Commonly Confused Research Terms

Concept vs. Construct

A concept is a bundle of meanings and characteristics created by classifying and categorizing objects or events. A construct is an image or idea specifically invented for a given set of research and / or theory-building purposes. Concepts are often borrowed from another field of study and then applied in a new way during a research study. An abstract concept can often be considered a construct. For example, pass percentage of completion for the quarterback in football is a relatively well-understood concept that could be considered a construct, while ability to win is also an important, but abstract concept. Both pass percentage of completion and ability to win are skills expected of a good quarterback that can be researched and quantified to some degree, but there are vast differences in their measurability and precise definitions. Furthermore, a researcher may build a construct from other simpler concepts to assist in a theory building exercise. For example, pass percentage of completion could be one of concepts that comprises a construct named ability to win.

Deduction vs. Induction

Dewey’s so-called Double Movement of Reflective Thought (Cooper and Schindler, 2003) refers to the use of Induction and Deduction in tandem; it is an essential part of hypothesis formulation and testing prevalent in scientific thought processes. Deduction is a form of inference that presumes to be conclusive in that the conclusion follows from the reasons given and the reasons actually imply the conclusion (and represent a proof.) Induction is another form of inference in which a conclusion is drawn from one or more facts, and the process of inducing a conclusion represents an inferential jump beyond the evidence presented. In effect, Induction produces hypotheses that are tested through Deduction; Deductive / Inductive processes only produce hypotheses that must be later confirmed with data collection and analysis.

Operational Definition vs. Dictionary Definition

Clear definition of terms is an essential element of research. Dictionary-based definitions are provided through language synonyms. Often times, these synonyms are used to define one another or related word groups of similar, but not precisely the same meaning. This lack of precise definition is why dictionary definitions of concepts are unsuitable in a research environment. Operational definitions, however, are instead defined in terms of specific testing criteria or operations. An operational definition is one in which we must be able to measure, count, or collect data to verify a particular meaning. The operational definition of a concept must specify the characteristics to study and how those characteristics are to be observed, so that another researcher would classify the objects likewise.

Concept vs. Variable

A concept is a set of characteristics created by classifying objects or events that have common characteristics in two or more observations. Meanwhile, a variable is a synonym for the property under examination in an empirical setting; that is, a variable is defined in such a way that it takes an observed value at an instant, when we measure it. Observed variables may comprise an overall concept or construct in research, if they possess common characteristics.

Hypothesis vs. Proposition

Although there may be some dispute over the exact definition of a proposition and its relationship to a hypothesis, a proposition can be defined simply as a statement about concepts which can be judged to be either true or false, if the concepts are rooted in observable phenomena. A hypothesis is different in that it specifically refers to a variable or variables that can be empirically tested. A hypothesis is also more formally stated than a proposition, so that it can be accepted or rejected based on the actual observed phenomena. A hypothesis may describe the existence or magnitude of some variable, or it may describe a relationship between two variables with respect to some case. The most important role for the hypothesis in research is that it guides the direction of the study. In more lengthy research articles, it is common to find propositions stated quite generally that are later refined into testable hypotheses.

Scientific Method vs. Scientific Attitude

The Scientific Method can be thought of as the mind of science while the Scientific Attitude is the spirit driving scientific inquiry. The scientific method is structured inquiry into a well-defined topic. The scientific attitude is the underlying curiosity, imagination, and motivation to capture the most important element of a problem and apply the best technique for observing related phenomena in the most natural state. By analogy, business travel is a set of methods (i.e., scientific method) for traveling to the city of Chicago, whereas, desire to get to Chicago is the spirit of motivation (i.e., scientific attitude) to apply those business travel methods in the most optimal way. A scientific attitude in research provides the motivation continually to pursue inquiry in a scientific manner.

Examples of Variable Operationalization

Perhaps the distinguishing feature between concepts and constructs can be understood best as steps from an "abstract" research question toward a "concrete" variable. Consider these progressive stages in operationalization:

1. Research Question: Do parents have affection and concern for their children?
2. Conceptualization: Love (i.e., the concepts affection and concern might be conceptualized as "love")
3. Theoretical Construct: Parental Love for Children (i.e., a specific type of love is identified).
4. Operationalized Construct: Parental Love for Children as Time Spent with Children
5. Measurable Variable: Parental Love for Children as Time Spent with the Child per day.
6. Alternative Hypothesis: Parental Love for Children will be positively correlated with happiness of the child (not operationalized in this example).
   

The underlying lesson is that variables can be operationalized in multiple ways. In operationalizing Parental Love for Children, we could measure time spent with children, money spent in their care, number of words spoken to them, a qualitative analysis of themes discussed when speaking to the child, or we could even administer a survey to the child to ascertain perceived love as a proxy for parental love. All of those ways to measure love approximate the actual love experienced. There are many ways to operationalize a variable and these ways are determined (or bounded) by the original conceptualization.

An example of the many ways that variables can be operationalized, either optimally or otherwise, can be explained in attempting to measure whether Aunt Sally is at home baking pies on Sunday night after church. In order to test whether Aunt Sally is at home, we must decide how we are going to operationalize what the variable at home means for purposes of measurement. Do we see the lights on in the house? Does she answer the telephone? Does she answer a knock on the door? Does she answer her email? Is the Sunday paper still out front? Has she picked up her postal mail from the mailbox? Did she update her Apple Pie Blog website? Can you see her baking pies through the kitchen window? Is her Harley still parked in the driveway? Is the dog tied up out back? Are there spent shotgun shells on the back porch? Measuring whether Aunt Sally is indeed at home can be accomplished in many ways but there are only one or two best ways to stipulate an operational definition to arrive at a testable hypothesis.

Reference

Cooper, D.R., & Schindler, P.S. (2003). Business research methods, (8th ed.). Boston, MA: McGraw Hill.