Research methods Flashcards
(239 cards)
Independent variable- definition and example
-This is the variable that is manipulated by the
researcher.
- Participants consume either
0.5 units or 2 units of alcohol.
Dependent variable - definition and example
This is the variable that is measured.
Reaction time in a driving simulator is measured
Extraneous variable definition and example
A variable (other than the IV) that might affect your DV.
These are identified (as much as possible) at the start of the study and controlled for.
If they are not controlled for they can become confounding variables.
Room temperature, time of
day, task given.
For example if some participants used the driving simulator in the morning and others in the afternoon, this could be a factor that influences concentration and reaction time
Confounding variable definition and example
type of extraneous variable that you did not control for that does interact with the IV and affect the DV (it becomes a further unintended IV).
We do not want these confounding variables to affect the DV, as we are interested in the affect the IV has on the DV.
Therefore, researchers try to control (stop) the confounding variables as much as they can.
Number of years driving experience.
This is likely to influence reaction time, with people with more driving experience anticipating hazards and reacting more quickly.
What must we do to variables
Operationalisation of variables:
This refers to how the variables are made measurable. It is not enough to use vague terms, as this makes replication (somebody else repeating your experiment) difficult.
Therefore operationalisation refers to drawing out the most relevant elements of the variables so we can measure them.
For example, intelligence is a very broad term. To make it measurable we could use a specific intelligence test that measures certain elements of personality.
Memory is also a broad term, this could refer to what you can remember from the day before, the week before or your whole life. To make this measurable the researcher could give participants a list of 20 words to remember and count how many were successfully remembered
Name 2 types of extraneous/confounding vraiables
- Demand characteristics
- Investigator effects
Demand characteristics- describe, and say how you could reduce effects
-The tendency of participants to use cues in an experiment to work out how the experimenter expects
them to behave, thus participants behave in an experiment in the way they think the researcher wants
them to behave.
- This change in behaviour can be conscious or unconscious and can refer to other changes in behaviour
such as nerves or purposely trying to sabotage the results. If participants’ behaviour is not natural in
the study, this can be a confounding variable, giving you inaccurate results and subsequently reducing internal validity.
How to reduce demand characteristics:
• Use different participants in each condition (independent groups) so that they are not exposed
to each condition of the IV and do not have the opportunity to guess the aims of the research.
• Single-blind technique where the participant does not know which condition of the experiment
(control or experimental) they are assigned to
Investigator effects- describe and say how you could reduce effects
- The researcher should try to remain objective throughout the research and to avoid influencing the outcome of the research in any way. If the experimenter does exert an influence (be it conscious or
unconscious) then they are introducing investigator effects.
• Coolican (2006) - Expectation effects can occur where a researcher is deeply committed to achieving a
particular outcome. This may be a problem when observing events that can be interpreted in more
than one way (e.g. children fighting or rough and tumble play?!).
• In naturalistic observational studies, the presence of the observer can cause participants to behave in ways that are different from their normal behaviour – for example, participant’s behaviour may be more restrained or exuberant than usual.
• When research is carried out using questionnaire surveys or interviews, then many
different aspects of the investigator may have an influence, including the investigator’s age,
gender, ethnic group, appearance, facial expressions and communication style. The
way in which an investigator asks a question may lead a participant to give the answer the
investigator ‘wants’. Alternatively, the way the investigator responds to a participant may
encourage some participants more than others. Research has found that males are more pleasant,
friendly and encouraging with female participants than with other male participants (Rosenthal,
1966).
If the investigator is influencing the results somehow, then this means the results are not a true
reflection of behaviour and can reduce internal validity.
How to reduce investigator effects:
• To use a double-blind technique
where neither the researcher nor the participants know the aims and/or conditions of the study. This also helps to reduce demand characteristics.
Name 2 types of controll
- Random allocation and counterbalancing
- Randomisation and standardisation
Describe random allocation, give example
This is used in an independent groups design in an attempt to
control for participant variables. The aim is that each participant has the same chance of being allocated to either condition of the IV. For example – You can put
all of the participants’ names into a hat and every other name drawn is in condition A.
