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    Home > Experimental Research

EXPERIMENTAL RESEARCH

Experimental research is commonly used in sciences such as sociology and psychology, physics, chemistry, biology, medicine etc.

It is a collection of research designs which use manipulation and controlled testing to understand causal processes. Generally one or more variables are manipulated to determine their effect on a dependent variable.

The experimental method
is a systematic and scientific approach to research in which the researcher manipulates one or more variables and controls and measures any change in other variables.

Experimental Research is often used where:

  1. There is time priority in a causal relationship (cause precedes effect)
  2. There is consistency in a causal relationship (a cause will always lead to the same effect)
  3. The magnitude of the correlation is great.

    4. (Reference: en.wikipedia.org)
The word experimental research has a range of definitions. In the strict sense, experimental research is what we call a true experiment. This is an experiment where the researcher manipulates one variable, and control/randomizes the rest of the variables, it has a control group and the subjects has been randomly assigned to the groups and that you only test one effect at a time. You also know what variable(s) you want to test and measure.

A very wide definition of experimental research, or a quasi experiment, is that it is research where the scientist actively influence something to observe the consequences. Most experiments tend to fall in between the strict and the wide definition. A rule of thumbs is that physical sciences, such as physics, chemistry and geology tend to define experiments more narrowly than social sciences, such as sociology and psychology, are conducting experiments closer to the wide definition.

AIMS OF EXPERIMENTAL RESEARCH

Experiments are done to be able to predict phenomenons. Typically an experiment is constructed to find some kind of causation.

Experimental research is important to society - many experiments have made the world a better place.

IDENTIFYING THE RESEARCH PROBLEM

After deciding to test something with an experiment, the researcher tries to define the research problem to focus the research. The research problem is then operationalizationed, to help measure the research problem. The results will depend on what measurements the researcher choose.

Defining the research problem helps you to formulate a research hypothesis which can be tested against the null hypothesis.

CONSTRUCTING THE EXPERIMENT

There are various aspects to remember when constructing an experiment. Planning ahead ensures that the experiment is carried out properly and that the results reflect the real world in the best possible way.

SAMPLE GROUPS

Choosing and sampling groups is important when we have more than one condition in the experiment. One group is often a control group while others are in the experimental conditions. Experiments frequently have 2 condition, and rarely more than 3 conditions at the same time.

Sampling groups can be done in many different ways. Randomization, quasi-randomization and pairing are the most commonly used sampling methods.

CREATING THE DESIGN

The research design is chosen based on a range of factors. Typical valued factors are time, money, ethics and measurement problems. The design of the experiment is critical for the validity of the results.

TYPICAL DESIGNS IN EXPERIMENTS

  • Pretest
    To check whether the groups are different before the manipulation starts. Warning - this test can sometimes influence the effect.
  • Posttest
    Measurement of the effect(s).
  • Control Group
    Since there is often a measurement effect, a control group, a group not receiving the same manipulation, is added to see how big this effect is.
  • Solomon Four-Group Design
    With two control groups and two experimental group, to test both the effect and the effect of a pretest.
  • Double-Blind Experiment
    Neither the researcher nor the participants knows what is the control group. The results can be affected if the researcher or participants knows this.

PILOT STUDY

It may be wise to first conduct a pilot-study or two before you do the real experiment. This ensures that the experiment measures what it should and that everything is set up right. Minor error, which could have destroyed the experiment, is often found during this process. That way you can get information about errors and problems, which can be improved before putting a big effort into the real experiment. If the experiments involve humans, a common strategy is to first have a pilot study with someone involved in the research, but not too closely, and then arrange a pilot with a person who resembles the subject(s). Those two different pilots are likely to give the researcher very different information about problems of the experiment.

CONDUCTING THE EXPERIMENT

An experiment is typically carried out by manipulating a variable, called the independent variable, for the experimental group. The effect of the researcher is interested in, the dependent variable(s), is measured.

Identifying and controlling non-experimental factors which the researcher does not want to measure the effect from, is crucial to be able to draw a valid conclusion. This is often done by controlling variables if possible or randomizing variables to minimize effects that can be traced back to third variables. Researchers just want to measure the effect of the independent variable(s) when conducting an experiment, to be able to conclude that this was the reason for the effect.

ANALYSIS AND CONCLUSIONS

In quantitative research, the data measured can be enormous. Data not prepared to be analyzed is called "raw data". The raw data is often summarized to something called "output data", which typically consists of one line per subject (or item). A cell of the output data is for example an average of an effect in many trials for a subject. The output data is used for statistical analysis, e.g. significance tests, to see if there really is an effect.

The aim of an analysis is to draw a conclusion, together with other observations. The researcher might generalize the results to a wider phenomenon, if there is no indication of confounding variables "polluting" the results.

If the researcher suspects that the effect stems from another variable than the independent variable, further investigation is needed about the validity of the results. An experiment is often conducted because the scientist want to know the independent variable is causing the effect of the dependent variable. Variables correlating are not proof that there is causation.

Experiments are seldom of qualitative nature, although it happens.

EXAMPLES OF EXPERIMENTS

This website contains many examples of experiments. Some are not true experiments, but involve some kind of manipulation to investigate a phenomenon. Others fulfill most or all criterias of true experiments.

Here are some examples of scientific experiments:

SOCIAL PSYCHOLOGY

GENETICS

PHYSICS


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