Generalizability: Example

An example of generalizability in everyday life involves driving. Operating an automobile in traffic requires that drivers make assumptions about the likely outcome of certain actions. When approaching an intersection where one driver is preparing to turn left, the driver going straight through the intersection assumes that the left-turning driver will yield the right of way before turning. The driver passing through the intersection applies this assumption cautiously, recognizing the possibility that the other driver might turn prematurely.

American drivers also generalize that everyone will drive on the right hand side of the road. Yet if we try to generalize this assumption to other settings, such as England, we will be making a potentially disastrous mistake. Thus, it is obvious that generalizing is necessary for forming coherent interpretations in many different situations, but we do not expect our generalizations to operate the same way in every circumstance. With enough evidence we can make predictions about human behavior, yet we must simultaneously recognize that our assumptions are based on statistical probability.

Consider this example of generalizable research in the field of English studies. A study on undergraduate instructor evaluations of composition instructors might reveal that there is a strong correlation between the grade students are expecting to earn in a course and whether they give their instructor high marks. The study might discover that 95% of students who expect to receive a "C" or lower in their class give their instructor a rating of "average" or below. Therefore, there would be a high probability that future students expecting a "C" or lower would not give their instructor high marks. However, the results would not necessarily be conclusive. Some students might defy the trend. In addition, a number of different variables could also influence students' evaluations of an instructor, including instructor experience, class size, and relative interest in a particular subject. These variables -- and others -- would have to be addressed in order for the study to yield potentially valid results. However, even if virtually all variables were isolated, results of the study would not be 100% conclusive. At best, researchers can make educated predictions of future events or behaviors, not guarantee the prediction in every case. Thus, before generalizing, findings must be tested through rigorous experimentation, which enables researchers to confirm or reject the premises governing their data set.

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Generalizability & Transferability

Generalizability: Example