Experimental research is the type of research design most familiar to individuals in the physical sciences and a host of other fields. This is mainly because experimental research is a classical scientific experiment, similar to those performed in the institute’s science classes.
Imagine taking two samples of the same plant and exposing one of them to sunlight, while the other stays away from sunlight. Let the plant exposed to sunlight be called sample A, while the second is called sample B.
If at the end of the research we verify that sample A grows and sample B dies, although both are wet regularly and receive the same treatment. Therefore, we can conclude that sunlight helps the growth of all similar plants.
What is experimental research?
Experimental research is a scientific approach to research, in which one or more independent variables are manipulated and applied to one or more dependent variables to measure their effect on the latter. The effect of independent variables on dependent variables is usually observed and recorded over a period of time, to help researchers draw a reasonable conclusion about the relationship between these two types of variables.
According to Fleischer et al (2002), the experimental research method is widely used in the physical and social sciences, psychology, and education. It is based on the comparison between two or more groups with simple logic, which however can be difficult to execute.
Experimental research designs, mostly related to a laboratory test procedure, involve collecting quantitative data and performing statistical analyses on them during research. Therefore, it is an example of a quantitative research method.
What are the characteristics of experimental research?
Experimental research contains dependent, independent, and strange variables. Dependent variables are the variables that are treated or manipulated and are sometimes called the object of the investigation.
On the other hand, the independent variables are the experimental treatment that is exerted on the dependent variables. Strange variables, on the other hand, are other factors that affect the experiment and that can also contribute to change.
The stage is the place where the experiment is performed. Many experiments are carried out in the laboratory, where you can exert control over the foreign variables, eliminating them.
Other experiments are carried out in a less controllable environment. The choice of environment used in the research depends on the nature of the experiment being conducted.
Experimental research can include multiple independent variables, e.g. time, skills, test results, etc.
What are the types of experimental research design?
The types of experimental research design are determined by the way the researcher assigns subjects to different conditions and groups. According to Demetrescu (2000), they are of 3 types, namely: pre-experimental, quasi-experimental and true experimental research.
Pre-experimental research design
In the pre-experimental research design, one or more dependent groups are observed to test the effect of applying an independent variable that is supposed to cause the change. It is the simplest form of experimental research design and is treated without a control group.
Although very practical, experimental research lacks several areas of true-experimental criteria. The design of pre-experimental research is divided into three types:
Unique case study research design
In this type of experimental study, only one dependent group or variable is considered. The study is carried out after some treatment that is supposed to cause a change, so it is a post-test study.
Pretest-postest research design of a group
This research design combines both the post-test and the pretest study by performing a test in a single group before administering the treatment and after administering it. The first is given at the beginning of treatment and the second at the end.
Static comparison of groups
In a study comparing static groups, 2 or more groups are observed, in which only one of them undergoes any treatment while the other groups remain static. All groups undergo further testing and it is assumed that the differences observed between the groups are the result of treatment.
Quasi-experimental research design
The word “quasi” means partial, medium, or pseudo. Therefore, quasi-experimental research bears a resemblance to true experimental research, but it is not the same. In quasi-experiments, participants are not randomly assigned, and are therefore used in settings where randomization is difficult or impossible.
This is very common in educational research, where administrators are unwilling to allow random selection of students for experimental samples.
Some examples of quasi-experimental research design are: the time series, the non-equivalent control group design, and the counterbalanced design.
True experimental research design
True experimental research design relies on statistical analysis to approve or disprove a hypothesis. It is the most accurate type of experimental design and can be carried out with or without a pre-test on at least 2 randomly assigned dependent subjects.
The true experimental research design must contain a control group, a variable that can be manipulated by the researcher, and the distribution must be random. The classification of true experimental design includes:
Control group design only after testing
In this design, subjects are randomly selected and assigned to the 2 groups (control and experimental), and only the experimental group is treated. After close observation, both groups are subsequently tested and a conclusion is drawn from the difference between these groups.
