Summary AQA Psychology for A Level Year 1 & AS Student Book, ISBN: 9781912820429 Research Methods - Year 1
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Research Methods - Year 1
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AQA
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AQA Psychology for A Level Year 1 & AS - Student Book
A succinct and complete summary of the Year 1 Research Methods topic of AQA A-level Psychology (including model answer 12 marker). Using only this material alongside my Year 2 - Research Methods summary revision notes when revising for the Research Methods section of Paper 2 I was able to achieve a...
Research Methods Revision Notes (Yr 1)
Experiment method
Hypothesis and Aims
Aim and hypothesis
- The aim states the purpose of the study: “To investigate the effect of X on Y.”
- The hypothesis states what is going to be tested, and the expected outcome
Two types of hypothesis:
- Directional - stating increase / decrease (one-tailed test), “The IV will cause the DV to increase”
- Non directional - difference (two-tailed test), “The IV will have significant effect on the DV”
Deciding which type of hypothesis to use
- Researchers tend to use a directional hypothesis when a theory or the findings of previous
research studies suggest a particular outcome.
- When there is no theory or previous research, or findings from earlier studies are contradictory,
researchers instead decide to pursue a non-directional hypothesis
Independent and dependent variables
Independent variable (IV) - what the researcher changes or manipulates
Dependent variable (DV) - the variable measured by the researcher
All other variables that might potentially affect the DV should remain constant
Operationalisation of variable
- Variables must be operationalised in the hypothesis in order to make it testable
- Not operationalised hypothesis - The group that drinks an energy drink will be chattier than the
group that drinks water
- Operationalised hypothesis - After drinking 300 ml of SpeedUp, participants say more words in the
next five minutes than participants who drink 300ml of water.
So, 3 conditions for a hypothesis
- Operationalise variables
- Clearly state the two conditions
- State the expected relationship or difference between two variables
,Research issues
Extraneous variables: nuisance variables which may interfere with the experiment.
In an experiment we want to see how the change in the IV affects the DV. We don’t want anything else to change
the DV.
Any other unwanted variables are called EXTRANEOUS variables. They should be identified at the start and
controlled to minimise their influence.
Examples:
● Age of participants, Lighting, Noise in the background & Difficulty of the words/nonsense words
These variables might make it harder to detect a result - but they don’t confound the findings of the study.
Types of extraneous variable
Participant variables - to do with differences between the participants
Situational variables - features of the experimental situation
Confounding variables
Confounding variables change systematically with the IV i.e. variables that interfere with the effect of the IV - you
could explain the results of the study (change in the DV) with a factor other than the IV.
E.g. if all the people in the music condition:
● Happen to have better memories
● If the words in this condition are easier than the other
If these people were spread evenly between the 2 conditions, it wouldn’t be an issue, but if they only affect the
music condition they become a confounding variable because the results could be explained by something other
than the effect of the IV.
Demand characteristics:
- Any cue from researchers or from the research situation that may be interpreted by participants as
revealing the purpose of an investigation. This may lead to a participants change their behaviour within
the research situation.
Participants may act in a way that they think is expected and over perform to please the experimenter (the
‘please U effect’), or, they may deliberately under perform to sabotage the results of the study (the ‘screw U
effect’).
Either way, participants' behaviour is no longer natural.
Example - Demand characteristics
- Participants are told that the study is about how people learn.
- They are given a list of words to learn in a set time period.
- Most of them realise that they are going to be tested on these words, and so assume that the study is on
memory.
- They know that this will result in a test score, and so want to do well as they are concerned about
appearing less intelligent than other people.
- This affects how they apply themselves to learning the words.
Investigator effects:
- Any unwanted influence of the investigator on the outcome
- Includes expectancy effects, unconscious cues, experimental design e.g. selection of participants, the
materials, the instructions, etc.
For example:
- Choosing particular types of participants to take part in particular conditions (biased sample)
- Acting differently with different participants - e.g. unconsciously encouraging those ‘expected’ to perform
better in a particular condition to help support the hypothesis
- Biased interpretation of data
Randomisation
- The use of chance methods to reduce the researcher’s unconscious biases when designing an
investigation. In short, an attempt to control the investigator effect.
For example:
- A memory experiment may involve participants recalling words from a list. The order of the list should be
randomly generated so that the position of each word is not decided by the researcher.
Standardisation: Giving all participants the exact same environment, information and experience. For example,
standardised instructions are read to each participant. Such standardisation means that non standardised
changes produced do not act as extraneous variables.
, Experimental designs
Experimental design - how participants are arranged in relation to the different experimental
conditions
Independent group
- Recruit a group of participants and divide them into two groups
- One group does the experimental task with the IV set for condition 1 and the other group does
the experimental task with the IV set for condition 2
- Measure the DV for each group
- Then compare the results for the two groups
Problems:
Participant variables - The natural variation between the individuals in each group may affect the DV
measurements, making it look as if the IV has had an effect when it actually hasn’t (confounding
variable).
Control:
Random allocation - After the Participants have been recruited, they should be randomly assigned to
their groups. This should ensure the groups are similar, on average.
Strength:
No order effect
Repeated measures
- Recruit a group of participants but instead of dividing the group this whole group does both
conditions. The scores from both conditions are then compared.
Problems:
Order effects - Doing both conditions may (1) give participants practice on the task; (2) make them
bored or tired; (3) allow them to work out the aim of the study (more demand characteristics), all of
which might affect the DV measurement. (4) Reuse of stimuli is not possible.
Control:
Counterbalancing - Divide the participants into two groups. Half does condition A first, then condition
B. The rest do condition B then condition A. DV measurement for the conditions A and B are then
compared.
Strength:
No participant variables
Matched participants
- Recruit a group of participants
- Find what sorts of people you have in the group and then recruit another group that matches
them one for one/Match the participants in your group depending on a relevant characteristic
- Then one participant from each pair would be allocated to a different condition of the
experiment
- After this you treat the experiment as an independent group.
Problems:
Several problems: (1) time consuming and expensive, particularly if a pre test is required; (2) an exact
match is rarely possible; (3) if one participant drops out you lose 2 participants' data.
Control:
Members of each pair should be randomly assigned to conditions. However, this does not solve all
these problems.
Strengths:
No order effect and little participant variables.
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