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An example of a posttest only nonequivalent groups design is evaluating a new fraction-teaching strategy by implementing it in one third-grade classroom (the treatment group) and comparing the final math scores to another classroom taught with traditional methods (the control group). Because the researcher did not randomly assign students to these classes, preexisting factors—such as varying student motivation levels, differing classroom environments, or distinct teacher disciplinary styles—serve as confounding variables that could independently explain any outcome differences.

Example of a Posttest Only Nonequivalent Groups Design

To enhance the internal validity of a posttest only nonequivalent groups design, researchers can intentionally select comparison groups that share key characteristics. For instance, when evaluating a teaching method across two classrooms, a researcher might select classes within the same school that have similar baseline test scores and teachers with comparable styles to eliminate major confounds. However, because true random assignment is absent, unmeasured confounding variables may still influence the outcomes, meaning researchers cannot make definitive causal claims.

Controlling Confounds in a Posttest Only Nonequivalent Groups Design

A researcher wants to test a new fraction-teaching strategy. She implements it in one third-grade classroom and compares those students' final math scores to another classroom that used traditional methods. Students were not randomly assigned to these classrooms. What is the primary reason this design cannot establish that the teaching strategy caused any observed difference in scores?

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