A Level Psychology - Experiments



Independent variable (IV) - what is manipulated by the researcher, creating different conditions, e.g. music or no music.

Dependent variable (DV) - what is measured by the researcher, e.g. time taken to complete a maze.

Extraneous variables - factors other than the independent variable (IV) that could confound/affect the results of the study. These can be situational, participant or experimenter.

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- precisely defining a variable so that it can be measured.
- for the IV, this means knowing how the variable was manipulated.
- for the DV, this means being confident that any variation is measured accurately.

For example:

Memory - could be operationalised as 'the number of words recalled out of 20'.

Intelligence - could be operationalised as ' score in an intelligence test out of 100'.

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Control conditions

- a control condition is where no manipulation is made and is usually used to gain a baseline measure.

- using a control condition allows us to conclude whether or not there is a cause and effect relationship because of the IV.

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Lab experiment

- manipulate IV and measure DV
- high control
- artificial environment

- high control means the researcher can be confident that there are no extraneous variables and can establish a clear cause and effect relationship.
- high control also means the study can be easily replicated and tested for reliability.

- artificial settings and tasks mean that the study often lacks ecological validity and cannot be generalised to real life behaviour.
- participants are usually aware that they are being observed so may not act naturally - due to demand characteristics or evaluation apprehension. Affects the internal validity.

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Field experiment

- manipulate IV and measure DV
- low control
- natural environment

- high ecological validity - behaviour can be generalised to real life situations.
- low chance of demand characteristics as participants are often unaware they are being observed.

- low levels of control so there may be a lot of extraneous variables to take into account, making it hard to establish a clear cause and effect relationship.
- difficult to replicate and check for consistency due to low control - can't confirm findings so not as reliable.

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Quasi experiment

- naturally occurring IV, so not directly manipulated by the researcher.
- could be in a lab or a field environment.

- the researcher can use an IV that would be unethical/unpractical to manipulate, e.g. age, gender, height, hair colour, etc.

- the IV is naturally occurring so participants will naturally belong to only one condition. Increases the risk of individual differences.
- some IV's are not frequently occurring so it may take time to fullly test the effects of something.

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Independent measures design

- where participants are randomly allocated to one of the experimental conditions.

- no risk of order effects as participants are in one condition or another.

- can be individual differences, for example, participants may be better at one task, etc.

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Repeated measures design

-participants take part in all experimental conditions.

- no risk of individual differences as participants take part in all conditions/complete all tasks.

- high chance of order effects, as participants may get bored/fatigued as they take part in all conditions. Can be solved by counterbalancing = when tasks are given in different orders to prevent order effects influencing the results.

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Matched pairs/participants design

- the researcher allocates participants to each group carefully to ensure the groups match in terms of key characteristics.

- no risk of order effects as participants take part in one condition or another.
- less risk of individual differences as participants are matched based on characteristics.

- very difficult, time consuming and costly to successfully match participants based on similar characteristics.

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Extraneous variables

- factors other than the IV that could affect the DV.

Situational - environmental factors, e.g. temperature, time of day, noise level, etc.
How to control - keep the environments the same for all participants in all conditions.

Participant - any differences not accounted for in the IV, e.g. age, gender, cultural background, etc.
How to control - use large sample sizes, randomly allocate participants to groups, use repeated measures design (however, could lead to order effects, e.g. boredom), matched pairs design.

Experimenter - the researcher may unconsciously convey to participants how they should behave = demand characteristics. Researcher may give away too much information about the study which can also lead to demand characteristics. Participants may want to appear 'normal' so may give socially desirable answers. Expectation effects - where experimenter is committed to achieving a particular outcome so may unknowingly influence the outcome.
How to control - single blind procedure (participants don't know aims/conditon they are in), double blind procedure (participants and researcher don't know aims/condition they are in), use placebo conditions, standardised instructions (all participants given the same information and all treated identically).

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Pilot studies

- a pilot study is a small scale practice run of your study.
- the researcher can find out whether certain aspects of the study do not work and therefore make alterations to their study to improve its design.

By identifying potential problems with the research, a psychologist can control possible extraneous variables.

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