Experiments are an excellent data collection strategy. Experiments are designed to test hypotheses under controlled conditions. The simplest form of true experimental design is a classical experimental design. The design is a simple approach that includes five steps that are followed in every experiment from start to finish. These steps are a random assignment of subjects to either control or experimental group, administering pretests, exposing the experimental group to the intervention administering a posttest to both groups, and determining the change between pretests and posttest for both control and experimental groups.
Of all the approaches discussed this week, the classical design is the most sound approach in terms of guaranteeing the integrity of internal validity. This approach institutes rigorous controls to link cause and effect through treatment manipulation to ensure the experiment's internal validity. The design uses random selection and assignment of subjects in the experiment. This results in subjects having equal chances of being part of the control or experimental group. This allows for internal validity by allowing the researchers to look at both sides of the experiment. The data collected from these subjects is then analyzed to measure the outcome, thus maintaining the integrity of the experiment's internal validity.
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The classical experimental design cannot be useful in ensuring internal validity in all circumstances. The approach shows results from the sample size that take part in the experiment. This could interfere with the internal validity since the sample size may not be a true representation of everyone who could have been sampled for the experiment. The approach has a low external validity due to its generalization. Moreover, the approach produces results that apply to one scenario. This means that it would be difficult to replicate the results of the study if it is conducted again. As such, the approach is not useful in ensuring internal validity in all settings.
