Generalization & External Validity

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  • 0:06 External Validity
  • 1:57 Across Subjects
  • 3:19 Procedures & Concepts
  • 4:31 Beyond the Lab
  • 5:35 Lesson Summary
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Lesson Transcript
Instructor: Natalie Boyd

Natalie is a teacher and holds an MA in English Education and is in progress on her PhD in psychology.

The point of research is to be able to generalize findings to the world at large. In this lesson, we'll look at three types of generalizing that make up external validity: across subjects, from procedures to constructs, and beyond the lab.

External Validity

Phil is a psychologist, and he wants to know if rewarding students leads to more engagement in class. He decides to run an experiment where he gathers students together in his lab and asks them general knowledge questions, like, 'What color is the sky?' or 'What country was Shakespeare from?' Each time a student answers a question correctly, Phil gives the student a piece of candy. He then counts how often they raise their hand to answer another question. If rewards do increase engagement, he expects students who have been rewarded to participate more afterwards.

Phil, like many researchers, is doing research in a lab, not in the real world. This might be for many reasons: perhaps Phil doesn't have access to actual classrooms in which to try his theory out, or perhaps there are other variables that might come into play when in a real classroom, like how well the students understand the material. By doing research in a lab, Phil has a controlled setting where he is able to focus on only the variables that he's interested in (rewards and engagement). But, can he say that his study applies to the real world? Maybe, but maybe not.

External validity in research is the extent to which the results of a study can be generalized to the world at large. Generalization is a major part of research. The point of doing a study is to say something about the world at large. For example, Phil wants to know if rewarding students leads to more engagement in class. He's doing the experiment in a lab setting, but he wants to be able to generalize it to classes in schools, not simply what goes on in his lab. Let's look at some ways that researchers want to generalize and some issues that can arise with each.

Across Subjects

For Phil's experiment, he asked for volunteers to participate. Since he works at a college, the volunteers were all college students. They were all between the ages of 18 and 24. So, what do Phil's results tell us about rewards and class engagement? Phil would like to generalize across subjects, or be able to say that his results are true about more than just the subjects that he worked with.

For example, let's say that Phil finds that rewards do encourage students to be more engaged. He knows this is true of college students between the ages of 18 and 24 because that's the people he did the experiment on. But, Phil wants to be able to say that this is also true of other groups. Maybe he wants to tell middle and high school teachers that they should reward their students to increase engagement. In that case, he wants to make generalizations across subjects.

But, there's a problem. Phil's subjects might be very different from the people he wants to generalize to. For example, all of Phil's participants are in college, which means they did well enough in high school to get into college. But, would the rewards also work on students who are struggling in high school? Maybe, but maybe not. Phil wouldn't know for sure unless he did research on that group of subjects.

Procedures & Concepts

Remember that Phil wants to show that rewards impact engagement. But, how do you measure engagement? You can't see or hear or smell engagement. That's because engagement, like most aspects of psychology, is a construct, or an abstract idea that cannot be directly observed.

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