Describe counterbalancing, give example
This is used in a repeated measures design and it splits participants so that
they complete the different levels of the IV in a different order. The aim is to balance out any
differences between participants results that are due to the order they have taken the test, i.e. it
controls the impact of order effects and distributes them evenly across both conditions
For example- A researcher was investigating whether women are better at reading without or with glasses. The researcher got the participants to complete a reading
test without wearing glasses and then repeat the test with glasses; they found that participants did better in the second condition (with).
- counterbalanced by half of PPs reading with glasses first and thee other half reading without first
Describe randomisation, give example
Randomisation involves adopting a strategy for randomly determining the order of presentation of
experimental conditions by, for example drawing lots or tossing a coin.
Randomisation can also be used as a technique for deciding the order of presentation of, for example, individual stimuli within a condition.
For example:
suppose an investigation involves each participant rating 20 photographs for their
attractiveness. If all participants experience the same presentation order, then some rating biases might occur. E.g. the photo presented first is likely to
be given an average rating by many participants, simply because they are rating this photo in an average manner because they feel they may wish to use more extreme
ratings in either direction for subsequent photos
Describe standardisation, give example
This means that all participants in a study have exactly the same experience, so that individual experience does not cause some participants to engage with the study differently.
The procedure therefore needs to be standardised to ensure all participants share the same experience- means non-standardised changes in procedure don’t act as confounding variables.
For example, having written instructions so all participants
receive the same information and any error in interpretation will affect all participants in all conditions.
Name 4 types of experiment
- laboratory
- field
- natural
- Quasi
Laboratory experiments- describe
3 Key factors:
Direct manipulation of an independent variable (IV):
The experimenter manipulates the IV and measures the DV, both need to be operationalised
Control:
The experimenter has high levels of control and aims to control extraneous/confounding
variables meaning that the only difference between the two conditions is the IV. A control group also acts as a control, here there is no manipulation of the IV and the DV is measured, this allows a baseline measurement for comparison. High levels of control allow for cause and effect to be established between the IV and the DV.
Randomisation:
In a true experiment, participants are randomly allocated to conditions, for example
by tossing a coin or by choosing names from a hat. This is to reduce any extraneous variables
associated with the participants from affecting the DV. Other factors are randomised, such as the
order stimuli are presented to participants and the order the participants take part. Counterbalancing also uses randomisation
Laboratory experiments- strengths
A strength of using laboratory experiments are that the procedure can be easily replicated. :
-This is because of the high levels of control in laboratory experiments
-for example the clear
operationalisation of the IV and DV, the control of extraneous variables and the standardisation of materials.
- This is a strength as replication allows experiments to check for reliability and whether the results are consistent.
A further strength is the internal validity is high in laboratory experiments:
- This is because it is far easier to control potential confounding variables in the laboratory than in any other setting or with any other research method.
-This means that we can be sure that the only factor affecting the
DV is the IV.
- This is a strength as it increases the ability to
establish cause (IV) and effect (DV) between the variables being measured.
Laboratory experiments- weaknesses
Ecological validity- bad due to controll:
- high levels of control, with
specified narrowly defined operationalised IVs and DVs are likely to become artificial and
therefore recognisably different from real-life situations.
- lack generalisability- low external validity
- This is a weakness because it questions the accuracy of the results and their ability to measure the complexity of human behaviour, the emotions and motives behind our actions
Demand characteristics:
- These are particularly an issue in laboratory research as participants know they are being researched and may feel even more inclined to
act in a way they think is required. - - After all, these participants have actively given up their time to participate in the research.
- This is an issue as if participants are showing demand characteristics, the measurement of
the DV is not a true reflection of behaviour and this reduces the internal validity of the
findings as we cannot be sure we measured what we set out to measure.
Mundane realism:
- tasks may not represent everyday experience- e.g. recalling random lists of words in memory experiment
Field experiments- describe
• Field experiments are experimental investigations carried out in the natural environment, e.g. in homes, schools or on the street. They attempt to improve the realism of the research.
▪ They are used in situations where it is considered particularly important for research to take
account of the natural environment.
▪ The researcher still manipulates the independent variable and measures the dependent
variable. The researcher also attempts to control extraneous variables as much as possible.
