An operational definition is an aspect that provides or makes a description of the variable concrete. Furthermore, the operational definition provides a description of characteristics of a variable that are observable (Zimmermann, Lorenz, & Oppermann, 2007). Objects that can be seen and measured by a researcher usually represent visible qualities of an abstract. The three parts that often forms a part of an operational definition include concrete definitions of the given abstract qualities, the name of the variables value, and the assigned number of each variables value. The paper will, therefore, focus on providing a operational definition of a variable, validity reliability, and the laid out plan of how to conduct a measure of a study variable.
Operational Definition of a Variable
Operational definition of a variable is, therefore, a specific way through which the variable is measured in a given study and should be effectively tied to any theoretical constructs that exist within the given study (Zimmermann, Lorenz, & Oppermann, 2007). For example, the variable of self-esteem in a study tends to measure the feeling people have about themselves. The variable is often not measurable directly. However, there are three aspects of the variable called self-esteem that are measurable. The aspects include confidence of success level, self-belief level, and willingness of an individual to ask a question. Values that different confidence levels might take may often vary from high confidence or low confidence to very high confidence. Anxiety is another variable that defines any unpleasant feeling that may occur in a given situation. Anxiety can, therefore, be operationally defined through the measure of three aspects, including inquiring of the anxious level of people, measuring of the level of their psychology, and behavioral observation.
The term ‘validity’ often defines truthfulness of a given measure in a study, i.e. if it measures what it has intended to measure within the study (Morse, Barrett, Mayan, Olson, & Spiers, 2002). For example, when measuring such an aspect as intelligence, the major debate among psychologists has been whether the measures of intelligence that are frequently used assess all various aspects of intelligence. The major question has often been whether the given tests fully assess social intelligence, emotional intelligence, and creativity. There are five commonly distinguished types of validity, namely face validity, content validity, predictive validity, construct validity, and concurrent validity.
The aspect assesses the current performance and does not focus much on predicting future performance. In other words, the aspect of content validity tends to estimate the level by which a given measure represents each and every given element within a construct (Wynd, Schmidt, & Schaefer, 2003). For example, in any given program a test is often presented at the end of the program to measure whether those who participated in the program have mastered any content of the program or not.
The aspect shares a similar trait with the content validity, but in most cases it is determined only by the way a given test has been constructed. In other words, face validity defines the degree by which a given test appears to measure a variable subjectively.
The aspect measures the degree of perfection of how a given test correlates with a measure that has been previously validated. The concept is usually used in education psychology and social sciences. Besides, concurrent validity can refer to the aspect of concurrently testing two given groups or persuading two sets of groups of people that are different to take a similar test.
The aspect involves subjecting a particular group of subjects to a test for a certain construct and then comparing them with certain results that are obtained at some given point in the predicted future. The aspect is crucial in the process of developing required assessment tools in a given study.
The aspect tends to define the degree through which any inference can legally be made from the study operationalization to a theoretical construct (Nosek, Greenwald, & Banaji, 2005).
In most cases, researchers of a given study tend to be in need of dependable measurement. Furthermore, measurements tend to be reliable to a repeatable extent and existence of any random influence that makes the measurement different in different occasions is normally seen as a source of measurement error in a study (Golafshani, 2003). Reliability, therefore, measures the degree of a test consistency. Main errors that often affect the aspect of reliability are mainly random errors.
Plan of Measurement
One of the most important aspects of a research study is the question of how to plan to conduct measurement of study variables. The first important part is to identify and define the given study variable to be measured or any given factor that can change in the study. After identification of variables, the researcher must classify given variables into either continuous or discrete. The lack of awareness or understanding of classifying the study variables by researchers has often been the major cause of errors within a study and should be given maximum consideration when planning to measure a given study variable. The scale of measurement is then determined and in most cases the scale of measurement to be used depends on the given variable itself. The scale of measurement often includes a nominal scale that defines non-numeric variables, an ordinal scale that focuses on the order and not difference, and an interval scale that focuses on the interval between given numeric measurements.
The operational definition of a variable mostly provides a researcher with a given way to measure a variable in the study, while validity defines the aspect of providing accurate and credible measures. In turn, reliability provides consistency in measures. The plan to measure study variables, in turn, requires taking into account several aspects, which are directly related to the given variable.