- A01 for each topic and evaluation where needed
- All notes were created from the AQA approved textbook
- Diagrams and examples included to assist in some topics
- Highly detailed to simplify both year 1 and 2 research methods
- Demonstrates how to answer common exam questions that come up
Experimental method
- A theory is an explanation or idea about a certain topic
- Aims are developed by theories when we want to prove them right
- Aim is a general statement of what the researcher intends to investigate, the purpose of the study.
- For example, ‘Investigating whether energy drinks make people more chatty’
- Hypothesis is a clear, precise, testable statement that states the relationship between the variables to be
investigated. Stated at the beginning of any study
- For example, ‘Drinking an energy drink causes people to become more talkative’
- Directional hypothesis states clearly the direction of the difference or relationship
- For example, ‘People who drink energy drinks become more talkative that people who do not’
- Non-directional hypothesis does not state the direction of the difference or relationship
- They suggest the variables differ but they do not say how
- For example, ‘Those who drink energy drinks differ in terms of talkativeness than those who do not’
- When there has been research previously done on your topic then you would use a directional hypothesis
- If there has been no research done before on the topic you would use a non directional hypothesis
- Now we need to choose a method (experimental method) to test our hypothesis
- Experimental methods involve the manipulation of an independent variable (IV) to measure the effect on
the dependent variable (DV). Experiments may be laboratory, field, natural or quasi
- Dependant variable is the one you measure and the independent variable is the one you change
- Variables are any 'thing' that can vary or change within an investigation. Variables are generally used in
experiments to determine if changes in one thing result in changes to another
- Independent variable (IV) is some aspect of the experimental situation that is manipulated by the
researcher - or changes naturally-so the effect on the DV can be measured.
- Dependent variable (DV) is the variable that is measured by the researcher. Any effect on the DV should
be caused by the change in the IV
- Any other variables that could affect the DV should be controlled to ensure that only the IV is causing a
change to the DV
- To test the effect of the IV we need different experimental conditions. The two possibilities are:
- (1) Compare the participant before and after (How many words they can say in 5 minutes with the energy
drinks and after some time how many words can they say without the energy drink)
- (2) Or we could split the participants into two groups and keep one as a control to compare (one
group would drink the energy drink and be tested whereas the other would drink water and then be
tested)
- There should always be a control condition and an experimental condition…
- (1) When they do not have the energy drink they act as the control condition
- (2) When they are tested after they drink the energy drink they act as the experimental condition
- (1) The group that will drink water will be the control condition
- (2) The other group that drink the energy drink is the experimental condition
- Operationalisation is clearly defining variables in terms of how they can be measured
- This is to make sure that everything is measured accurately and more specific
- For example, ‘After drinking 300ml of energy drink, participants will say more words in the next 5 minutes
than those drinking 300ml of water’
- We can concentrate on how we are going to measure more accurately
, Research issues
- When completing an experiment the IV should be the only thing influencing the DV
- Any other variables affecting the DV are known as extraneous variables
- Extraneous variable (EV) is any variable, other than the independent variable (IV), that may affect the
dependent variable (DV) if it is not controlled. EVs are essentially nuisance variables that do not vary
systematically with the IV so they can be controlled (age can be controlled)
- Confounding variables is a kind of EV that varies systematically with the IV. Therefore we can't tell if any
change in the DV is due to the IV or the confounding variable (Harder to control)
- Demand characteristics is any cue from the researcher or from the research situation that may be
interpreted by participants as revealing the purpose of an investigation. This may lead to a participant
changing their behaviour within the research situation
- An investigator during an experiment may also encourage a particular outcome
- For example, if the group who had the energy drinks are chatty the investigator may smile at them which
encourages them to say more - This is known as investigator effects
- Investigator effect is any effect of the investigator's behaviour (conscious or unconscious) on the research
outcome (the DV). This may include everything from the design of the study to the selection of, and
interaction with, participants during the research process
- Randomisation is a method that can be used to minimise effects of extraneous/confounding variables
- Randomisation is the use of chance methods to control the effects of bias when designing materials and
deciding the order of experimental conditions
- All participants should be in the same environment and receive the same information for the experiment
- To achieve this the experiment can be standardised
- Standardisation is using exactly the same formalised procedures and instructions for all participants in a
research study
Experimental designs
- Experimental design is the different ways in which participants can be organised in relation to the
experimental conditions - There are 3 ways to do this:
- Independent groups design is when the participants are allocated to different groups where each group
represents one experimental condition eg controlled or experimental condition
- Random allocation is an attempt to control participant variables in an independent groups design which
ensures that each participant has the same chance of being in one condition as any other.
- P: One limitation of independent groups is the way in which the two groups are separated.
- E: For example, they may not be the same in terms of participant variables - Some participants may be
chattier than others in the experiment.
- E: If a researcher finds a mean difference between the groups on the dependent variable (DV) this may be
more to do with participant variables than the effects of the IV.
- L: These differences may act as a confounding variable reducing the validity of the findings. (This can also
be avoid this using random allocations)
- P: Another limitation of independent groups is they are less economical than repeated measures.
- E: For example, each participant contributes a single result only when they are divided into two groups.
