the cause of the effect and then investigates the effects of that cause on some variables that are involved in the study. This type of study is commonly used in research institutions for educational purposes (Gay et al, 2008). The availability of management in this design helps in providing sufficient information for the study. However, in some instances in-depth study on independent variables is required so as to develop necessary test differences between groups.

Example is a research study done on the causes of death amongst the newborn babies, the researcher selects the record on actual cases of babies who have died within the first month of life and then record the ‘controls’ who are the babies who survives their first month of life. The researcher then interviews the nurses to compare the history of these two groups in order to determine the prevailing risk factors that might have caused the deaths as opposed to survival (Gay et al, 2008).

The variables used in casual comparative studies cannot be manipulated, hence making this method desirable. This is quite different from other study methods like correlation. The study tries to “highlight the cause of the effect” making implementation easier (Resenthal and Rosnow, 1999, p. 190). Also compared to other study types like quasi experimental study, casual-comparative does not provide “an actual or accurate data to the researcher” (Resenthal and Rosnow, 1999, p.222). Casual comparative study has the weakness that a researcher cannot make predictions but can only compare the distinct characteristics in each group of variables. The relationship between variables cannot be made when using the casual-comparative studies (LaFountain & Bartos, 2002).

Quasi-experimental study

This study examines the results through comparison of subjects that receive program activities and the results of such similar group that do not receive program activities. The results before and after group’s participation are compared. The advantage of this type of experiment is that it has the ability to reveal causes and effects. Its disadvantage is that it cannot establish relationship between the results (Creswell, 2008).Quasi experiment can be very valuable in providing important information such as; detailed information about the population under study, information that identifies the expected changes and results, detailed data on the level of change that occurs over a period of time, it also provides information on the changing outcomes and those that do not change (Bogdan and Biklen, 2007).

Experimental study

This is the method where the variables defining one or more phenomena can be adjusted to suite the definition of other variables. This is a type of study where researchers are involved in some sort of hypothesis and competing methods. An experimental study is done to either existing theories which are to be proved wrong or right or the use of hypothesis. This type of study involves many methods which are used in solving a certain problem. An experimental study involves two features that are control and natural experiments. In a controlled experiment normally shows the effect of a certain treatment on a subject and its effects (Harrison, 2004).

One of the advantages is that it allows for direct manipulation and control of the independent variable. It limits any other explanations and allows direct casual relationship between variables. One of the limitations is that it requires a laboratory for the experiment to be undertaken; this affects the outcome since the results are artificially generated. There is minimal control of variables and this may sometimes make the experiments difficult to undertake (Creswell, 2008).


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