Research methods Flashcards
what is a lab experiment?
- when the independent variable is manipulated directly by the researcher in a controlled environment.
- as the setting is controlled it allows the procedure to be kept the same for all participants which means participants are less likely to be influenced by variables other than the IV, such as EVs
strengths of a lab experiment
- good control of EVs
- strict procedures can be replicated, so researchers can be more confident in there findings as controls have been put in place.
- participants are aware they are in a study so have already given informed consent.
weaknesses of a lab experiment
- participants can conform to demand characteristic and might alter their behaviour
- an artificial situation could make participants unrepresentative
what is a field experiment?
- experiments conducted in a natural environment of the participants in which the independent variable is still manipulated by the experimenter.
- it’s procedures are harder to standardise as the environment is uncontrolled but the setting is more reflective of the participants everyday life.
strengths of a field experiment
- as participants are in their natural environment, their behaviour is likely to be representative
- participants are unaware they are in a study so demand characteristics are less problematic
weaknesses of a field experiment
- participants are unaware that they are in a study so have not given informed consent.
- control over EVs are much more difficult than in a lab so are less reliable and replication is more difficult.
- the researcher cannot be sure that changes in the DV have been caused by the IV.
what is a quasi experiment?
- may take place in lab settings or everyday settings but the IV is naturally occurring rather than manipulated by the experimenter.
strengths of a quasi experiment
- if the participants are in their normal situations, their behaviour is more likely to be representative.
- they can use this to study real world issues.
weaknesses of quasi experiments
- control over extraneous variables is often very difficult.
- they are generally hard to replicate.
what is a target population?
- a smaller group of people with specific characteristics taken from a wider group of people to receive a specific outcome when conducting a piece of research.
what is opportunity sampling?
- taking the sample from people who are available at the time of the study being carried out and meeting the criteria you are looking for.
strengths of opportunity sampling
- quick and convenient to obtain.
weaknesses of opportunity sampling
- could be biased as they will most likely pick people they like or people they know which usually will have something in common so is not representative.
what is random sampling?
- every member has an equal chance of getting chosen to participate in the study from establishing the target population and sample size then randomly choosing the participants.
strengths of random sampling
- the sample will be representative of the target population.,
weaknesses of random sampling
very difficult to obtain a random sample as researchers may not have all the details of the target population.
what is volunteer sampling?
- participants becoming part of a study because they volunteer when asked or responding to an advert.
strengths of volunteer sampling
- convenient and easy.
- can reach a a large number of participants.
- is ethical as all participants who volunteer have given some degree of consent.
weaknesses of volunteer sampling
- participants who volunteer may not be representative of the target population.
what is snowball sampling?
- you start with a small group of participants and get them to contact and find more participants, like a snowball would roll.
strengths of snowball sampling
- easy as you only need to find the first few participants.
weaknesses of snowball sampling
- can be non representative as participants are likely to be similar and with common characteristics to the other participants they gather.
what is independent measures design?
- using different participants for each condition when two or more conditions apply.
strengths of independent measures design
- quicker to carry put due to participants only experiencing one condition of the study.
- the same task can be used in the two different conditions and the other condition will be unaware.
- participants will be less likely to respond to demand characteristics.
weaknesses of independent measures design
- twice as many participants needed.
- participant variables may confound results.
- may be difficult to keep variables constant across conditions.
what is repeated measures design?
- the same group of participants taking place in each condition of the IV when the IV is manipulated.
strengths of repeated measures design
- participant variables will not confound results as the same participants are used for each condition.
- fewer participants are needed.
weaknesses of repeated measures design
- participants may be affected by order effects e.g. boredom, performing better or worse second time due to understanding, practice.
- more likely to have guessed the aim of the study by the second time of completing it so might display demand characteristics.
- cant use the same materials used for condition 1 and 2.
what is matched pairs design?
- participants are matched on a factor important within the study.
strengths of matched pairs design
- reduces the effect of some key participant variables.
- participants are less likely to guess the aim or portray demand characteristics.
- there will be no order effects occurring.
-the same task can be used in all conditions.
weaknesses of matched pairs design
- requires twice as many participants.
- it may be difficult to establish matches and the matching might take a long time.
what is the IV?
- variable which brings about change, this variable is manipulated by the researcher.
what is the DV?
- what occurs as a result of the manipulation of the IV. - the DV is what is measured or what counts as the results of the experiment.
what is the EV?
- variables that might effect the DV.
what are participant variables?
