Experimental Research explained
Experimental research: This article explains the concept of experimental research in a practical way. The article contains the definition of the term, followed by a brief explanation of what it is, what types of experimental research there are and several practical examples. Enjoy reading!
What is experimental research?
Experimental research is a scientific approach to research that aims to explore causal relationships between variables by manipulating one or more independent variables and measuring its effect on other dependent variables while controlling for other factors.
In simple terms, experimental research is when researchers try to understand how changing one thing affects another. In an experiment, researchers change one thing about a so-called independent variable. It is then observed how something else changes: the dependent variable. They do this while controlling for other factors that may affect the outcome.
This type of research is widely used in social sciences, in fields such as psychology and sociology. These studies are usually about examining the effectiveness of interventions, treatments or programs.
In this article you can read all about the most important aspects of experimental research and you will first find an example below.
Example of experimental research
Consider the following example. A child would like to test how fertilizer affects the growth of a plant in the garden. The child designs an experiment by planting two identical plants. One of them receives fertilizer. This is the independent variable. The other plant receives no fertilizer.
The child then observes how each plant grows for 2 months. This is the dependent variable. Factors such as water supply and the amount of sunlight are fully controlled.
If the plant with fertilizer grows faster than the plant without fertilizer, it can be concluded that the fertilizer has an effect on the growth of the plant.
This is a simple example of experimental research. It is a valid experiment, because changing one thing, the fertilizer, results in observing an effect on another thing, namely the growth of the plant.
Background of experimental research
Experimental research has a long history in conducting scientific research. The method dates back to the 17th century, when Francis Bacon, a British philosopher and scientist, conducted experiments to test hypotheses in the natural world.
The experimental method became popular in the 19th century when the scientific method was developing and positivism emerged. This wave made empirical observation and measurement widely adopted in several areas.
Experimental research and experimental design
The experimental design involves the manipulation of one or more independent variables, which are believed to influence the result, and the measurement of one or more dependent variables, which may or may not change as a result of the independent variable manipulated by the researcher.
In a human study, participants are randomly assigned to different treatment groups. Each group receives the independent variable to varying degrees. The dependent variable is measured in each group.
The design of the experiment may also include control groups, which receive no treatment or placebo at all. This measures the effect of the treatment in relation to a so-called baseline. A static group comparison means comparing two groups of participants based on predetermined characteristics to understand the impact of different variables. Randomized assignments involve randomly assigning participants to different experimental conditions or groups to ensure fairness and reduce bias.
This type of experimental design is also known as group pretest posttest design, as it compares participant groups and measures the degree of change, for example, as the result of treatments or other interventions.
Pre experimental research design involves gathering initial observations and data before conducting a more structured and controlled experiment.
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Variables of experimental research
Experimental research can measure cause and effect relationships between variables. As discussed, variables are the things in research that researchers can change or that can change themselves. The two most important variables are dependent variables and independent variables.
As mentioned in the example, the independent variables are things that researchers themselves can change in an experiment. They are factors that they believe may have an effect on the dependent variables.
The dependent variable is the thing that the researchers measure in an experiment. This variable is expected to be influenced by the independent variable.
The control variables are the variables that researchers keep constant throughout the experiment. In the example, they are sunlight and water supply. These are important because any change in the dependent variable can result from changes in the independent variable.
Extraneous variables are often of no interest to the researcher, but may still have an effect on the dependent variable. In the example of the experiment with the plants and fertilizer, this could be the temperature if it is not controlled. If one plant grows in a warmer environment than another, it can affect the plant’s growth. That makes it more difficult to determine whether it is because of the fertilizer that one plant grows faster than another.
Confounding variables are related to both the independent and dependent variables and can influence the outcome of an experiment. An example of this is the type of soil in which the plants are planted. One type of soil may be better than another and thus can affect the growth of the plants.
Thus, controlling variables is extremely important to ensure that the results of the study are valid. Creating a solid research design should therefore be a priority.
Sampling
Another important element of true experimental research is sampling. Sampling refers to the process of selecting some subsets, or individuals, in a study from a larger population of the study.
The purpose of sampling is to get a selection that is representative of the larger population. What is meant by this is that these selections represent the characteristics of the greater whole. This is important because the results of the study can then be generalized to the population as a whole.
There are several methods of sampling in experimental research.
One of them is random sampling. Stratified sampling and convenience sampling are also used. Each technique has its own strengths and weaknesses that need to be considered. The choice of method depends on the specific research question and the resources available.
Applying an example of sampling
Consider the following example. Suppose a researcher in the pharmaceutical industry wants to investigate whether a new drug is effective in the treatment of condition X. The researcher can then recruit participants by placing an advertisement in the newspaper, but this may result in a biased sample. Only people who read a newspaper will then respond. This can lead to the population being too one-sided.