- E: Twice as many participants would be needed to produce equivalent data collected in a repeated
measures design.
- L: This in turn increases the time and money spent on recruiting participants.
,- P: One strength of independent groups is that order effects may not be a problem.
- E: For example, because the participants are divided into two groups they are less likely to figure out the
aims of the study.
- E: This means that they won’t be able to reply to demand characteristics.
- L: This increases the validity in the research by using this method.
- Repeated measures is when all participants take part in all conditions of the experiment - they might be
used as the control group first and then after as an experimental group
- Counterbalancing is an attempt to control the effects of order in a repeated measures design: half the
participants experience the conditions in one order, and the other half in the opposite order.
- In the energy drink example there would be two groups one group will have water first and then they will
have the energy drink
- Participant variable is the characteristic of the participant that can affect the results - a participant could
be more or less chatty so it’s best to get them to complete both tasks
- P: One limitation of repeated measures is order effects can arise.
- E: For example, repeating two tasks causes boredom/fatigue that might cause deterioration in
performance on the second task, so it matters what order the tasks are in.
- E: Alternatively, participants' performance may improve through practice, especially on a skill
based task.
- L: Therefore the order the study takes place in can act as a confounding variable.
- P: One limitation of repeated measures is that each participant has to do at least two tasks and the order
of these tasks could affect the results of the study. (Order effects)
- E: For instance, one task can have a continuing effect on the later task - In the energy drink example,
having the energy drink first may have a continuing effect when a participant drinks water afterwards.
(This can be prevented by counterbalancing)
- E: It is also more likely that participants will work out the aim of the study when they experience all
conditions of the experiment.
- L: This can cause them to react to demand characteristics making the results invalid.
- P: One strength of repeated measures is participant variables are controlled
- E: For example, all participants are taking part in each condition. (In the energy drink example we don’t
have the chattiest person in one group and the less talkative in the other)
- E: This means that a more valid comparison can be made between the two groups' abilities in the task.
We are using the same participants twice so we yield more results than we would if the groups were
divided.
- L: This leads to more accurate results as well as less time and money required for recruiting the
participants.
- Matched pairs design is when pairs of participants are first matched on some variable(s) that may affect
the dependent variable. Then one member of the pair is assigned to Condition A and the other to
Condition B - For example, we might observe the two most chattiest people and then split them into two
different groups
- P: One strength is participants take part in a single condition.
- E: For example, if their study is controlled well then the participants may not know the aims. This prevents
them from reacting to demand characteristics and also reduces order effects.
- E: This means that you would get the same results possibly as independent groups however they are more
likely to be accurate.
- L: Therefore this can be seen as a better method than independent groups and repeated measures.
, - P: One limitation is that the participant variables can’t always be controlled.
- E: Participants will never be matched exactly even in the case of identical twins.
- E: Matching also takes time and can be expensive.
- L: This means it might not be worth it as the results could be inaccurate and more expensive to achieve.
Types of experiment
- Laboratory (lab) experiment is an experiment that takes place in a controlled environment within which
the researcher manipulates the IV and records the effect on the DV, whilst maintaining strict control of
extraneous variables.
- P: One strength of lab experiments is high control over confounding and extraneous variables.
- E: For example, any distractions the participant may come to face can be disregarded.
- E: This means that we can be more certain of cause and effect in the research.
- L: This gives the experiment a high degree of internal validity.
- P: Another strength is that replications are possible because of the high levels of control.
- E: Replication in a study is important so that we can conclude the results first time was not just a one off.
- E: Because we are conducting the study in a lab new extraneous variables are not introduced.
- L: This means we can compare the results of the study more confidently (improves reliability)
- P: One limitation of lab experiments is that they may lack generalisability.
- E: The lab environment may be rather artificial and not like everyday life.
- E: In an unfamiliar context participants may behave in unusual ways so their behaviour cannot always be
generalised beyond the research setting. (low external validity)
- L: This means that the result may not reflect the study but is distorted due to demand characteristics.
- Field experiment is an experiment that takes place in a natural setting within which the researcher
manipulates the IV and records the effect on the DV.
- P: One strength of field experiments is that they have higher mundane realism than lab experiments.
- E: For example, if the participants can’t identify what the procedure is about they are less likely to reply to
demand characteristics. (not just given them a list of words to read out)
- E: This means that the results are more likely to be valid and authentic.
- L: This gives the experiment a high degree of internal validity.
- P: One limitation of field experiments is although it increases realism it now has a loss of control in
confounding and extraneous variables.
- E: There may be distractions within the experiment that could influence how to participant reacts to the
dependent variable.
- E: This means cause and effect between the IV and the DV in field studies may be much more difficult to
establish and precise replication is often not possible.
- L: This can lead to invalid results as well as an invasion of privacy.
- Natural experiment is an experiment where the change in the IV is not brought about by the researcher
but would have happened even if the researcher had not been there. The researcher records the effect on
a DV they have decided on.
- P: One strength of natural experiments is that it provides opportunities for research.
- E: Some research may not be taken due to practical or ethical reasons e.g. the Romanian orphans.
- E: The study looks into real world issues and problems as they happen.
- L: This gives the experiment a high external validity.
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