Updated May 2020
Operational definitions became important in Psychology when psychologists wanted to establish that psychological experimentation is truly scientific in nature. In this blog post, we’ll look at exactly what is an operational definition is and how to do it. This is a common error in IB Psychology IAs. Hopefully after reading this post, students will be able to write excellent operational definitions of their independent and dependent variables.
What is an operational definition?
We all know that a “definition” is the given meaning of something. The “operational” part means giving the meaning of something as it’s being used in a particular study. So in psychology, an operational definition means defining the variable as it exists in the present study. You need to state clearly and very specifically, how you are manipulating your IV, and how you are measuring your DV?
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Here are some common independent variables that psychology students use in their experiments:
- Depth of processing (e.g. in a levels of processing study like Craik and Lockhart).
- Schema activation (e.g. Bransford and Johnson or Loftus and Palmer)
- Anchors (high and low) (e.g. in a Kahneman and Tversky study).
These terms are quite vague. What does “schema activation” mean? In order to provide an operational definition of this variable, you have to clearly describe the two conditions of your experiment (see below for examples).
Similarly, if we look at some examples of dependent variables we’ll see they’re just as vague:
- Working memory
These are the variables being measured in experiments. In order to write an operational definition you must write exactly how you plan on measuring these variables.
IB Psych IA Tips
- The rubric states that you must operationally define your IV and DV in your research and/or null hypothesis. I recommend doing it in your research hypothesis (see below for examples).
- Write your operational definitions of your IV and DV separately before you write your hypotheses. Include them separately (and well labelled) in your IA Introduction as well as in your research hypothesis. You might get credit for operational definitions of your IV and DV even if they’re not in your hypotheses.
- Using brackets is a good way to include operational definitions in your hypotheses (see below).
- You will not get it right the first time. Write, edit, re-write, edit, re-write and keep going until you think it’s perfect.
Example #1: Drug Trial
Imagine I was conducting an experiment that was trialling the effectiveness of a drug treatment on PTSD symptoms. The drug therapy is my independent variable and PTSD symptoms is my dependent variable. In order to write an operational definition of the IV I must describe the two conditions of my experiment. It might look something like this:
- Drug treatment: One group will take 20mg of Paroxetine (as a pill) every morning for 7 days, whereas the control group will take an identical placebo pill every morning for 7 days.
The above operational definition of “drug therapy” is stated in a way so you know exactly how it is being manipulated., i.e. you know the two different conditions of the experiment. If you want to know if you’ve written a good operational definition, ask someone to read it and get them to tell you the difference between the two groups in your study. If they can’t do this, the chances are your operational definition is too vague. Remember, we want our studies to be easily replicated, so others have to be able to follow our methodology.
“PTSD symptoms” is very vague. It doesn’t tell me how they’re being measured. So in order to operationally define this DV I need to describe exactly how they’ll be measured. It could look like this:
- Symptoms of PTSD are measured using scores from the Clinically Administered PTSD Scale (CAPS).
My research hypothesis with operational definitions might look something like this: Taking 20mg of paroxetine (as a pill) every morning for 7 days has a greater reduction of PTSD symptoms (measured the CAPS scale) than taking a placebo pill every morning for 7 days.
Example #2: Media and Body Image
I wrote an example IA I wrote on how media can affect body image (I didn’t really do this experiment, but I wrote it as an example that students can’t copy). In my study, I wanted to see if watching a video that shows beautiful people can affect body image. My IV is “type of media watched.” This is quite vague so I need to clearly describe how I’m manipulating this, which as you’ll see ends in me describing my two conditions of the experiment:
- Type of media:” Watching a video portraying the thin ideal in a Baywatch film trailer compared with watching media with “normal” body types in the Grownups film trailer.
You define my IV specifically in my study I have to describe the different conditions very specifically.
My DV is “body dissatisfaction.” But this could be measured a number of different ways. To have an operational definition I need to explain exactly how I am measuring it in my particular study. In my made-up study, the operational definition of body dissatisfaction was:
- Scores on the Body Shape Questionnaire (BSQ-34).
My research hypothesis with operational definitions might look something like this: Watching a video portraying the thin ideal (in a Baywatch film trailer) increases body dissatisfaction more than watching a clip with “normal” body types (in the Grownups film trailer) as measured using the Body Shape Questionnaire (BSQ-34).
Travis Dixon is an IB Psychology teacher, author, workshop leader, examiner and IA moderator.