Operational Definitions of Reasearch Variables Education

 Operational Definitions of Variables

journalpapers.org Such variables as giftedness, academic achievement, and creativity are conceptualizations that are defined in dictionary terms. But because these aspects cannot be observed directly, they are vague and ambiguous and provide a poor basis for identifying variables. Much more precise and unambiguous definitions of variables can be stated in operational form, which stipulates the operation by which they can be observed and measured.


Giftedness could be operationally defined as a score that is 2 or more standard deviations above the mean on the Wechsler Adult Intelligence Scale, academic achievement as a score on the Stanford Achievement Test, or creativity as a score on the Torrance Tests of Creative Thinking. When an operational definition is used, there is no doubt about what the researcher means.

 

To be useful, however, operational definitions must be based on a theory that is generally accepted. For instance, there are several theories of intelligence. If a researcher wants to use the term intelligence in her research report, she must define the term as it relates both to a theory and to how it will be measured (e.g., the theory of general intelligence and the IQ determined from the Stanford-Binet Test of Intelligence).

Operational definitions do not always prove useful in describing variables, for it is conceivable that they could be based on irrelevant behavior. For instance, defining self-esteem in terms of the number of seconds an individual smiles in a minute would not be a useful or realistic definition even though such behavior could easily be observed and recorded. To be meaningful, the behavior observed (or test score) must be related in a relevant way to the concept being defined.


The Hypothesis

 

Two important functions that hypotheses serve in scientific inquiry are the development of theory and the statement of parts of an existing theory in a testable form. In his now-classic chapter, Snow (1973) describes six levels of theory, with the first level being hypothesis for- mation. At this initial level, the theory the developer has a hunch based on theory, past experience, observations, and/or information gained from others.

 

A hypothesis is formulated in such a way that this hunch can be tested. Based on the findings of the subsequent research, the hypothesis is supported or rejected and more hypotheses are formulated to continue the process of building a cohesive theory.

 

The most common use of hypotheses is to test whether an existing theory can be used to solve a problem. In everyday situations, those who confront problems often propose informal hypotheses that can be tested directly. For example, when a lamp fails to light when the switch is turned on, several hypotheses come to mind, based on our understanding of electricity and on our past experiences with lamps:

 

1. The plug is not properly connected to the wall outlet.

2. The bulb is burned out.

3. The fuse is burned out or the circuit breaker has been tripped.

4. There has been a power failure in the neighborhood.

 

Each of these speculations can be tested directly by checking the plug connection, substituting a bulb known to be in working condition, inspecting the fuse or circuit breaker, or noting whether other lights in the house or in neighbors houses are on.

 

Research hypothesis

A study or scientific hypothesis is a formal positive statement that predicts a single outcome of a study, a conditional explanation of the relationship between two or more variables. In order for a hypothesis to be verified, the variables must be defined operationally. That is, the researcher shows what operations were performed or what tests were used to measure each variable. Hence, the hypothesis focuses the investigation on a specific goal and determines which observations or actions should be used.



Several years ago it was hypothesized that there is a positive causal relationship between smoking and the occurrence of coronary artery disease. This hypothesis offers an indicative explanation leading to many studies comparing the incidence of heart disease in smokers and nonsmokers. Based on this extensive study, the medical community now generally believes that this connection was made.

 

The Null Hypothesis (H0)

At the beginning of their study, researchers state an affirmative scientific or research hypothesis as a prediction of the outcome that they propose to test. Most often this research hypothesis suggests that a difference of some kind (e.g., one group will do better than another) will occur. Later, at the stage of the statistical analysis of the observed data, they restate this hypothesis in negative, or null, form.

 

For instance, the previously stated hypothesis, that third-grade children taught the Chisanbop method would score higher on a specified test of arithmetic than those using the conventional method would be restated: There is no sig- significant difference between the arithmetic achievement of the two groups. Some authors have argued that the null hypothesis cannot possibly be correct (e.g., Cohen, 1990; Murphy, 1990).


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