Operationalization is the process of translating abstract things into concrete, measurable variables. It is one of those things that is more easily said than done. It is quite simple to explain to someone the purpose and importance of operational definitions for variables and even to describe how operationalization generally takes place. But a researcher will quickly appreciate some of the subtle difficulties involved when he or she attempts to operationalize a complex variable. Operationalization is how researchers define things by what they do. In other words, the “operations” are the procedures or steps one must go through in order to observe the concept being defined (Babbie 2001; Katzer et al. 1998). To get to this point in the research process, we must first look at how research begins.
Concepts, Conceptualization, And Operationalization
The research process starts off with a concept that a researcher is interested in measuring or observing. A concept is a “mental image that summarizes a set of similar observations, feelings, or ideas” (Schutt 2004, 86) or a “term that expresses an abstract idea formed by generalizing from particulars and summarizing related observations” (Wimmer & Dominick 2003, 42). Concepts are important for two reasons: (1) they simplify the research process by combining characteristics, objects, or people into more general categories; and (2) they simplify communication among those who have a shared understanding of them (Wimmer & Dominick 2003).
It is easy to identify concepts; for example, a story which appeared in the New York Times reported that five US colleges were participating in a pilot program to ban alcohol in their fraternities. The article also claimed that “substance-free housing” would become the norm on US campuses. Some of the concepts used in the article, like alcohol, colleges, campuses, and pilot program, are widely understood and commonly used. We might use these terms in conversation and never realize that your colleague was visualizing something completely different from you. From reading this article we might be left with several questions. (1) Is a junior college included in the term “college”? (2) Does the concept of “on campus” extend to fraternity and sorority houses that are not physically on college property? (3) Does “substance free housing” mean banning tobacco as well as alcohol?
Some of the concepts from the New York Times article illustrate that oftentimes there are concepts used in everyday conversation where people do not share the same definition. When this occurs, we need to explicitly define the concept so that all readers will share the same definition. This is what is known as conceptualization. It is the process of specifying what we mean by a term (Schutt 2004; Wimmer & Dominick 2003). In a similar vein, Babbie (2001) defines conceptualization as the mental process whereby fuzzy and imprecise notions are made more specific and precise. In addition, Schutt sees conceptualization differently based according to whether we are conducting inductive or deductive research. “In deductive research, conceptualization helps to translate portions of an abstract theory into specific variables that can be used in testable hypotheses. In inductive research, conceptualization is an important part of the process used to make sense of related observations” (Schutt 2004, 87). For example, if a person were to go into a classroom of 25 people and ask “What is your favorite cake?” It’s likely that most of the students in the classroom will probably not think of the same type of cake. If a researcher wanted to measure this concept, he or she would need to define what is meant by the term “cake.”
After we define the concepts in a theory, we can then identify variables corresponding to the concepts. Let’s say that we are interested in measuring differences between males and females on binge drinking. Our concept is binge drinking and we conceptualize it as “heavy episodic drinking.” Once we have defined it so that all readers will share the same definition, we can decide how we can measure this variable. One way we can measure it is by asking both males and females how many drinks they consumed in succession during some period.
Once we have specified the variable we want to measure, we can proceed to the next step in the design of our study – deciding on our measurement procedures. The goal is to devise operations that actually measure the concepts we intend to measure. This is referred to as the “operationalization of variables” or an “operational definition” (Wimmer & Dominick 2003). During this process, there will probably be several possible operational definitions for a given concept; the researcher must make a choice which one is most suitable for his or her research study. For this example, we are interested in conducting a study measuring people’s incomes. To measure income, we conceptualize income as annual earnings and operationalize the variable by asking the question “What was your total income from all sources in 2006?” When looking at income there is a large range of variation, from some people earning millions of dollars to those earning less than $5,000 per year. Depending on your sample, you as the researcher must decide what the highest and lowest income categories will be (Babbie 2001).
A good illustration of this process takes us back to our cake example from earlier. The operationalization for white cake is the recipe. It makes public what someone means by “white cake.” Anyone who has the recipe will be able to replicate the “white cake.”
White cake
Preheat oven to 375 degrees.
Sift together 31/2 cups of flour, 1/2 teaspoon of salt, and 4 teaspoons baking soda.
Blend together 1 cup of butter and 2 cups of sugar.
Add 1 teaspoon of vanilla to 1 cup of milk.
Slowly mix together in stages the flour mixture, the milk, and the creamed sugar.
