Experiments Flashcards
What is an experiment?
The purpose of any experiment is to establish a cause and effect relationship between two variables. Researchers conducting experiments will manipulate one variable in order to measure/observe the effect on another variable, whilst attempting to control all other factors. There are several different types of experiments.
Lab experiment
The lab experiment is conducted in a HIGHLY CONTROLLED ENVIRONMENT, which is artificial and specifically set up for the purpose of the investigation. The researcher directly manipulates the IV and whilst keeping any other factors under close control (EV’s) in order to observe the changes in the DV as a direct cause of the IV.
- Manipulates an IV
- Measures a DV
- Lower controls in a natural setting
- Participants are usually unaware of research taking place
Field experiment
Unlike a lab experiment a field experiment is conducted in a NATURAL ENVIRONMENT. The researcher still manipulates the IV but is in a naturally occurring environment. Subsequently it is often the case that participants are unaware that a study is taking place and that they are in it.
- Manipulates an IV
- Measures a DV
- Lower controls in a natural setting
- Participants are usually unaware if research taking place
Quasi experiment
In this case the researcher makes use of an existing IV and therefore does not manipulate the IV. Usually takes place in laboratory conditions where there are high levels of control.
- Cannot manipulate the IV- naturally occurring
- Measures a DV
- Usually high controls in a setting which has been purposefully set up
- Participants are usually aware of research taking place
VARIABLES
IV
DV
Extraneous variables
IV- is manipulated by the researcher, creating different conditions eg music or no music
DV- is the behaviour that is being measured eg time taken to complete a maze or number of words recalled on a memory task
EV- If not controlled can confound the results of the study. Remembering that the aim of experiments is to find a cause and effect relationship between the IV and DV, the researcher needs to control any other variable that could interfere with that relationship
Operationalisation of variables
This refers to the idea of precisely defining a variable so that it can be measured.
For he IV this means knowing precisely how the variable was manipulated.
For the DV this means being confident that any variation is measured accurately.
Examples:
MEMORY- could be operationalised as ‘free recall out of a list of 20 words’
Experimental and control conditions
An experimental investigation usually has two or more conditions or levels of the IV and the DV is measured in each of these situations. To be certain that any changes in the DV arise only because of changes in the IV, the experimenter uses controls to keep constant any other factors that could affect the DV. It is this that ensures they can conclude whether or not there is a cause and effect relationship.
Example of experimental and control conditions
In a study investigating the effects of hunger on concentration, students could be tested an hour before and an hour after lunch. The time of day would be the IV, with two experimental conditions ‘before lunch’ and ‘after lunch’. The DV (of concentration) would be measured in each condition. A control condition is where no manipulation is made and is usually used to gain a baseline measure.
Cond 1: Before lunch
Cond 2: After lunch
Control condition: Any time of the day (no manipulation)
Strengths of lab
-High levels of control mean that the researcher is usually very confident that no extraneous variables have confounded his data and as such can establish a clear cause and effect relationship.
High levels of control also mean that the study can be easily replicated, thus allowing it to be tested for reliability.
Weaknesses of lab
Artificial settings and tasks mean that the study often bears little resemblance to the real life behaviour. As such lab experiments often lack ecological validity.
are often brought into lab experiments purposefully. As such they are aware that they are being observed and may not act naturally. This could be because of demand characteristics or evaluation apprehension. Ultimately this would affect the internal validity
Strengths of field
- High ecological validity- likely to get behaviour which has resemblance to real life and therefore can be generalised to real life situations.
- Low chance of demand characteristics- high ability to determine cause and effect and suggest high internal validity (measuring what you intend to)
Weaknesses of field
- Low levels of control therefore lots of extraneous variables which means establishing cause and effect is difficult reducing internal validity.
- Difficult to replicate and check for consistency- can’t confirm our findings and reduces reliability.
Strengths of quasi
- The researcher can use an IV that it would be unethical or not practical to manipulate. For example, comparing the behaviour of participants with a disorder to those without.
- There will still be high levels of control over extraneous variables and as such the researcher (as within a lab experiment) would be able to establish cause and effect)
Weaknesses of quasi
- Because the IV is naturally occurring, participants will naturally belong to one condition or another. As such, the researcher cannot randomly allocate to conditions which may increase the risk of individual differences.
- Some IV’s (for example some health conditions) are not frequently occurring so it may take time to fully test the effects of something.
- If the task is unnatural then the study could lack ecological validity and can’t be generalised to real life behaviour
Independent Measures
- Participants are randomly allocated to one of the experimental conditions.
- EG. In a study to test the effects of sleep deprivation on driving skills 20 participants are randomly allocated to the 3hr sleep condition and the other 20 to the 8hr sleep condition.
