Do you have to write up a conceptual framework for your thesis?
Then you should definitely keep watching! A conceptual framework illustrates what
you expect to find through your research. It defines the relevant variables for your study
and maps out how they might relate to each other.
In this video, we will go through an example with 2 key variables: hours of study and exam score.
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Variables are simply the characteristics or properties that you want to study.
The conceptual framework will map the expected rel ationship between them.
You develop the conceptual framework based on your literature review.
Speaking of which, we have a whole playlist on literature reviews, check it out here!
By looking at what other researchers have found or theorized,
you can come up with ideas about the relationship between your variables.
And based on what we've learned about these variables from our literature review, we think
that studying more hours will cause a higher exam score. We want to test whether there is a
cause-and-effect relationship between the amount of hours you study and the exam score you get.
That means hours of study is our independent variable, and exam score
is our dependent variable. Because we think that exam score depends on hours of study.
A conceptual framework can be designed in many different ways. The form yours takes will depend
on what kinds of relationships you expect to find. To visualize our expected cause-and-effect
relationship, we will use the basic design components of boxes, arrows,
and lines. We used the boxes for the variables, and an arrow starting from the independent
variable to indicate a causal relationship. Now that we have the basics laid down,
let's move onto expanding the conceptual framework. As you develop your conceptual
framework, you should also aim to identify other variables that might influence the relationship
between your independent and dependent variables. Some common variables to be incorporated into the
conceptual framework include: Moderator variables
Mediator variables Control variables
A moderator alters the effect that an independent variable has
on a dependent variable. For example,
the variable “IQ” moderates the effect that the number of study hours has on the exam score. In
other words, the higher your IQ, the fewer hours of study you must put in to do well on the exam.
a mediating variable is a variable that links the independent and dependent variables,
helping explain how or why the independent variable affects the dependent variable.
For example, the hours of study impacts the variable “number of practice problems completed”,
which in turn impacts the exam score.
The more hours a student studies, the more practice problems they will complete;
the more practice problems completed, the higher the student’s exam score will be.
By adding the mediating variable of “number of practice problems completed,”
we help explain the cause-and-effect relationship between the two main variables.
So while both moderators and mediators have an
impact on the dependent variable, the key difference between them is:
A moderator is not affected by the independent variable
A mediator is affected by the independent variable
For example, the variable “IQ” is a moderator, not a mediator: although IQ may impact the exam
score (the dependent variable), the number of hours spent studying (the independent variable)
does not affect IQ. No matter how many hours you study, your IQ will not increase.
A control variable is a variable that is held constant to prevent
it from influencing the outcome of a study.
These are variables that aren't relevant to your research question - you're not interested in
actually studying their effects, you just want to make sure they don't interfere with your results.
For example, it is likely that if a student feels ill, they will
get a lower score on the exam. Therefore, we’ll add “health” as a control variable.
Now you should know the basics you need to construct a conceptual framework! Click on this
playlist to continue working on other parts of your research process, see you in the next video!