External validity is the likelihood that results obtained from a sample group apply to the entire population in various situations and time frames. Researchers strive for high external validity to predict future outcomes accurately. However, achieving external validity can be challenging, and researchers should note “threats to external validity” to improve future studies.
External validity is one of many types of validity that researchers seek to achieve in order to maximize the accuracy and minimize the shortcomings of their study or experiment. External validity is a term that scientific researchers use to describe how likely it is that results obtained from a sample group apply to the entire population in various situations and time frames. Scientists strive to obtain high external validity for each experiment, because if the results of the experiment do not apply to the population outside the sample group, then the experiment has not found any useful results that can be used to predict the future results.
An example of a situation where external validity needs to be evaluated might be a study conducted by an undergraduate psychology class that evaluates the connection between the hours college students spend working at a job and those students’ grades. It may seem like a good idea to use all the data from students in the psychology class, or even all students involved in the psychology department, to get a quick and easy sample to test. This, however, would hurt the study’s external validity, because it assumes several things that may not be true for the general population. For example, do psychology students have the same study and work habits as students in other majors? Also, do students at that particular school have the same study habits as students at schools around the country or the world?
Unfortunately, because a large number of experiments take place in a laboratory setting rather than in the subjects’ daily lives, external validity can be quite difficult to achieve. Usually, the researchers conducting the study or experiment would summarize what they deem to be “threats to external validity” in their written experiment report, in an attempt to explain what might have gone wrong and what can be improved in the future to achieve a higher level of prediction accuracy. For example, if study subjects are told to perform a task under the supervision of the researchers, they may behave and act very differently than they would if they were at home with family and other influences around them. If the study doesn’t account for them, the external validity is flawed and the results probably won’t predict future outcomes very accurately because they were found under special circumstances. Researchers should take note of this and try to improve future studies to minimize the difference.
Protect your devices with Threat Protection by NordVPN
