Summary
Highlights
Experimental research design is an effective method for testing cause and effect relationships. It is commonly used in various fields, such as in the time of a pandemic to test a vaccine's efficacy. Results from this type of research can be statistically analyzed once a hypothesis is made, making hypothesis testing a starting point for experimental research, unlike descriptive research.
Experimental research design tests cause and effect relationships between variables and conditions that are controlled by researchers. The process typically involves a pre-test, followed by the intervention material's implementation, and then a post-test or assessment to measure the effects of the intervention.
Key concepts in experimental design include the manipulation or control of variables to achieve desired conditions. Researchers control variables, analyze results from control and experimental groups, and manipulate independent variables to determine effects on dependent variables. Subjects are randomly assigned to experimental treatments, and the research relies heavily on hypothesis testing.
Advantages include the statistical analyzability of results, ease of replication for validating findings, its ability to provide clear 'yes' or 'no' answers, the easy manipulation of single variables, and the accuracy of the results obtained.
Disadvantages involve conditions being too controlled and not representative of real-world scenarios, the difficulty in obtaining a complete rejection or acceptance of a hypothesis due to stringent proof standards, the expense and complexity of setting up such research, and potential impracticality.
Examples include studying the effect of teaching strategies (competitive group vs. traditional lecture) on student achievement, comparing personalized instruction to traditional instruction on computation skills, and investigating the effect of new treatment plans on breast cancer.
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