▪ Cause (IV) and effect (DV) can be established and participants are usually unaware that they are participating in an experiment
Field experiments- strengths
Better ecological validity than labs:
take place in the natural environment- behaviour more likely to be representative of behaviour outside of experiment
- strength as can be more confident when generalising to situations outside experiment
Demand characteristics lower:
- PPs don’t now they’re taking part in research
- means they can’t guess researchers aims or amend behaviour during research
- strength as increases the internal validity of the results- can be more confident that DV has measured what it set out to measure
Better mundane realism:
- tasks realistic as in real world
Field experiments limitations
Time-consuming:
- e.g. may only be small number of people around at certain times or may not be practical to set the experiment up the amount of times necessary
- issue as it may lead to less PPS being gathered, or may mean you only get PPs who go to the area where research is happening
- reduces population validity- hard to generalise to outside of population used
Hard to get full control over extraneous variables:
- natural environment- hard to predict everything that may occur and put controls in place
- may be uncontrolled extraneous variables impact on IV and affecting DV
- reduces confidence establishing cause and effect- reducing internal validity
- also makes replication an issue
Ethics:
- PPs not aware they’re being studied
- cant consent to being studied- research may constitute invasion of privacy
Describe natural experiments
▪ Natural experiments take advantage of naturally occurring events which create a change, over which the researcher has no direct control over the IV. The researcher
makes use of naturally occurring differences in the independent variable.
▪ This means the participants are already assigned to a condition of the IV, for example if you
were researching the impact of the smoking ban and comparing smoking levels before and
after. Here the IV would have occurred/made the change even if the research was not taking
place – it is natural. Thus, participants are not randomly assigned to conditions.
▪ Sometimes due to ethical and practical reasons, this is the only experiment suitable
- may still happen in labs- it is the IV that is natural
- DV may also be natural- e.g. exam results
Strengths of natural expeiments
High ecological validity:
- This is because they take place in the natural surroundings of participants, meaning that the
behaviour measured is likely to be representative of behaviour outside of the experiment.
- This is a strength as it means we can be more confident generalising the results to situations other than the experiment.
- high external validity as involves study of real world issues and problems as they happen e.g. effects of natural disaster on stress levels
Low demand characteristics:
- This is because in a natural experiment the participants do not know they are taking part in
the research.
- This means they are not able to guess the researcher’s aims, nor will they amend their behaviour during the research.
- This is a strength as it increases the internal validity of the results, as we can be more confident
that our DV has measured what it set out to measure.
Allows study of things not otherwise ethical/practical:
- e.g. Rutters Romanian Orphan study
Limitations of natural experiments
Low chances of desired behaviour being displayed:
As the researcher has no control over the situation, they are unable to ensure the participants behaviour on the DV is shown as the naturally occurring situation that the researcher wishes to study may occur only rarely.
- This is a weakness as it reduces the available opportunities for researchers to replicate the
research to test for reliability.
Low control of extraneous variables:
- As it is a natural environment, it is not possible for the experimenter to predict everything that may
occur and put controls in place. As such, it is a weakness as means there may be uncontrolled extraneous variables that are impacting on the IV and affecting the DV.
- This reduces confidence when establishing cause and effect, reducing internal validity
- if using independent groups, the PPs may nit be randomly allocated- may be less sure whether IV affected DV- e.g. in Rutters ERA study, IV was whether adopted early or late, but this was caused by other factors like social scores which then affected DV
Limitations of natural experiments
Low chances of desired behaviour being displayed:
As the researcher has no control over the situation, they are unable to ensure the participants behaviour on the DV is shown as the naturally occurring situation that the researcher wishes to study may occur only rarely.
- This is a weakness as it reduces the available opportunities for researchers to replicate the
research to test for reliability.
Low control of extraneous variables:
- As it is a natural environment, it is not possible for the experimenter to predict everything that may
occur and put controls in place. As such, it is a weakness as means there may be uncontrolled extraneous variables that are impacting on the IV and affecting the DV.
- This reduces confidence when establishing cause and effect, reducing internal validity
- if using independent groups, the PPs may nit be randomly allocated- may be less sure whether IV affected DV- e.g. in Rutters ERA study, IV was whether adopted early or late, but this was caused by other factors like social scores which then affected DV