Definitional brainstorming session

R.W. Schwester
© 2015
All Rights Reserved
Except from Teaching Research Methods in Public Administration
Subsequent to identifying one’s variables, a researcher must thoroughly define all of
those variables. A researcher must convey his or her conception of what each variable means.
Using our recurring example – Do students that attend research methods class more frequently
perform better than students that attend class less frequently – a researcher cannot assume that
the reader understands his or her conception of the independent variable “attendance” or the
dependent variable “performance.” These are vague and ambiguous labels that can mean
different things to different people. You must specifically define what is meant by these labels,
because at this point, a researcher has done little more than label the DV, IV, and EVs. It is
necessary to go a step further and define what these “labels” mean. A logical question at this
point is: from where do variable definitions emerge? That is, does a researcher come up with his
or her own definitions, or does a researcher use (borrow and cite giving credit to that person)
another researcher’s definitions? Answer: Both are acceptable.
It is very important when defining your variables to be specific as possible. Let us
concentrate on defining the independent variable attendance. What do we mean by attendance?
What are the elements of attendance? What does it mean to “attend” class? It is important that
everyone is on the same page as to what constitutes attendance. Is attendance simply showing up
to class? In other words, if someone shows up to class, signs the attendance sheet, and then
leaves, does this count as having attended class? What if a student shows up, but only stays for
half of the class period. Does this count as having attended class? What if a student shows up,
stays for the entire class period, and then falls asleep in the back of the classroom. Does this
count as having “attended” class? Is attendance showing up, staying for the entire class period,
and “being engaged” (i.e., not falling asleep, participating, asking questions, etc…)? These are
the decisions that a researcher must make. Variable definitions must be specific. In this recurring
“attendance – performance” example, let us construct our own definitions.
When constructing your own definition, one way to start is by brainstorming the possible
“elements” of attendance?
Box 3.1
(IV) Attendance
may consist of…
 Physically showing up to class
 Signing in
 Staying for entire class period?
 Staying for part of the class period?
 Being attentive – taking notes, asking questions, etc…
versus day dreaming or sleeping in the back of the
 Arriving on time?
Box 3.2
Boxes 3.1 and 3.2 depict a definitional brainstorming session, albeit a very simplified
one. Ideas are first presented in Box 3.1 as to what elements might constitute “attendance.” In
Box 3.2, some of the elements presented in Box 3.1 are eliminated from consideration, and thus
the definition of “attendance” begins to take shape (at least this author’s conception of
attendance). I eliminated “signing in” because a student may simply sign in and leave class.
Staying for the entire class is central to attendance, and thus the notion of partially attending a
class was eliminated as a potential element of attendance. “Being attentive” speaks more to a
student’s performance within the class, their motivation and enthusiasm for the course material,
and ultimately their understanding of the course material when presented in lecture form. This, in
my estimation, goes beyond the scope of attendance. Given this, we are left with the definition
presented in Box 3.3 below.
 Physically showing up to class
 Signing in
 Staying for entire class period
 Staying for part of the class period?
 Being attentive – taking notes, asking questions, etc…
versus day dreaming or sleeping in the back of the
 Arriving on time
Box 3.3
Let us define another variable from our attendance – performance example. This time, we
will define the extraneous variable “professor quality.” When using this example in my own
classes, it elicits a number of entertaining responses.
The IV attendance is defined as:
Physically coming to class, arriving on time, and
staying for the entire class.
Professor Quality
may consist of…
Box 3.4
 Expert grasp of the subject matter
 Clarity
 Organization
 Enthusiasm and energy
 Availability for help
 Grades fairly
 Answers emails in a timely fashion
 Addresses questions effectively
 Good people skills
 Uses technology effectively
Box 3.5
Boxes 3.4 and 3.5 depict a brainstorming session for the extraneous variable “professor
quality.” Initial conceptions as to what might constitute “professor quality” are presented in Box
3.4 and subsequently some are eliminated from consideration in Box 3.5. In Box 3.6, the
definition of professor quality is presented. I eliminated “enthusiasm and energy” and “people
skills” simply because these are, in my opinion, luxuries when considering one’s teaching ability.
These elements would be nice to have but should not be considered a necessity. “Grades fairly”
was also eliminated given the subjective nature of this element. Students that do well are more
likely to believe that a professor has graded fairly than students that do poorly, irrespective of
whether professor quality played a role in the student’s final grade. For these reasons, after this
hypothetical brainstorming session, we are left with the following definition of professor quality.
