This covers the entire content of Research Methods for A Level Psychology, which covers both first year and second year, these notes helped me achieve a B in my exams and will be useful for you.
Research Methods (Mainly Paper 2 + Across all 3 Papers)
Aims, Hypotheses and Variables
- Aim = a generic statement about what the researcher intends to
study.
- Hypothesis = a specific, restable statement that references the
operationalised variables being investigated.
Types of hypothesis:
1. Directional states there will be a differences between two
results and predicts the differences.
2. Non-Directional states there will be a differences between
the results but not what the difference will be.
Variables in Experiments:
- Dependant variable (DV) = is the factor that’s being measured in
the study to assess the effect of the independent variable. Will
always be quantitative data e.g. numbers.
- Independent variable (IV) = is the factor that’s changed to see its
effect on the dependent variable.
- Extraneous variables (EV) = unwanted variables that may affect
the result situational, experimenter and participant.
- Situational variables = an external influence which impact a child
or a young person’s life.
- Experimenter variables = an extraneous variable which occurs
when researchers unintentionally influence how participants should
behave e.g. age, gender.
- Participant variables = are personal variables which occurs when
a participants feelings or character traits affect the experiment e.g.
mood.
- Operationalising variable = is the process of defining variables
into measurable factors. Variables must be operationalised; this
allows for manipulation of the IV and means the DV can be
precisely measured. If variables aren’t measured properly, results
become unreliable and cant be replicated, which affects the
validity.
Demand Characteristics and Investigator Effects:
- Demand characteristics cues that may indicate the aim of the
study to the participants.
, - Investigator Effects occurs when a researcher unintentionally or
unconsciously influences the outcome of the research they are
conducting.
Experimental Method – Types of Experiments
Laboratory Experiment:
- Researcher has high levels of control over all the variables in the
experiment. Researcher is able to control environmental factors
e.g. noise and temperature as well as the experiences of the
participant and ensure participants have the same instructions.
The procedure will be standardised to allow for this control.
EVALUATION:
- Strengths = use of standardised procedures means research is
replicable which increases the reliability. Cause and effect
conclusions are more possible than other methods due to the
researchers control.
- Weakness = Lacks ecological validity due to the artificial nature of
the procedures. Demand characteristics as participants know that
they are in a study, this may alter the behaviour which impairs
validity of the study.
Field Experiment:
- is conducted in a naturalistic setting e.g. a school, the researcher
has less control. The IV is manipulated by the researcher but not in
the lab setting. The DV is measured quantitatively as in laboratory
experiments.
- Strengths = high ecological validity as it is a real-life setting. High
levels of mundane realism means results are more likely to be
generalised to real-world behaviours.
- Weakness = it’s hard to control the extraneous variables within the
experiment and this could change the measurements of the DV. It
is hard to randomly assign participants – likely a change could
happen due to participant variable.
Natural Experiment:
- Researcher doesn’t manipulate the IV to measure the outcome.
The IV will change to its own accord naturally. The researcher then
, measures the natural change in the DV. Variables that could affect
the DV aren’t measured or controlled.
EVALUATION:
- Strengths = there is high external validity as its conducted in a
natural setting with natural behaviours. It allows for research in
areas that controlled experiments couldn’t conduct research.
- Weakness = lack of reliability – unlikely to be able to replicate the
same situation again to test. It’s difficult to say there is a cause-
and-effect relationship as too many variables are unable to be
controlled and this could affect the outcome.
Experimental Design
Independent Measures Design:
- uses different participants for each condition.
EVALUATION:
- Strength = avoids order effects as participants are in only one
condition.
- Weakness = errors occur due to individual differences – controlled
by being randomly assigned to groups.
Repeated Measure Design:
- same participants take part in each condition of the experiment.
EVALUATION:
- Strengths = participant variables are reduced as all the same
participants are used in one condition and fewer people are
needed which saves time.
- Weakness = order effects – participants performance in the
second condition may be better/worse can be controlled using
counterbalancing.
Matched Pairs Design:
- participants are paired based on specific characteristics or
variables then divided into different conditions.
EVALUATION:
- Strengths = avoids order effects so counterbalancing isn’t needed
and reduces participant variables.
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