In traditional experimental research, variables are carefully controlled by researchers in a lab setting. In non-experimental study, there are no variables the observer can directly control.
Non-experimental research gets its name from the fact that there is no independent variable involved in testing. Researchers instead look to take past events and re-examine them; analyzing them for new information and coming to new or supporting conclusions.
In traditional experimental research, variables are carefully controlled by researchers in a lab setting. In non-experimental study, there are no variables the observer can directly control. Instead, researchers are tasked with parsing through established context to come up with their own interpretation of the events.
While non-experimental research is limited in use, there are a few key areas where a researcher may find using this kind of methodology is beneficial.
These key characteristics of non-experimental research set it apart from other common methods:
There are three primary forms of non-experimental research. They are:
Single-variable research involves locating one variable and attempting to discern new meaning from these events. Instead of trying to discern a relationship between two variables, this type of study aims to ganer a deeper understanding of a particular issue - often so that further testing can be completed.
One example of a single-variable research project could involve looking at how high the average person can jump. In this case, researchers would invite participants to make 3 attempts to jump up into the air as high as they could from a standing position; researchers would then average out the 3 attempts into one number. In this case, researchers are not looking to connect the variable jump height with any other piece of information. All the study is concerned about is measuring the average of an individual’s jumps.
Correlational research involves measuring two or more variables of interest while maintaining little or no control over the variables themselves. In the quasi-experimental method, researchers change an independent variable - but will not recruit or control the participants involved in the experiment. An example would be a researcher who starts a campaign urging people to stop smoking in one city - and then comparing those results to cities without a no-smoking program.
The qualitative research method seeks to answer complex questions, and involves written documentation of experiences and events. Unlike the quantitative research method, which is concerned with facts and hard data, the qualitative method can be used to gather insights for a breadth of vital topics.
Non-experimental designs can open a number of advantageous research opportunities. The benefits include:
The limitations of non-experimental research are:
These disadvantages can be mitigated by applying the non-experimental method to the correct situations.
Experimental research often involves taking two or more variables (independent and dependent) and attempting to develop a causal relationship between them. Experimental designs will be tightly controlled by researchers, and the tests themselves will often be far more intricate and expansive than non-experimental ones.
Non-experimental research is best suited for situations where you want to observe events that have already happened; or you are only interested in gathering information about one isolated variable.
Experimental designs are far more common in the fields of science: medicine, biology, psychology, and so forth. Non-experimental design often sees use in business, politics, history, and general academia.
Determining when you should use either experimental or non-experimental methods boil down to the purpose of your research.
If the situation calls for direct intervention, then experimental methods offer researchers more tools for changing and measuring independent variables.
The best place to use non-experimental research design is when the question at hand can be answered without altering the independent variable.
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