<![CDATA[Quasi-experimental research is a research method used to measure the effect of a particular treatment on a variable without using full subject randomization. This method is often used in situations where full control of external variables is difficult, such as in educational, social, or health settings. Quasi-experimental research designs involve a treatment group and a control group, but the subjects in both groups are not selected randomly. There are several types of designs in quasi-experiments, such as nonequivalent control group design, time series design, and pretest-posttest design. The main advantage of quasi-experiments is their flexibility in real-world situations, allowing researchers to test causal relationships in a more natural environment. However, this method has the disadvantage of potential threats to internal validity, such as selection bias and the influence of external variables. Therefore, data analysis in quasi-experiments requires special attention to control these factors, such as the use of analysis of covariance (ANCOVA) or other statistical methods. Quasi-experimental research is very relevant in developing policies or interventions that can be practically implemented in society. With a good design, this method is able to produce valid and useful findings for evidence-based decision making.]]>
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