A researcher administered a math test to a group of 9th graders in September. During the school year these students received an intensive program designed to improve their math skills. In May the math test was again given to these students and their math scores improved. A major problem in this research is that the researcher failed to control for:
A. Selection biases
B. Testing
C. History
D. The researcher failed to control for all of these choices
E. Maturation

C. History

Explanation:

Internal validity refers specifically to whether an experimental treatment/condition makes a difference or not, and whether there is sufficient evidence to support the claim.

Factors which jeopardise internal validity

History: The specific events which occur between the first and second measurement. Maturation: The processes within subjects which act as a function of the passage of time. i.e. if the project lasts a few years, most participants may improve their performance regardless of treatment. Testing: The effects of taking a test on the outcomes of taking a second test. Instrumentation: The changes in the instrument, observers, or scorers which may produce changes in outcomes. Statistical regression: It is also known as regression to the mean. This threat is caused by the selection of subjects on the basis of extreme scores or characteristics. Give me forty worst students and I guarantee that they will show immediate improvement right after my treatment. Selection of subjects: The biases which may result in selection of comparison groups. Randomization (Random assignment) of group membership is a counter-attack against this threat. However, when the sample size is small, randomization may lead to Simpson Paradox, which has been discussed in an earlier lesson. Experimental mortality: The loss of subjects. For example, in a Web-based instruction project entitled Eruditio, it started with 161 subjects and only 95 of them completed the entire module. Those who stayed in the project all the way to end may be more motivated to learn and thus achieved higher performance. Selection-maturation interaction: The selection of comparison groups and maturation interacting which may lead to confounding outcomes, and erroneous interpretation that the treatment caused the effect. John Henry effect: John Henry was a worker who outperformed a machine under an experimental setting because he was aware that his performance was compared with that of a machine.

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