External validity - the results can be generalized beyond the immediate study. In order to have external validity, the claim that spaced study studying in several sessions ahead of time is better than cramming for exams should apply to more than one subject e. It should also apply to people beyond the sample in the study. Different methods vary with regard to these two aspects of validity. Experiments, because they tend to be structured and controlled, are often high on internal validity.
However, their strength with regard to structure and control, may result in low external validity. The results may be so limited as to prevent generalizing to other situations.
In contrast, observational research may have high external validity generalizability because it has taken place in the real world. However, the presence of so many uncontrolled variables may lead to low internal validity in that we can't be sure which variables are affecting the observed behaviors. Relationship between reliability and validity. If data are valid, they must be reliable. If people receive very different scores on a test every time they take it, the test is not likely to predict anything.
When we conduct research, we are continually flitting back and forth between these two realms, between what we think about the world and what is going on in it. When we are investigating a cause-effect relationship, we have a theory implicit or otherwise of what the cause is the cause construct. For instance, if we are testing a new educational program, we have an idea of what it would look like ideally. Similarly, on the effect side, we have an idea of what we are ideally trying to affect and measure the effect construct.
But each of these, the cause and the effect, has to be translated into real things, into a program or treatment and a measure or observational method. We use the term operationalization to describe the act of translating a construct into its manifestation. In effect, we take our idea and describe it as a series of operations or procedures.
Now, instead of it only being an idea in our minds, it becomes a public entity that anyone can look at and examine for themselves. It is one thing, for instance, for you to say that you would like to measure self-esteem a construct.
But when you show a ten-item paper-and-pencil self-esteem measure that you developed for that purpose, others can look at it and understand more clearly what you intend by the term self-esteem.
Now, back to explaining the four validity types. They build on one another, with two of them conclusion and internal referring to the land of observation on the bottom of the figure, one of them construct emphasizing the linkages between the bottom and the top, and the last external being primarily concerned about the range of our theory on the top.
Assume that we took these two constructs, the cause construct the WWW site and the effect understanding , and operationalized them -- turned them into realities by constructing the WWW site and a measure of knowledge of the course material. Here are the four validity types and the question each addresses:. In this study, is there a relationship between the two variables? In the context of the example we're considering, the question might be worded: There are several conclusions or inferences we might draw to answer such a question.
We could, for example, conclude that there is a relationship. We might conclude that there is a positive relationship. We might infer that there is no relationship. We can assess the conclusion validity of each of these conclusions or inferences. Assuming that there is a relationship in this study, is the relationship a causal one?
Just because we find that use of the WWW site and knowledge are correlated, we can't necessarily assume that WWW site use causes the knowledge. Both could, for example, be caused by the same factor. For instance, it may be that wealthier students who have greater resources would be more likely to use have access to a WWW site and would excel on objective tests.
Researchers often rely on subject-matter experts to help determine this. In our case, the researchers could turn to experts in depression to consider their questions against the known symptoms of depression e. In this case, the researchers could have given a questionnaire on a similar construct, such as anxiety, to see if the results were related, as one would expect.
Or they could have given a questionnaire on a different construct, such as happiness, to see if the results were the opposite.
The researchers could see how their questionnaire results relate to actual clinical diagnoses of depression among the workers surveyed. Researchers also need to consider the reliability of a questionnaire. Will they get similar results if they repeat their questionnaire soon after and conditions have not changed?
In our case, if the questionnaire was administered to the same workers soon after the first one, the researchers would expect to find similar levels of depression.
Internal validity and reliability are at the core of any experimental design. External validity is the process of examining the results and questioning whether there are any other possible causal relationships.
Internal validity - the instruments or procedures used in the research measured what they were supposed to measure. Example: As part of a stress experiment, people are shown photos of war atrocities. Example: As part of a stress experiment, people are shown photos of war atrocities.
Validity: the best available approximation to the truth of a given proposition, inference, or conclusion. The first thing we have to ask is: "validity of what?" When we think about validity in research, most of us think about research components. "Any research can be affected by different kinds of factors which, while extraneous to the concerns of the research, can invalidate the findings" (Seliger & Shohamy , 95). Controlling all possible factors that threaten the research's validity is a primary responsibility of every good researcher.
Internal consistency reliability is a measure of reliability used to evaluate the degree to which different test items that probe the same construct produce similar results. Average inter-item correlation is a subtype of internal consistency reliability. Research validity in surveys relates to the extent at which the survey measures right elements that need to be measured. In simple terms, validity refers to how well an instrument as measures what it is intended to measure.