The pretest-postest control group design
In this control group design, subjects are randomly assigned to the two groups, both are presented, but only the experimental group is treated. After close observation, both groups are subjected to a subsequent test to measure the degree of change in each group.
Solomonic design of four groups
In this type of design, four random groups are formed, including two experimental groups and two control groups. Only two groups undergo a pre-test. Next, a pre-tested group and a non-pre-tested group receive the treatment. All four groups receive the subsequent test. And, in the end, the results of the subsequent test demonstrate the effects of the dependent variable compared to the effects of the independent variable on the dependent variable. This method is a combination of the above two and possible sources of error are eliminated by using this design.
Two or more independent variables (factors) are manipulated simultaneously to observe their effects on the dependent variable. This design allows the researcher to test two or more hypotheses in a single project.
Random block design
When there are intrinsic differences between subjects and possible differences in experimental conditions, this design is used. When there are a large number of experimental groups, the design of random blocks makes the groups homogeneous.
Cross-design (also known as repeated measure design)
In this design, different treatment orders are randomly manipulated to the subjects, and they are assigned more than one treatment. According to Moret (2002), the compared groups must have an equal distribution of characteristics and there must be a high level of similarity between the subjects. In this type of design, subjects serve as their own control groups. Cross-designs are very good tools for doing research, but, there is something that should be of concern and that is the point that the subjects’ experience with the first treatment can affect their response to the second treatment or condition.
Examples of experimental research
Examples of experimental research are different, depending on the type of experimental research design being considered. The most basic example of experimental research is laboratory experiments, the nature of which may vary depending on the research topic.
Administration of exams at the end of the semester
During the semester, students in a class are taught on certain courses and administered an exam at the end of the semester. In this case, the students are the dependent subjects or variables, while the classes are the independent variables treated on the subjects.
In this research only a group of carefully selected subjects is considered, which makes it an example of pre-experimental research design. We will also note that the tests are only done at the end of the semester, and not at the beginning.
Which makes it easier for us to conclude that this is unique case study research.
Assessment of employee skills
Before hiring an employee, organizations conduct tests that serve to discard the least qualified candidates from the pool of qualified applicants. In this way, organizations can determine an employee’s skill set at the time of hiring.
In the course of employment, organizations also carry out employee training to improve their productivity and, in general, grow the organization. At the end of each training, a subsequent evaluation is carried out to check the impact of the training on employees’ skills and see if they can be improved.
Here, the subject is the employee, while the treatment is the training provided. This is an example of experimental pretest-postest control group research.
Evaluation of the teaching method
Let’s consider an academic institution that wants to evaluate the teaching method of 2 professors to determine which is the best. Imagine a case in which the students assigned to each teacher are carefully selected, probably due to the personal request of the parents or stubbornness and intelligence.
This is an example of non-equivalent group design because the samples are not the same. By evaluating the effectiveness of each teacher’s teaching method in this way, we can conclude after conducting a subsequent test.
However, this can be influenced by factors such as a student’s natural sweetness. For example, a very intelligent student will grasp more easily than his peers, regardless of the teaching method.
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You may also be interested in: Case Studies
Moret (2002). Towards a discipline of experimental algorithmics. In M. H. Goldwasser, D. S. Johnson, C.C. McGeoch (Eds.), Data Structures, Near Neighbor Searches, and Methodology: Fifth and Sixth DIMACS Implementation Challenges,vol. 59 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science,pp. 197-213, American Mathematical Society, Providence, RI, USA.
Fleischer, B. Moret, E.M. Schmidt (Eds.) (2002). Experimental Algorithmics: From Algorithm Design to Robust and Efficient Software,vol. 2547 of Lecture Notes in Computer Science. Springer Verlag, Berlin, Germany, Berlin, Germany.
Demetrescu, G. F. (2000). What do we learn from experimental algorithmics?. In M. Nielsen, B. Rovan (Eds.), MFCS,vol. 1893 of Lecture Notes in Computer Science,pp. 36-51, Springer Verlag, Berlin, Germany, Berlin.