 Expert grasp of subject matter
 Clarity
 Organization
 Enthusiasm and energy
 Availability for help
 Grades fairly
 Answers emails in a timely fashion
 Addresses questions effectively
 Good people skills
 Uses technology effectively
As you can see in Boxes 3.1 through 3.6, the process of creating your own definitions
begins with conceptualizing the potential elements of the variable and then narrowing down
those elements. Now, let us consider an example where we might use existing definitions as
opposed to creating our own from scratch. The research question – Does the death penalty
impact murder rates – works well for our purposes. The independent variable is the death
penalty and the dependent variable is murder rates. Murder rates are a function of several other
socio-demographic factors as well. Some of these factors – or extraneous variables – might
include: population density of a given area, unemployment rate, poverty rate, and education level
to name a few.
According to Black’s Law Dictionary, the death penalty is defined as:
Professor Quality
The EV professor quality is defined as:
Having an expert grasp of the course material;
presenting the course material in a clear and
organized way; being available to students;
answering emails in a timely fashion and addressing
questions effectively.
Box 3.6
Box 3.6
“Supreme penalty exacted as punishment for murder and other capital crimes”
(1979, p. 360).
By “supreme penalty,” a death sentence is implied in this definition.
According to the Uniform Crime Reports (UCR) of the FBI, murder is defined as:
“The willful (non-negligent) killing of one human being by another. The
classification of this offense is based solely on police investigation as opposed to
the determination of a court, medical examiner, coroner, jury, or other judicial
body. The UCR Program does not include the following situations in this offense
classification: deaths caused by negligence, suicide, or accident; justifiable
homicides; and attempts to murder or assaults to murder, which are scored as
aggravated assaults” (U.S. Department of Justice, 2013).
Recall that murder “rates” is the dependent variable, and the notion of “rates” implies x number
of murders for every y number of people in a given geographic location. The UCR collects data
on the number of murders statewide, but we have to decide what the “y” portion of this
calculation will be. Most crime data are presented in the context x number of offenses per 1,000
in population or x number of offenses per 100,000 in population – which is usually reserved for
larger populated geographic units. Either is fine, as the results are the same regardless of which
one you use. Only the decimal place is different. Our final definition for murder rates reads:
The number of willful (non-negligent) killings of one human being by another
for every 100,000 in population statewide.
Regarding the extraneous variables, let us focus on population density. The
concept of population density is this: a geographic location that is one square mile that
has 10,000 people has greater population density than a similar sized location with 5,000
people. The more people within a geographic unit, the greater the population density.
Urban areas have greater population density than rural areas. Knowing this, we need to
find a definition that captures this general concept. According to the U.S. Census Bureau,
population density is:
The total population of a given geographic area divided by the total square
mile of land area.
The extraneous variable unemployment rate deals with the number of people within a
specified geographic location that are not working and want to be working (i.e., people that are
looking for work and want to work are considered part of the labor force). Accordingly, the
Bureau of Labor Statistics defines unemployment rate as:
The total number of people considered to be unemployed divided by total
number of people within the labor force.
The extraneous variable poverty rate is defined in the context of income levels,
the size of the family unit, and the age of the family members within the unit. Figure 3.11
shows the federal poverty thresholds for 2013.
Figure 3.11
Source: U.S. Census Bureau
Accordingly, the poverty rate is defined as:
The percentage of families that fall below the federal poverty thresholds.
Finally, the extraneous variable education level is defined several ways by the
U.S. Census Bureau. That is, education level could be defined as:
The percentage of individuals that are high school graduates or higher for
persons age 25 and older.
Alternatively, education level could be defined as:
The percentage of individuals that have a Bachelor’s degree or higher for
persons age 25 and older.
The definition that is chosen is largely up to the researcher. The nature of the research
might dictate which variable definition, and therefore which measure of that same
variable, should be used. For example, a research topic that differentiates between
“higher educated” and “lower educated” communities might necessitate choosing the
definition that makes a distinction among those with at least a four-year college degree.
When defining your variables, it is important to keep in mind the nature of your
unit of analysis. Typically, although not exclusively, when your unit of analysis is
“individual” in nature, a researcher usually has the option of crafting his or her own
definitions or borrowing someone else’s definitions (provided of course that the
researcher cites the source of this definition). You could also use some combination of
self-crafted definitions and borrowed definitions when the unit of analysis is individual in
nature. When the unit of analysis is “collective” in nature, a researcher will, more often
than not, use existing definitions from reputable sources rather than craft his or her own.

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