Welcome to Experiments and Experimental Design!
In Unit 1 Topic B, we explore Cognitive Psychology—the study of how our minds process information like a computer. But how do psychologists actually "see" what is happening inside your head? Since we cannot watch a memory being formed, we use experiments to test our theories. This chapter will teach you the "tools of the trade" for designing a scientific study that is fair, accurate, and reliable.
1. Types of Experiments
In Cognitive Psychology, researchers usually choose between two main settings for their experiments. The choice often depends on how much control they need versus how realistic they want the situation to be.
Laboratory Experiments
These take place in a controlled environment (not necessarily a room with test tubes, but a place where the researcher manages everything).
Example: Asking a participant to sit in a quiet room and recall a list of words from a computer screen.
Strengths: High control over extraneous variables, making it easier to replicate (repeat) the study to check for reliability.
Weaknesses: The environment can be artificial, leading to low ecological validity (it doesn't reflect real life).
Field Experiments
These happen in a natural, everyday setting. The researcher still manipulates an independent variable, but the participants are often unaware they are in a study.
Example: Changing the way a teacher gives instructions in a real classroom to see if it affects students' memory of a lesson.
Strengths: High ecological validity because behavior is natural.
Weaknesses: Harder to control outside distractions, which can lower internal validity.
Quick Review: Think of a Lab experiment like a "closed set" movie studio and a Field experiment like "hidden camera" footage in a park!
2. Variables: The Building Blocks
To run a successful experiment, you must identify exactly what you are changing and what you are measuring.
Independent and Dependent Variables
1. Independent Variable (IV): The thing the researcher changes or manipulates.
2. Dependent Variable (DV): The thing the researcher measures (the "effect").
Operationalisation
This is a fancy word for making your variables measurable. You can't just measure "memory." You have to measure "the number of words correctly recalled from a list of 20."
Common Mistake: Forgetting to include the unit of measurement. Always say "the score on a test" or "time in seconds," not just "intelligence" or "speed."
Extraneous and Confounding Variables
These are the "nuisance" variables that might ruin your results:
- Situational Variables: Features of the environment (e.g., noise, temperature) that might affect the DV.
- Participant Variables: Differences between the people in the study (e.g., one person has a naturally better memory than another).
- Confounding Variables: If an extraneous variable actually changes the results, it becomes a confounding variable, making the study's findings confused or invalid.
3. Hypotheses: Predicting the Future
A hypothesis is a clear, testable statement about what you think will happen. In your exam, you may need to write these using the symbols \(H_1\) (experimental) and \(H_0\) (null).
Experimental Hypotheses (\(H_1\))
- Directional (One-tailed): You predict exactly which way the results will go.
Example: "Participants will recall significantly more words in a quiet room than in a noisy room."
- Non-directional (Two-tailed): You predict there will be a difference, but you aren't sure which way.
Example: "There will be a significant difference in the number of words recalled between the quiet and noisy conditions."
The Null Hypothesis (\(H_0\))
This predicts that there will be no difference or that any difference is just down to chance.
Example: "There will be no significant difference in words recalled... any difference is due to chance."
4. Experimental Designs
How do you organize your participants? There are three main ways:
Independent Groups
Different participants are used in each condition of the IV.
Pros: No order effects (participants don't get tired or bored).
Cons: Participant variables (one group might just be "smarter" than the other).
Repeated Measures
The same participants take part in both/all conditions of the IV.
Pros: No participant variables; you need fewer people.
Cons: Order effects! Participants might get better with practice or worse due to fatigue.
Matched Pairs
Pairs of participants are matched on a specific trait (like IQ or age). One person from the pair goes into Condition A, the other into Condition B.
Pros: Reduces participant variables without causing order effects.
Cons: Very time-consuming and difficult to match people perfectly.
5. Controlling the Experiment
To keep an experiment "fair" and objective, we use these controls:
- Counterbalancing: Used in Repeated Measures. Half the group does Condition A then B; the other half does B then A. This cancels out order effects like boredom or practice.
- Randomisation: Using chance (like flipping a coin) to decide who goes in which group or what order tasks are done. This prevents researcher bias.
- Control Groups: A group that does not receive the "treatment" (the IV). This provides a baseline to compare results against.
- Standardisation: Keeping the instructions and procedures exactly the same for every single participant.
6. Evaluation: Reliability and Validity
When you evaluate a study (AO3), use these "Big Six" terms:
1. Reliability: Is the study consistent? If we did it again, would we get the same result?
2. Validity (Internal): Are we measuring what we claim to be measuring? Or did an extraneous variable interfere?
3. Validity (Ecological): Does the task and setting reflect real-world behavior?
4. Validity (Predictive): Can the results help us predict future behavior?
5. Objectivity: Is the researcher being factual and unbiased, or are they letting their own feelings slip in (Subjectivity)?
6. Credibility: Overall, how believable and "scientific" is the research?
Problems to Watch Out For:
- Demand Characteristics: When participants guess the aim of the study and change their behavior to "help" or "hinder" the researcher.
- Experimenter Effects: When the researcher’s own behavior (like body language or tone of voice) accidentally influences the participants.
Summary Key Takeaways
- Lab Experiments: High control, low realism.
- Field Experiments: Low control, high realism.
- Independent Groups: Avoids order effects but risks participant differences.
- Repeated Measures: Avoids participant differences but risks order effects (use counterbalancing!).
- Hypotheses: Directional (predicts which way) vs. Non-directional (predicts any change).
Don't forget! In Unit 1 Topic B, you will need to apply these designs to your own Practical Investigation (a laboratory experiment using a repeated measures design). Keep these rules in mind when planning your own memory test!