1/2 Types of Experiments + Aims and Hypotheses

Experiment

A research method where the researcher manipulates an independent variable (IV) to measure its effect on a dependent variable (DV) under controlled conditions.

Independent variable (IV)

The variable that is manipulated by the researcher.

Dependent variable (DV)

The variable that is measured to see the effect of the IV.

Operationalisation

Defining variables in a way that allows them to be measured or manipulated clearly and precisely.

Extraneous variables

Any variables other than the IV that could affect the DV and threaten validity.

Situational variables

Extraneous variables in the environment, such as noise, lighting or temperature, that may affect participant behaviour.

Participant variables

Extraneous variables related to individual differences, such as age, intelligence or mood, that may affect results.

Confounding variables

Extraneous variables that change systematically with the IV, making it impossible to know which variable caused the effect.

Internal validity

The extent to which changes in the DV are caused by the IV rather than extraneous variables.

External validity

The extent to which the findings of a study can be generalised beyond the research setting.

Ecological validity

A type of external validity referring to how well the findings can be generalised to real-life settings.

Population validity

A type of external validity referring to how well the findings can be generalised to the target population.

Cause and effect

A relationship where changes in the IV directly result in changes in the DV.

What are the Types of experiments

Quasi, Natural, Lab and Field

Laboratory experiment

An experiment conducted in a highly controlled environment where the researcher manipulates the IV and measures the DV.

Field experiment

An experiment conducted in a natural environment where the IV is manipulated by the researcher.

Natural experiment

An experiment where the IV is naturally occurring and not manipulated by the researcher.

Quasi-experiment

An experiment where the IV is based on an existing difference between participants rather than being manipulated.

Laboratory experiment – Strength

High control over extraneous variables increases internal validity.

Laboratory experiment – Strength

Allows researchers to establish cause and effect relationships.

Laboratory experiment – Weakness

Artificial environment may reduce ecological validity.

Laboratory experiment – Weakness

Demand characteristics may influence participant behaviour.

Field experiment – Strength

Higher ecological validity because behaviour is more natural.

Field experiment – Strength

Reduced demand characteristics as participants are often unaware they are being studied.

Field experiment – Weakness

Less control over extraneous variables reduces internal validity.

Field experiment – Weakness

Ethical issues such as lack of informed consent may arise.

Natural experiment – Strength

Useful when manipulation of the IV would be unethical or impractical.

Natural experiment – Strength

High ecological validity due to real-life context.

Natural experiment – Weakness

Lack of control over the IV reduces internal validity.

Natural experiment – Weakness

Extraneous variables may confound results.

Quasi-experiment – Strength

Allows research into variables that cannot be ethically manipulated, such as mental health conditions.

Quasi-experiment – Strength

Often high ecological validity.

Quasi-experiment – Weakness

Participants cannot be randomly allocated, reducing internal validity.

Quasi-experiment – Weakness

Cause and effect cannot be confidently established.

Improving Validity in Experiments

Randomisation

The use of chance to control extraneous variables, such as randomly allocating participants to conditions.

Randomisation – Effectiveness

Reduces the impact of participant variables and increases internal validity.

Standardisation

Keeping procedures, instructions and conditions the same for all participants.

Standardisation – Effectiveness

Reduces situational variables, improving reliability and internal validity.

Control group

A group that does not receive the experimental treatment and acts as a baseline for comparison.

Control group – Effectiveness

Allows researchers to determine whether changes in the DV are due to the IV, increasing internal validity.

What are the types of Research Design/ Participant Allocation

Matched pairs, Independent group design, Repeated measures

Independent groups design

Different participants are used in each condition of the experiment.

Independent groups – Strength

No order effects such as fatigue or practice.

Independent groups – Weakness

Participant variables may affect results.

Repeated measures design

The same participants take part in all conditions of the experiment.

Repeated measures – Strength

Controls participant variables.

Repeated measures – Weakness

Order effects may occur.

Matched pairs design

Participants are matched on key characteristics and placed into different conditions.

Matched pairs – Strength

Reduces participant variables without order effects.

Matched pairs – Weakness

Time-consuming and difficult to match participants accurately.

Quantitative data

Numerical data that can be analysed statistically.

Qualitative data

Descriptive data that describes experiences or behaviours.

Measures of central tendency

Statistical averages such as mean, median and mode.

Measures of dispersion

Statistics that show spread of data, such as range and standard deviation.

What are the Ethics in Experiments

Informed consent

Debriefing

Deception

Right to withdrawal

Confidentiality

Protection from arm

Informed consent

Participants must be fully informed about the study and agree to take part.

Deception

Misleading participants about the true aim of the study.

Debreifing

ensuring that participants have been debriefed and have the opportunity to ask questions

Right to withdraw

Participants can leave the study at any time without penalty.

Protection from harm

Participants should not be exposed to physical or psychological harm.

Confidentiality

Participants’ personal data must be kept private.

Aim

A general statement of the purpose of a study, outlining what the researcher intends to investigate.

Why aims are used

Aims provide a clear focus for the research and guide the design, procedure and hypotheses of the study.

Operationalisation (aims)

The process of defining variables in a clear, measurable way so the study can be replicated.

Hypothesis

A testable prediction about the relationship between variables that can be supported or refuted by evidence.

Why hypotheses are used

Hypotheses allow researchers to test predictions scientifically and draw conclusions from data.

Experimental hypothesis (research hypothesis)

A statement predicting a difference or relationship between variables.

Example of an experimental hypothesis

Participants who revise using flashcards will score higher on a memory test than participants who do not revise.

Null hypothesis

A statement predicting that there will be no difference or no relationship between variables.

Example of a null hypothesis

There will be no notable difference in memory test scores between participants who revise using flashcards and those who do not.

Why both null and experimental hypotheses are used

The null hypothesis is tested statistically, and if rejected, it provides support for the experimental hypothesis.

Difference between experimental and null hypotheses

The experimental hypothesis predicts an effect, whereas the null hypothesis predicts no effect.

Directional hypothesis

A hypothesis that predicts the direction of the difference or relationship between variables.

Example of a directional hypothesis

Participants who revise using flashcards will score higher on a memory test than those who do not.

When to use a directional hypothesis

Used when previous research or theory suggests the expected direction of results.

Non-directional hypothesis

A hypothesis that predicts a difference or relationship but does not state the direction.

Example of a non-directional hypothesis

There will be a difference in memory test scores between participants who revise using flashcards and those who do not.

When to use a non-directional hypothesis

Used when there is little or no previous research or when the direction of results is unclear.