In this chapter, we will look at how variables fit into research, how they differ from constructs, how they are operationalized
by researchers, how they are categorized in studies, how the categories relate to each other, and what you must consider in looking
at the different types of variables.
In the simplest terms, a variable is something that may vary, or differ. For instance, a person's proficiency in Spanish
as a foreign language may differ over time as the person learns more and more Spanish. As a tentative definition for statistical
research in our field, we will view variables as human characteristics or abilities that differ over time or among individuals.
Most variables that differ over time also vary among individuals, but the reverse is not necessarily true. Some of the many variables
that differ both over time and among individuals include language proficiency, motivation, self-esteem, and health.
A few that typically vary only among individuals are sex(the state of being male or female), nationality, fist-langauge
background, intelligence, and language ability(although there is some conterversy about whether the last two can vary over
time as well).
- Abstract variable (construct or trait) ===> Theoritical definition ===> Operationalize definition ===> Quantifying observation
- Concrete variable
- Discrete variable (discontinus variable) : for instance, sex is different from one person to another
- Continus variable
Variables versus constructs
It is important to distinguish variables from the underlying constructs that they represent. A variable is essentially what
we can observe or quantify of the human characteristics or abilities involved, whereas a construct is the actual characteristic
or ability that it represents in human beings. The construct proficiency in Spanish (the actual human ability) could be represented
by the variable test scores in Spanish proficiency (what we can observe and measure of the construct in question). However, it is important
to remember that the scores are not the ability about reflection of the ability.
The operationalization of variables is a researcher's chance to explain how each variable is being defined with respect to the construct
in question. Basically, it must be a definition that is based on observable, testable, or quantifiable characteristics.
Moreover, an operational definition must be unique, or exclusive; the definition must not also fit other possible constructs. We would
probably encounter a much more narrowly labeled abstraction in any real study, such as a construct called "overall proficiency in English as
a foreign language." One step, then, in looking at a researcher's operational definition of variables is to evaluate whether the construct
has been labeled with adequate precision, both theoritically and practically. Although the construct in this example may now seem narrower in
scope, it should be clear to any language teacher that "overall proficiency in English as a foreign language" is still a broad abstraction.
To bring this construct down to earth and form a variable, the investigator might choose to define it as follows: overall proficiency in English
as a foreign language as measured by the Test of English as a Foreign Language(TOEFL). This is an operational definition of the variable.
Different types of variables
Dependent, independent, moderator, control, and intervening are five types of variables that distinguished primarily by the relationships
that the research hypothesizes to exist among them. Hence, a variable that functions as a dependent variable in one study may be an independent variable in another.
And you should keep in mind that a variable is an observed or quantified representation of a construct, which is the actual underlying human characteristic or
ability in question.
A dependent variable is observed to determine what effect, if any, the other types of variables may have on it. In other words, it is the variable
of focus -- the central variable -- on which other variables will act if there is any relationship. Thus, a dependent variable cannot be identified in isolation. The key to
figuring out which is the dependent variable is to ask which variable is being measured to determine the effect of other variables on it.
a VARIABLE which changes or is influenced according to changes in one or more INDEPENDET VARIABLES. For example, suppose two methods
of teaching reading comprehension were being compared: the dependent variable might be the number of correct responses on a reading comprehension test adminstered
after instruction. The reading test scores would be the dependent variable, because those scores are dependent on the independent variable of instruction.
Hacth & Farhady 1982; Kerlinger 1976