Variables•It is very important

in research to see variables, define

them, and control or measure them.

Outline of today’s presentation

1. The concept and definition of variable2. Variables in research3. Constructs versus variables4. Operationalization5. Types and functions of variables6. Measurement Scales

The concept of variable

•The concept of variable is basic but very important in research. You won't be

able to do very much in research unless you know how to deal with variables .

•A variable is any entity that can take on different values across individuals and

time .

Some examples•Age can be considered a variable because

age can take different values for different people or for the same person at different

times .

•Similarly, country can be considered a variable because a person's country can

be assigned a value .

Variables in research

•Variables are things that we measure, control, or manipulate in research .

•The measurement may be different from everyday notions of measurement such as

weight and temperature .

•Measurement can involve merely categorization (e.g. sex, country, etc.)

Remember•Most variables that differ over time also vary

among individuals, but the reverse is not true. That is, the variables that differ among

individuals may not necessarily differ over time.

•An example for the former is “proficiency” and for the latter is “sex”.

Operationalization

•Variables such as intelligence, motivation, and academic achievement are concepts,

constructs, or traits that cannot be observed directly.

•They should be stated in precise definitions that can be observed and

measured. This process is called operationalization.

Operationalization

Intelligence

Trait or construct

Scores on the Wechsler Adult Intelligence Scale

Operational definition of intelligence

operationalization

Operationalization

Proficiency

Trait or construct

Scores on the TOEFL test

Operational definition of proficiency

Operational definition of a variable

•With students’ intelligence scores or TOEFL scores, we now have observable and

quantifiable definitions of what the researcher means by the constructs of “intelligence” and

“proficiency.”

•This is an operational definition of the variable.

Important point!

•Operational definitions must be based upon a theory that is generally

recognized as valid.

•For example, to operationalize the construct of “proficiency” we should

construct a test based on an accepted theory or model of language proficiency.

Different types and functions of variables

•In addition to knowing how constructs are operationalized as variables, it is

important to understand how such variables are classified and manipulated

by researchers in their quest to empirical knowledge.

•To that end, we describe five different functions of variables.

Functions of variables•To assess the relationship between variables

in research, we must be able to identify each variable. Variables can be classified as:

1.Independent2.Dependent3.Moderator4.Control5.Intervening

Independent vs. Dependent Variables

•An important distinction having to do with the term 'variable' is the distinction between an

independent and dependent variable .•This distinction is particularly relevant when

you are investigating cause-effect relationships (experiment). However, the

concept is also used in other research designs .

Independent vs. dependent V.

•In fact the independent variable is what you (or nature) manipulates --

a treatment or program or cause. The dependent variable is what is

affected by the independent variable -- your effects or outcomes .

Independent Variables•The independent variable is the major variable

which you hope to investigate. It is the variable which is selected, manipulated, and

measured (its effect) by the researcher. Examples:

•The effect of your instruction on reading scores of your students.

•The effect of social class on language use.

Dependent variable

•The dependent variable is the variable which you observe and measure to

determine the effect of the independent variable.

•In the previous examples, the reading scores of your students and the use of

language would be the dependent variable.

Two points.1A variable that functions as a dependent

variable in one study may be an independent variable in another study.

.2Depending on the design of the study, we may have more than one independent

and even more than one dependent variable in the study.

Moderator variable•A moderator variable is a special type of

independent variable which you may select for study in order to investigate whether it

modifies the relationship between the dependent and independent variables.

•Example, sex in the study of the effect of instruction on students’ reading scores

Independent vs. moderator variable

•The essential difference between independent and moderator variables lies in how the researcher views each in the study .

•For independent variables, the concern is with their direct relationship to the

dependent variable, whereas for moderator variables, the concern is with their effect on

that relationship.

Control variables•It is virtually impossible to include all the

potential variables in each study. As a result, the researcher must attempt to control, or

neutralize, all other extraneous variables that are likely to have an effect on the relationship

between the independent, dependent, and moderator variables.

Control variables•Control variables, then, are those that

the researcher has chosen to keep constant, neutralize, or otherwise

eliminate so that they will not have an effect on the study.

•Example, the effect of outside practice on reading in the previous example.

Intervening variables

•Intervening variables are constructs (other than the construct under study) that may

explain the relationship between independent and dependent variables but

are not directly observable themselves.

•We are somehow aware of their effects, but we are not able to account for them.

The relationship among variables

Independent

Variable(s)

Dependent

Variable(s)

Intervening

Variable(s)

Moderator

Variable(s)

Control

Variable(s)

The Study

Two points

•When designing a study, the researcher determines which variables fall into

each category.

•In real situations, all five types of variables may not be included in all

studies.

Measurement Scales

•To measure different variables, we have four measurement scales:

1. Nominal Scale2. Ordinal Scale3. Interval Scale4. Ratio Scale

Nominal Scale•Nominal scale classifies persons or

objects into two or more categories. Members of a category have a common set of characteristics, and each member may only belong to one category. Other

names: categorical, discontinuous, dichotomous (only two categories) .

True vs. artificial categories

•True categories are those to which the member naturally falls, such as gender

(male vs. female).

•Artificial categories are those to which the researcher places the members, such as learning style (field independent versus

field dependent).

Ordinal Scale

Ordinal variables allow us to rank order the items we measure in terms of

which has less and which has more of the quality represented by the

variable, but still they do not allow us to say "how much more“.Example: Ranking students

Ordinal ScaleOrdinal scales both classify subjects and

rank them in terms of how they possess the characteristic of interest. Members

are placed in terms of highest to lowest, or most to least. Students may

be ranked by height, weight, or IQ scores. Ordinal scales do not, however,

state how much difference there is between the ranks .

Interval ScaleNot only rank order the items that are measured, but also to quantify and compare the sizes of

differences between them .For example: students performance on a spelling test A score of 16 will be higher than 14 and

lower than 18 and the difference between them is 2 points (equal intervals) .

Interval scales normally have an arbitrary minimum and maximum point. A score of zero in a

spelling test does not represent an absence of spelling knowledge, nor does a score of 20

represent perfect spelling knowledge .

Ratio ScaleVery similar to interval scale; has all the properties of

interval variables, it has absolute zero point. Height, weight, speed, and distance are examples of ratio

scales. Measurements made with ratio scales can be added, subtracted, multiplied, and divided. For

example, we can say that a person who runs a mile in 5 minutes is twice as fast as a person who runs

the mile in 10 minutes. Because ratio scales are often used in physical measurements (where

absolute zero exists), they are not often employed in educational research and testing.