To get a more representative sample, the researcher may consider recruiting participants from a list of patients who have a condition relevant to the study. By using this method, the list of participants is likely to be more representative of the large population of patients with the condition.
In short, sampling is an important aspect of experimental research that ensures the validity and generalizability of the findings. Only if a representative sample can be taken from the population can researchers draw accurate conclusions based on the results of the study.
Data analysis in experimental research
The last element of experimental research that you need to know is data analysis. This form of experimental research refers to the process of exploring and interpreting the data collected during research.
The purpose of data analysis is to determine whether the results of the experimental research study confirm the hypothesis or not. There are different kinds of data analysis in experimental research. The most important are explained below.
1. Descriptive analysis
The descriptive analysis means that the characteristics of the data collected during the study are described and summarized. It provides the researcher with a detailed view of the data and helps to identify patterns and trends in the data.
2. Inferential analysis
This form of analysis involves using statistics to test the hypothesis and draw conclusions about the population based on the sample data collected during the study. It also helps to determine whether the differences between groups are statistically relevant, or whether they are the result of other factors.
3. Multivariate analysis
The multivariate analysis involves assessing the relationship between multiple variables in the study. It helps to establish complex relationships between variables and provides a more comprehensive understanding of the data.
Example of data analysis in experimental research
Consider the following example. A researcher is conducting experimental research to test whether a new mathematics teaching method is effective. The researcher collects data on students’ test scores before and after the implementation of the new approach.
To analyze the data, the researcher uses the inferential statistics method. He compares the mean scores of the tests of the experimental group with the control group. For example, the researcher can use a so-called t-test to determine whether the observed difference in the scores is statistically significant, whether it is due to chance or something else.
Also, the researcher can use a multivariate analysis to examine the relationship between variables such as a student’s prior knowledge and the effectiveness of the new approach. This analysis helps the researcher identify factors that may influence the effectiveness of the new method.
Neuralink
One of the most high-profile experimental studies being conducted today are the experiments of Neuralink, a company founded by Tesla boss Elon Musk.
Neuralink is developing a computer that can be connected to the human brain. This connection allows people to control the computer. The technology includes so-called neural threads, which are implanted directly in the brain.
The research has so far resulted in a monkey that can play the game of Pong with an implanted chip by controlling the computer with its thoughts.
The studies have received a lot of criticism, especially from an ethical point of view. One of the objections is that implanting a chip is an invasive treatment that hurts. A monkey does not give consent and is not aware of the dangers that the treatment entails. That is the reason for many critics to disapprove of the experiment.
Proponents argue that the use of animals in research is crucial to developing scientific knowledge that can be used to develop new treatments and technologies.
Case study
The term ‘case study’ is closely related to the subject of experimental research, particularly when considering the design and approach of the study.
case study research design refers to the specific framework and methodology employed to conduct a case study. It involves a detailed investigation of a particular individual, group, or situation to gain comprehensive insights into the underlying factors and dynamics.
Shot case study research builds upon the concept of a case study but emphasizes a concise and focused examination of a specific case or instance. It aims to provide a concentrated analysis of the subject, often with limited time or resources, while still seeking to capture essential details and extract valuable knowledge.
Both terms include the application of in-depth qualitative or quantitative analysis within the context of experimental research. They allow researchers to explore unique cases or phenomena, investigate causal relationships, and generate rich and comprehensive data for further interpretation and understanding.
It’s Your Turn
What do you think? Do you recognize the explanation about experimental research? Have you conducted experimental research for a thesis or other research? Do you find statistics difficult? Do you think control group testing is important in experimental research? Do you have ethical concerns about some of the experiments that are being conducted nowadays?
Share your experience and knowledge in the comments box below.
More information
- Barick, R. (2021). Research Methods For Business Students. Retrieved 02/16/2024 from Udemy.
- Campbell, D. T., & Stanley, J. C. (2015). Experimental and quasi-experimental designs for research. Ravenio books.
- Christensen, L. B., Johnson, B., Turner, L. A., & Christensen, L. B. (2011). Research methods, design, and analysis. Pearson.
- Ledyard, J. O. (1995). Public Goods: A Survey of Experimental Research. In: The Handbook of Experimental Economics. Princeton University Press , Princeton, pp. 111-194. ISBN 9780691042909.
- Verhoeven, N. (2007). Doing research. The Hows and Whys of Applied Research.
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Original publication date: 06/01/2023 | Last update: 01/02/2024
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Ben Janse
Ben Janse is a young professional working at ToolsHero as Content Manager. He is also an International Business student at Rotterdam Business School where he focusses on analyzing and developing management models. Thanks to his theoretical and practical knowledge, he knows how to distinguish main- and side issues and to make the essence of each article clearly visible.
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