- personal variables concerning the participants in studies such as personality, age, health status, mood or intelligence.
- participant variables can confound the DV if they are not controlled.
what are situational variables?
- variables concerning aspects of the research situation such as noise, interruptions, temperature and room layout.
- these can confound the DV if uncontrolled.
what are demand characteristics?
- features of the study that encourage the participants to think and therefore behave in a certain way.
what are investigator effects?
when the investigator influences the participants performance or behaviour by them projecting their expectations about what will be found onto the participants.
-participants then behave accordingly and expected results tend to occur through may have reduced validity as a result of this confounding variable.
what are order effects?
- when participants participate in more then one condition and their performance is affected by the other in which they experience the conditions.
- this might change due to more understanding in the second condition or being more relaxed or more practiced made them better at the task.
controls of participant variables
- random allocation of participants to conditions.
- screening participants before they participate by asking questions.
- use the same participants in all conditions so they are being compared to themselves or use matched pairs.
controls of situations variables
- use a lab setting
controls of demand characteristics
- deceive participants about the aim.
- use distraction tactics to keep them naïve about the aim.
- use a field setting in which participants are unaware of the fact they are in a study.
controls of investigator effects
- use a third party who is unaware of the aim to test participants.
- ensure the researcher is unaware which condition the participants are in.
controls of order effects
- use different participants in each condition.
- use a time break between conditions.
- counterbalance so some participants do condition A then B and other participants do condition B then A.
what is a research aim?
- the aim tells us why the research takes place then becomes the basis of a specific prediction or hypothesis.
one tailed hypothesises
- predict the outcome of the experiment.
- example: participants who (condition A of the IV) will (refer to the DV and its expected direction of change) than participants who (condition B of the IV).
two tailed hypothesis
- state there will be a difference but don’t predict the outcome.
- example: there will be a significant difference in (the DV) between (condition A of the IV) and (condition B of the IV).
null hypothesis
- any difference found between two sets of data has not been caused by the IV , or that correlations or associations shown in data are not meaningful.
- example: there will be no significant difference (in the DV) between (condition A of the IV) and (condition B of the IV). any difference found will be due to chance.
naturalistic observation
- in the participants normal environment are recorded without interference from researchers in their social or physical environment.
controlled observation
- behaviours seen are recorded by the researchers in situations in which there has been some manipulation by the researchers.
- these may be conducted in the participants natural environment or in a lab.
structured observation
- when the observer records a non specified, wide range of behaviours including any that seem relevant.
non structured observation
- the observer sets a list of behavioural categories of which to tally against each time they observe a specific behaviour.
participant observation
- when the researcher is engaged with them as part of a social setting.
non participant observation
- when the researcher who is collecting data is not engaging with those observed as a part of a social setting.
overt observation
when the participants are aware they are being observed and the role of the observer is known to them.
covert observation
when the participants are unaware they are being observed.
strengths of a naturalistic observation
- high in ecological validity.
- useful when intervention is unethical.
weaknesses of a naturalistic observation
- lack of control over extraneous variables.
- may be difficult to ensure reliable data if data is not collected discreetly.
strengths of a controlled observation
high levels of control.
- able to observe behaviour as a direct result of manipulations.
weaknesses of a controlled observation
- low in ecological validity.
- may not represent complexities of real life social settings.
strengths of structured observations
- specific objectives for the observation.
- fully operationalised behavioural categories agreed between observers.
weaknesses of structured observations
- observation may be restricted by the specific behavioural categories.
- behavioural categories may be too simplistic.
strengths of non-structured observations
- allows the observer to record a range of different behaviours.
weaknesses of non-structured observations
- may record behaviours which aren’t relevant to the aims of the observation.
- attempting to record everything may lead to missing important aspects of behaviour.
strengths of an overt observation
- participants have consented to being overserved.
weaknesses of an overt observation
- participants may display traits of demand characteristics.
strengths of a covert observation
- participants are more likely to display their normal behaviours.
weaknesses of covert observations
- participants will not have given consent to being observed.
strengths of a participant observation
- more likely to observe natural behaviour and form an understanding of the context of the behaviour.
weaknesses of a participant observation
- may not have time or opportunity to record results.
strengths of non- participant observations
- able to accurately record behaviours.
weaknesses of non- participant observations
- participants may behave differently if they know they are being observed and observer may be unsure why they are acting this way with no context.
behavioural categories
- we may decide beforehand what specific behaviours we are looking for, which are then recorded when they occur.
coding frames
- makes recording of behaviour in a structured observation easier. it represents different behaviours as abbreviations or codes such as the first letter of the word.
what is time sampling?
