Experimental Research Design: Its 3 Types, 10 Steps, and Importance

Experimental Research Definition

Scientific realism provides the foundation for experimental research, which aims to determine casual relationships. In order to ascertain the causes and effects of the phenomenon being studied, experimental research contrasts data obtained through experimentation with constant factors.

In experimental research, two different sorts of groups are created: an experimental or treatment group and a control group. Researcher creates group of volunteers, who then assesses the impact of each treatment on each group.

Variables under control:

One or more independent variables are under the control or manipulation of the researcher, who then analyzes the impact on the dependent variable. The participant treatment variable is referred to as an independent variable. Participants are typically divided into various groups that undergo various therapies. The dependent variable is often assessed with a test or other measurement tool that yields numerical data.

Types of experimental Design 

There are three types experimental design on the basis of methods of data collection.

1. Pre-experimental research design

This design is conducted in a situation where a group of many groups is under observation after the implementation of the factors of cause-and-effect relationship in the research. This design helps the researcher understand whether further investigation is essential or not. There are three types of pre-experimental research.

i. One-shot case study research

In this design, only one group is studied at a time after the treatment is supposed to cause a change. This one group is compared with the overall opportunities of what the case would have been if there was no treatment and to other events casually observed. So there is no comparison group in this situation.

ii. One-group pretest-posttest design

In this design, a single instance is observed at two different time points: the first preceding the treatment and the second after the treatment, and the treatment changes the results of the study. In this situation, no comparison groups are employed.

iii. Static-group comparison design

In this design, the treatment group is compared with another group that has not gone through a treatment. The results in this situation are supposed to be because of the treatment.

2. True Experimental Design

In a true experimental design, the hypothesis is tested through reliance on statistical analysis. The true experimental design specifically establishes the cause-and-effect relationship within the group. However, three factors are to be satisfied in this type of research.

1. There are no changes in the control group, while experimental group variables will be subjected to changes.
2. The researcher can manipulate the variable.

• The variables will be randomly distributed.

The true experimental design is found in the field of physical sciences.

3. Quasi-experimental Design

The quasi-experimental design is the same as experimental research, with the only difference being the assignment of the control group. There is manipulation of independent variables such that there is no random assignment of the group’s participants.

Steps in conducting experimental research 

Step 1: Select a Topic

Choosing the topic is the first step. The topic’s nature should allow for the assessment of whether a given course of treatment results in a sizable modification of behavior.

Step 2: Reviewing the literature and defining a research question

The researcher looks into earlier works and checks the investigation method for the same topic. The researcher looks for the factors studied and discussed, as well as the suggestions from the results of the previous studies.

After review, the researcher develops a research topic and makes a plan of methodology to conduct his or her research on the basis of a well-defined research question.

Step 3: Develop a Research Hypothesis:

Here, the researcher then formulates and presents a hypothesis that outlines the anticipated causal relationship between the variables in light of the results of the literature review. The three sorts of hypotheses are described in the following paragraphs.

• Directional Hypothesis:

The direction or anticipated result is stated in a directional hypothesis. To put it another way, the researcher is secure enough to predict which group would perform better than the other group. For example, a hypothesis can be developed that a group that receives the treatment will perform better than the control group.

• Non-directional Hypothesis:

The non-directional hypothesis is defined as the difference in variables anticipated without any direction. Let’s imagine that after reading the research on computer-assisted instruction and arithmetic achievement, you conclude that there is insufficient evidence to conclude that the computer group will perform better than the group receiving traditional classroom instruction.

Null Hypothesis:

A null hypothesis claims that there is no difference or relationship between the variables. The null hypothesis is implicit in all the experiments.

Step 4: Select and Assign Participants to Groups:

The experimental and control groups are typically the minimum number of groups in experimental investigations. In an experimental study, the researcher chooses and assigns volunteers.

Step 5: Select measurement instruments:

The same care and consideration is put into choosing the instruments or measurement equipment for an experimental study as it is for other sorts of research. First and foremost, you need to make sure that the instrument you choose is a suitable measurement for your dependent variable.