Whip the whites of 7 eggs until stiff and fold them into the batter.
Bake in lightly greased pans for about 25 minutes.
The cake recipe above tells us what we need to do to make a white cake. Anyone with basic cooking skills could follow it and likely end up with something similar to what the author of the recipe had in mind, but it could differ in terms of taste, weight, height, and moistness. Even though the recipe appears specific, some aspects of it are still missing: the size of the eggs and the quality of butter are not specified; there is no adjustment specified in the recipe for higher altitudes. Each of these might affect the outcome of the cake, and so the recipe could have included them. If we were to look in a different cookbook for white cake we would likely find a slightly different recipe. If we followed that recipe, we would probably produce a cake much like the first one. This example shows us that there is no one correct recipe for a white cake. Along the same lines, there is no one correct operational definition for a concept (Babbie 2001; Katzer et al. 1998).
Types Of Operational Definitions
An operational definition is a specification of the activities of the researcher in measuring or manipulating a variable. There are, in general, two kinds of operational definitions: (1) measured and (2) experimental (Kerlinger 1986).
A measured operational definition describes how a variable will be measured. For example, achievement may be defined by a standardized achievement test, by a teachermade achievement test, or by grades. On the other hand, an experimental operational definition spells out the details of the investigator’s manipulation of a variable. Reinforcement can be operationally defined by giving the details of how subjects are to be reinforced (rewarded) and not reinforced (not rewarded) for specific behaviors.
Whether it is a measured or an experimental operational definition, researchers cannot underestimate the importance of operational definitions. They are indispensable ingredients of scientific research because they allow researchers to measure variables and because they are bridges between the theory-hypothesis-construct level and the level of observation. There can be no scientific research without observations, and observations are impossible without clear and specific instructions on what and how to observe. Operational definitions are those instructions.
Operational Definition Goals
Most researchers try to create definitions that ensure publicness, replicability, and, if possible, fruitfulness. These goals are part of an attempt to create definitions that reduce error. First, when researchers talk about reality, one wants to know specifically what they mean. Thus one must look for clear, unambiguous definitions of terms. For example, if a researcher is studying “eating,” he or she should specify whether drinking liquids and taking vitamin pills fall under the definition. In normal usage of the term “eating,” lack of specificity is not very important, but if a physical education researcher is studying the effects of various diet programs you need to know precisely what is meant (Katzer et al. 1998).
Second, to generate factually accurate information, researchers must check what they say against reality, and this means they must do something to define what they are talking about. For example, a researcher who studies eating by asking subjects how many meals a day they eat is using a very different definition than if he or she follows them around recording everything they eat. The researcher may have had the same conceptual definition in mind but then chosen different methods to actually observe eating. An acceptable operational definition helps readers and researchers by linking words with reality and by being public, specific, and replicable. But this is not enough.
The major criterion for the evaluation of any definition is its fruitfulness and is usually the most difficult to assess. To be fruitful, the conceptual definition must build on current theories and prior research. Fruitful definitions usually fit into the research traditions of a field. They build on what exists. There is occasionally justification for writers to construct new definitions, but they should not introduce new terminology into a field unless they are convinced that the existing set of concepts is inadequate.
In addition, the operational definition should coincide with the conceptual definition in a useful way. Since operational definitions usually do not include exactly what is of interest; several operational definitions that, taken together, encompass the conceptual definition completely are usually needed. This goal should be of particular concern to the researcher and to the reader or user of research. Having more than one operational definition increases the chances that at least one will be useful.
References:
- Babbie, E. (2001). The practice of social research, 9th edn. Belmont, CA: Wadsworth and Thomson Learning.
- Katzer, J., Cook, K. H., & Crouch, W. W. (1998). Evaluating information: A guide for users of social science research, 4th edn. Boston, MA: McGraw-Hill.
- Kerlinger, F. N. (1986). Foundations of behavioral research, 3rd edn. New York: CBS College Publishing.
- Leedy, P. D. (1997). Practical research: Planning and design, 6th edn. Upper Saddle River, NJ: Prentice Hall.
- Schutt, R. K. (2004). Investigating the social world: The process and practice of research, 4th edn. Thousand Oaks, CA: Pine Forge Press.
- Wimmer, R. D., & Dominick, J. R. (2003). Mass media research: An introduction, 7th edn. Belmont, CA: Wadsworth and Thomson Learning.