variables it is very important in research to see variables, define them, and control or measure...
TRANSCRIPT
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.