Which design seeks to control experimental variables in high structure?

The design that seeks to control experimental variables in high structure is known as Experimental Group Design. This method involves the manipulation of independent variables and the random assignment of participants to different conditions. By establishing control over extraneous variables and typically utilizing strict protocols, researchers can more accurately determine the cause-and-effect relationships between the treatment (or intervention) and the outcomes measured.

Experimental Group Design often includes control groups, which serve as benchmarks against which the treatment effects can be compared. This level of structure helps minimize biases and confounding factors, thereby enhancing the reliability and validity of the findings. It is frequently employed in randomized controlled trials, allowing researchers to draw more robust conclusions about the effectiveness of a specific intervention.

Other design types, such as Random Group Design or Matched Pairs Design, also control for variables but may not achieve the same level of strictness in structure as Experimental Group Design. Baseline Treatment Design focuses more on observing outcomes over time rather than directly comparing different experimental groups, which may lead to less control over variables compared to the structured approach of Experimental Group Design.