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External Validity refers to the extent to which the cause-and-effect relationship found between the variables in the experiment can be generalized. It reflects whether or not the findings of the study can be generalized beyond an experimental setting, to real-life situations as well.
When research is conducted, it has the objective of identifying correlations and patterns that exist in the real world and therefore aims to obtain knowledge that is generalizable. This is why external validity is important in research studies.
There are three main types of external validity, namely:
Population validity is concerned with whether the findings of your research are generalizable to people in the general population, beyond those that you have sampled in your research.
The population validity of your research is influenced by how well you’ve chosen a sample group for your experiment. It is important to select a sample that can mirror the characteristics of the target population you are trying to study. The better your sample group is in doing so, the more generalizable your results will be to the larger population.
Temporal validity is concerned with whether the findings of your research are generalizable to different periods of time, beyond the season or specific time that you conducted your experimental research. For instance, many studies conducted for the social sciences in the 1900s may have findings that don’t necessarily hold true to the population today due to the evolving social attitudes and behaviour.
Environmental validity is concerned with whether the findings of your research are generalizable to other situations and environments beyond those in which your experiment was conducted.
Controlled test environments are usually designed in a way that allows participants to provide their best performance: the environment is designed to lack any sources of confusion, distraction, or fatigue. However, in real-life settings, people may not always be in such environments and may therefore not respond the same way as they would in a controlled experiment. Therefore, highly controlled environments that are significantly different from the real world will provide research findings with low external validity that may not be generalizable to the larger population.
Let’s take a look at some of the different threats to external validity:
A sampling bias is created when units from the target population haven’t been selected appropriately due to which the sample is not representative of the population. This leads to the sample having low external validity as it is less generalizable to the population.
This effect refers to the inclination of people to work harder and perform better when they are the subjects of an experimental study. This tendency of participants changes their behaviour, making the findings of the study less generalizable to real-life settings.
This refers to the concept that treatments are more effective or less effective for different individuals as a result of their specific abilities. It’s the tenet that optimal learning results are only achieved when the instruction is matched to the aptitude of each learner.
The situation effect refers to to the different situational factors that threaten the external validity of a study. This includes the time of day, location, researcher characteristics, setting, and more: each could limit the generalizability of the research findings.
The following three tips can be used to increase the external validity of an experiment:
Carefully select a sampling technique that will be most appropriate for your study. You must select one that allows you to obtain a sample group that is reflective of the larger population being studied.
Replicating your study multiple times can help enhance the generalizability of your research findings to other time periods, environmental settings, and populations.
Field experiments are experiments that are conducted in natural and “real-word” settings rather than in a laboratory setting. Field experiments often have higher external validity than studies conducted in controlled environments as they are more generalizable due to their real-world experiment setting.
Internal validity can be defined as the extent to which a research study establishes a reliable cause-and-effect relationship between the variables in the experiment.
There are two models that can be used to describe the relationship between internal and external validity:
The relationship between internal and external validity can be described as a trade-off. This means to achieve more of one, there has to be a compromise of the other, and vice versa. This is due to the fact that internal validity is achieved through increased control whereas external validity is achieved through naturalness and representation: contradictory ideas that can’t be achieved simultaneously.
According to this model, internal validity is a purchaser of external validity. In other words, if there is no control in the experiment (internal validity), the results cannot be generalized at all (external validity).
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