Introduction: Why do we need Control?
Imagine you are testing a new "brain-power" energy drink to see if it helps students study better. You give the drink to one group of students at 8:00 AM in a quiet library, and you give plain water to another group at 10:00 PM in a noisy cafeteria. If the first group does better, is it because of the drink? Or was it the time of day? Or the noise level?
In Psychology, if we don’t control our environment, we can’t be sure what actually caused the behavior we are measuring. This chapter is all about how researchers keep their "experiments clean" so they can find the truth. This is a vital skill for Paper 2, where you will often have to plan your own study!
1. What is Control of Variables?
When we conduct an experiment, we change the Independent Variable (\(IV\)) to see how it affects the Dependent Variable (\(DV\)). Everything else that could possibly affect the \(DV\) is called an extraneous variable.
Control is the process of keeping these extraneous variables the same (constant) across all conditions of the study. If we don't control them, they might become confounding variables—factors that mess up our results and make us think the \(IV\) worked when it actually didn't!
Common types of variables to control:
Situational Variables: These are features of the environment (like noise, temperature, or the time of day). Example: Ensuring every participant in the Andrade (doodling) study was in a dull, quiet room.
Participant Variables: These are individual differences between people (like age, intelligence, or personality). Example: Making sure one group isn't naturally much smarter than the other.
Quick Tip: Think of "Control" as "keeping things fair." If one group has an advantage the other doesn't, the experiment isn't fair!
2. Standardisation: The "Recipe" for Research
Standardisation means keeping the procedure exactly the same for every single participant. This ensures that the only difference between people is the \(IV\).
To standardise a study, researchers use standardised instructions (reading the exact same script to everyone) and standardised procedures (doing everything in the same order, using the same equipment).
Why is standardisation important?
1. Reliability: If a study is standardised, another researcher can replicate (repeat) it to see if they get the same results.
2. Validity: It ensures that the results are actually due to the \(IV\) and not because the researcher treated some people differently.
Example from Core Studies: In Milgram’s (obedience) study, the "prods" used by the experimenter were standardised. If the participant hesitated, the experimenter had a specific set of four verbal prompts to say. They didn't just make it up as they went along!
3. Experimental and Control Groups
To see if a change actually matters, we often compare two groups:
Experimental Group: The participants who receive the "treatment" or the level of the \(IV\) we are interested in.
Control Group: The participants who do not receive the treatment. They provide a baseline so we can compare the results.
Analogy: If you want to know if a plant grows better with music, the Experimental Group gets music, and the Control Group gets silence. If both plants grow the same amount, you know the music didn't actually do anything!
4. Techniques for Controlling Variables
Psychologists use specific "tricks" to keep their studies valid:
A. Random Allocation
This is used in independent measures designs. Every participant has an equal chance of being in the experimental group or the control group (like flipping a coin). This helps "cancel out" participant variables (individual differences).
B. Counterbalancing
This is used in repeated measures designs (where one person does both tasks). Sometimes people get better at a task because of practice, or worse because of fatigue (boredom). These are called order effects.
To solve this, we split the group in half:
Group 1: Does Task A then Task B.
Group 2: Does Task B then Task A.
This "balances out" the effect of the order!
Memory Aid: Counterbalancing Cancels Confusion from Order effects!
5. Real-World Application: The Core Studies
In your exam, you might be asked how a specific study controlled variables. Here are two examples:
Piliavin et al. (subway Samaritans):
The researchers controlled the "victim's" appearance (same clothes), the location (the same stretch of subway track), and the timing of when the victim collapsed (70 seconds after the train started). This made sure the situational variables were consistent.
Baron-Cohen et al. (eyes test):
They used a standardised set of 36 photos of eyes. Every participant saw the exact same photos with the same four target words to choose from. This is a great example of standardised materials.
Quick Review: Common Mistakes to Avoid
Mistake 1: Confusing "Control of Variables" with "Control Group."
Correction: Control of variables is a process (keeping things the same). A control group is a set of people who don't get the treatment.
Mistake 2: Thinking standardisation means the study is "boring."
Correction: Standardisation is a strength! It means the study is scientific and can be checked by other scientists (replicability).
Key Takeaways
• Control minimizes extraneous variables so they don't become confounding variables.
• Standardisation means every participant has the same experience (same instructions and procedure).
• Random allocation controls for participant variables.
• Counterbalancing controls for order effects (practice and fatigue).
• These concepts help make a study valid (accurate) and reliable (consistent).