- observing each participant exclusively for a specific amount of time them moving on to another participant and measure them for the same amount of time, and do that for the rest of the participants.
strengths of time sampling
- it can give an indication as to the order in which events occur.
- it can give an indication about the time spent on each behaviour.
weaknesses of time sampling
- time periods can sometimes be indicated by a sound such as a timer. if participants pick up on this, demand characteristic may occur.
- difficult to record as many behaviours in comparison to event sampling.
what is event sampling?
- observe all participants at one time, looking for when specific events occur and tallying when they occur.
strengths of event sampling
- it can record every occurrence of each behaviour.
- easy to analyse as just looking at totals for each behaviour category.
weaknesses of event sampling
- it can give an indication about the time spent on each behaviour.
- it doesn’t allow us to understand the order in which events from each behaviour category occur.
what is a questionnaire?
- respondents record their own answers.
- the questions are predetermined.
- when designing a questionnaire it is important to ensure the questions are without bias as if the respondent doesn’t understand the question they will give a meaningless answer which will make their results less valid.
strengths of a questionnaire
- can be easily repeated so that data can be collected from large numbers of people relatively quickly and cheaply.
- respondents may feel more willing to reveal private information in a questionnaire than in an interview.
weaknesses of a questionnaire
- response bias my occur as people might not give honest answers or might not give valid answers which will lead to invalid results.
- they don’t allow flexibility like an interview would as no questions can be added to clarify meanings of answers.
what is a structured interview?
- when all questions are predetermined and set.
strengths of a structured interview
- can be easily replicated.
- respondents can elaborate on their answers to give more detailed responses.
weaknesses of structured interviews
- the interviewers expectations may influence respondents answers.
- more difficult to analyse than questionnaires as respondents will give a range of different answers.
what is a semi structured interview?
- there are set questions but the interviewer can adapt and change questions to suit the respondent or to allow elaboration.
what is an unstructured interview?
- the interviewer will have themes they wish to cover but no set questions.
strengths of semi-structured and unstructured interviews
- lots of detail can eb gathered because the questions can be shaped to the participant.
-participants are able to clarify questions if they fail to understand what they are being asked.
weaknesses of semi-structured and unstructured interviews
- the interviewers expectations my influence the respondents answers.
-more difficult to analyse than questionnaires as participants my provide different responses.
what are open ended questions?
- questions which don’t provide the respondent with options, instead the respondent will have to come up with their own answers.
- usually these questions yield qualitative data.
strengths of open ended questions
- lots of in-depth detail and helps to establish why people have answered the way they have.
-valid because participants responses are not restricted.
weaknesses of open ended questions
- hard to analyse and compare as participant responses will vary.
what are closed questions?
- questions which restrict the responses that participants can give us.
- this is usually to collect quantitative level data.
strengths of closed questions
- easy to analyse and compare as participants responses will not vary.
weaknesses of closed questions
- no in-depth detail due to quantitative data collected and we cannot establish why people have answered the way they have.
- invalid because participants responses are restricted.
what is the Likert rating scale?
- allows participants to indicate how much they agree or disagree with a statement.
- participants respond by choosing an option typically ranging from ‘strongly agree’ to ‘strongly disagree’.
what are semantic differentials?
- measures participants attitudes towards something.
- the participants rate their responses between an opposing pair of descriptive words e.g. ‘weak’ and ‘strong’ and will place a cross between the two adjectives at the place they think matches their opinion best.
strengths of Likert scale and semantic differentials
- qualitative data is produced which is easy to analyse and interpret.
- they are easy for participants to respond allowing a degree of response to large amounts of data can be collected quickly.
weaknesses of Likert scale and semantic differentials
- they produce only qualitative data, which lacks detail, so participants cannot express opinions fully, lowering validity.
- there is a risk of response bias, such as consistently giving answers in the middle of the scale or one at one extreme end.
what is a positive correlation?
- as one co-variable increases or decreases, the other co-variable increases or decreases.
what is a negative correlation?
- as one co variable increases, the other one decreases so they change in different directions.
what is no correlation?
no relationship is found between the co-variables.
strengths of correlation research
- serves an effective starting point for more intensive research.
- can reveal the direction and strength of a relationship between co-variables.
weaknesses of correlation research
- can not reveal cause and effect relationships as the two co-variables may correlate but may not be casually linked.
- correlation analysis can only be used with variables that can be measured on a scale.
