Research Methods: Experimental Design

Research methods form the foundation of psychology as a science. To test hypotheses, establish cause-and-effect relationships, and generate reliable findings, psychologists must design studies carefully. The experimental method is the most powerful tool for establishing causation because it allows the researcher to manipulate one variable and measure its effect on another while controlling extraneous variables.

Key Definition: An experiment is a research method in which the researcher manipulates an independent variable (IV), measures a dependent variable (DV), and controls extraneous variables to establish a cause-and-effect relationship.

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Key Terms in Experimental Design

Term	Definition
Independent variable (IV)	The variable deliberately manipulated by the researcher to observe its effect
Dependent variable (DV)	The variable measured by the researcher to determine the effect of the IV
Extraneous variable (EV)	Any variable other than the IV that could affect the DV if not controlled
Confounding variable	An extraneous variable that has actually varied systematically with the IV, making it impossible to determine which variable caused the change in the DV
Hypothesis	A testable, precise prediction about the relationship between the IV and DV
Operationalisation	Clearly defining variables in terms of how they will be measured or manipulated

Hypotheses

• Directional (one-tailed) hypothesis — predicts the direction of the effect (e.g., "Participants who sleep for 8 hours will recall significantly more words than those who sleep for 4 hours").
• Non-directional (two-tailed) hypothesis — predicts that there will be a difference or effect but does not specify the direction (e.g., "There will be a significant difference in word recall between participants who sleep for 8 hours and those who sleep for 4 hours").
• Null hypothesis — states that there is no significant difference or effect; any observed difference is due to chance.

Exam Tip: When writing a hypothesis, always operationalise both the IV and the DV. A vague hypothesis such as "sleep affects memory" will not gain marks. Specify the amount of sleep and how memory is measured.

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Types of Experiment

Laboratory Experiment

Feature	Description
Setting	Controlled laboratory environment
IV	Manipulated by the researcher
Control	High — extraneous variables can be tightly controlled

Strengths:

• High internal validity — because extraneous variables are well-controlled, we can be more confident that changes in the DV are caused by the IV.
• Replicable — standardised procedures allow other researchers to repeat the study to verify findings.
• Precise measurement — equipment and conditions can be carefully calibrated.

Limitations:

• Low ecological validity — the artificial laboratory setting may not reflect real-life behaviour. Participants may behave differently because they know they are being studied.
• Demand characteristics — participants may guess the aim of the study and alter their behaviour accordingly (e.g., trying to "help" the researcher by confirming the hypothesis, or doing the opposite).
• Investigator effects — the researcher's expectations, behaviour, or appearance may unconsciously influence participants' responses.

Field Experiment

Feature	Description
Setting	Natural, real-world environment
IV	Still manipulated by the researcher
Control	Lower than lab — harder to control extraneous variables

Strengths:

• Higher ecological validity — behaviour is studied in a natural setting, so findings are more likely to reflect real-world behaviour.
• Reduced demand characteristics — if participants are unaware they are being studied, they are less likely to alter their behaviour.

Limitations:

• Lower internal validity — extraneous variables are harder to control in natural settings.
• Ethical concerns — if participants do not know they are being studied, informed consent cannot be obtained.
• Replication — it is harder to replicate a field experiment because conditions vary between settings.

Natural Experiment

Feature	Description
Setting	Varies — can be lab or field
IV	NOT manipulated by the researcher — occurs naturally (e.g., gender, exposure to a natural disaster, policy change)
Control	Variable — depends on the setting

Strengths:

• Allows study of variables that cannot be ethically manipulated (e.g., the effect of institutionalisation on children's development — Rutter et al., 1998).
• High ecological validity when conducted in real-world settings.

Limitations:

• The researcher cannot claim causation because the IV was not directly manipulated — the relationship may be confounded by other factors.
• Random allocation to conditions is not possible because the IV is naturally occurring.
• Difficult to replicate because natural events cannot be reproduced on demand.

Quasi-Experiment

Feature	Description
Setting	Varies
IV	Based on a pre-existing characteristic of participants (e.g., age, gender, clinical diagnosis)
Control	Variable

Strengths:

• Useful for studying variables that are inherent to participants and cannot be assigned (e.g., comparing people with and without a diagnosis of schizophrenia).

Limitations:

• No random allocation — participants are assigned to conditions based on their existing characteristics.
• Cannot establish causation — differences between groups may be due to other factors associated with the pre-existing characteristic, not the IV itself.
• Participant variables — pre-existing differences between groups are inevitable and cannot be eliminated.