Step 6:  Select Controls for Extraneous Variables

Extraneous variables are variables that are other than independent variables and affect our dependent variables. These variables are not part of our study but affect it. So, to generalize the ability and validity of results, it is necessary to control the extraneous variable.

Step 7: Define and Administer the Experimental Treatments

The study plan, sometimes referred to as the treatments to be given to the participants, is a crucial component in developing a research proposal. Every procedure that will be employed in the study should be covered in this plan. What transpires for each group’s members? How is the experimental group’s treatment different from that of the control group?

An experimental research study’s protocols are thoroughly laid out before it starts, and while the experiment is underway, there is often little to no variation from the plan. The distinction between the experimental and control groups is crucial to the strategy. Remember that specific explanations of how both groups are handled must be offered.

It is insufficient, for instance, to merely state that the control group receives the “traditional approach.”

Even if the researcher explicitly specifies the treatment, it might not really be administered in accordance with that definition. Let’s say, for illustration, that a school psychologist creates a behavioral program for use. He or she then gathers the data before implementing the behavior plan.

The instructor might not carry out the behavior plan as intended, which would prevent the school psychologist from ever truly testing the treatment. This would go against the principle of treatment integrity.

The school psychologist may give the teacher a script outlining exactly how the behavior plan should be carried out in order to allay this worry. This would cover things like the acceptable words or expressions she employs in various contexts and the actions to which the plan ought to be applied.

The purpose of an experimental study is to “prove” that the experimental treatment has had an impact; hence, defining the treatment is crucial. As a result, it is important to understand the experimental treatment and its comparisons.

Step 8: Collect and Analyze Data

The researcher organizes and gathers the data using the design of the study. Because experimental investigations generate quantitative data, the researcher who conducts the study analyzes the data using statistical techniques. Depending on the kind of data you gather, you can use different statistical analyses.

The process of gathering data involves the use of nominal, ordinal, interval, and ratio levels of measurement. The researcher often computes descriptive statistics on the data in quantitative research investigations initially. The researcher next chooses an inferential statistical test that is suitable for the degree of measurement employed in the study after completing this step.

Step 9: Decide About Hypothesis

The gathered data either confirms or refutes the study hypothesis. Keep in mind that the researcher generally wishes to disprove the null hypothesis, which claims that there is no discernible difference between the treatment groups and that any difference discovered was the result of chance rather than the experimental therapy.

Step 10: Form Conclusion

The selection of hypotheses in this research design is based on an analysis of the data. This data serves as foundation for the results of the study.

Why is experimental research important?

The experimental research has gained importance due to the following points:

Cause and Effect

Experimental research is important for finding out the cause-and-effect relationship, which is not the case with other types of research designs.

Reliable outcomes

The experimental research design is important because it produces highly reliable results. This is because the experiments are conducted in highly controlled environments, which implies quantitative measures. This feature enables the researchers to generalize the results to the population in which the experiment is conducted.

Provision of helpful insight

The experimental research is helpful in providing insights to solve immediate problems. For example, after a series of experiments, a suitable teaching method is recommended for the teaching of a particular subject.

Control over variables

Since the researcher has control over the variables, he or she is able to determine the influence of possible variables. Furthermore, the researcher can effectively measure the interrelationship of the variables.

Avoiding mistakes during designing research

1. The researcher must make sure that the hypothesis is logical and can be tested. Otherwise, there will be a need to rework the research work.
2. It is important to review the relevant literature and find out the ways in which the research gap will be filled. It is also important to state how your research will contribute to the research field.
3. It is important to avoid incorrect statistical analysis. It is because the research aims to gain valid and sustainable proof.
4. It is important to have a clear research question for addressing core problems.
5. The researcher must include in the report the perceived limitations of the study. It is because every study has some limitations.
6. To minimize the risk for the researcher’s participants, he or she must manage the ethical norms along with his or her research study objectives.