Strengths and Weaknesses of Component 1 PDF

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Evaluation of research methods...

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Strengths and Weaknesses of Component 1

Snowball Sampling

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Strengths Quick and easy Feasible Using readily available participants Quick and easy More practicals Often low costs Can reach people hard-to-reach Low costs Could be the only way

Random Sampling

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Representative of population Eliminates sampling bias Generalisable

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Strengths Strict control Replicable Eliminates extraneous variables Standardised instructions Reliable High ecological validity No demand characteristics

Opportunity Sampling Self-Selected Sampling

Laboratory Experiment

Field Experiment Quasi Experiment

Independent Measures Design Repeated Measures Design Matched Pairs Design

Quantitative Data

Qualitative Data

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Enables researcher to look at things not practical or ethical High ecological validity

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Strengths Order effects eliminated Less demand characteristics

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More economical Participant variables constant Cheaper and need less participants Less order effects Less demand characteristics Can control participant variables Less extraneous variables

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Strengths Easy to use for comparisons Can quantify behaviour Easy to replicate Standardised Highly reliable Objective as no interpretation Lots of detail High validity

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Weaknesses Could be biased Not representative Can only use those available Could be biased Not representative May not get enough people Could be biased Unlikely to know about population Secondary motives for respondents Lack of control Hard to achieve accurately in practice Time consuming and expensive Need everyone’s name and might not want to be involved

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Weaknesses Low ecological validity Demand characteristics

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Less control over extraneous variables No right to withdraw Deception No informed consent Hard to control extraneous variables Hard to replicate

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Weaknesses Participant variables differ Extraneous variables More participants needed Less economical Order effects Demand characteristics

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Hard to match participants Less economical

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Weaknesses Doesn’t give reasons for results Low validity May give false impressions No context in numbers Limited usefulness

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Hard to compare and summarise Less reliable

Structured Observation

Unstructured Observation

Naturalistic Observation

Controlled Observation

Participant Observation Non-Participant Observation Covert Observation Overt Observation

Time Sampling Event Sampling

Questionnaires

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Easy to interpret Can be useful

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Strengths Can be planned using pilot test Reliable Inter-rater reliability Can re-analyse using video data Not limited by pre-set categories Can record more information

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High ecological validity Not aware of being observed Are good for observations where interventions are unethical Data likely to be reliable Controlled extraneous variables High validity Can explore lots of behaviours Can see people’s real emotions Aware of observer

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Accurate and detailed records Observers remain objective

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Unaware of being observed Accurate and detailed records

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Ethical observations High reliability Not limited by categories

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Strengths Can indicate the event order Shows time spent on each behaviour Reliable Records occurrence Can record every occurrence Easy to obtain and analyse results

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Strengths Quick and easy Quantitative and qualitative data Cost-effective Results easy to compare Standardised Replicable Generalizable Representative High level of confidence

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Researcher bias when interpreting Subjective

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Weaknesses Simple definitions won’t be precise Low validity Limiting behaviour categories

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Could miss something All data collected may not be relevant Inconsistent Subjective recording Extraneous variables Low reliability Validity compromised if observers are identified or suspected Low ecological validity Aware they are in artificial situation Social situation is limited Not representative Observer would be subjective Ethical issues involved Know they are being observed Demand characteristics Ethical issues involved Low validity Change behaviour if aware of observer Validity can be compromised Ethical issues involved Hard for observers to record data without being notices Aware of observer so may not give genuine reactions Time consuming

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Weaknesses Hard to record all different behaviours Demand characteristics Timings must be precise which could be hard No indication of time spent on each category No indication of order of behaviours

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Weaknesses Lacks validity Participants could lie Could be rushed Questions could be misinterpreted Social desirability bias Cannot understand emotion No clue as to time spent on it Restricted answers Needs certain levels of maths/English

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Closed Questions

Open Questions

Rating Scales

Likert Scales

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Strengths Easy for participants to respond Quick way to get lots of data Reliable data Generalizable Produces quantitative data Easy to analyse Produces qualitative data Reliable data Detail in participant’s answers

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Easy for participants to respond More reliable Generalizable Quantitative data Test-retest reliability Valid with a large sample Easy to respond to More reliable Generalizable Quantitative data Test-retest reliability Valid with a large sample

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Specific information There is a neutral category so people don’t have to make a definite decision

Semantic Differentials

Structured Interviews Unstructured Interviews

SemiStructured Interviews

Correlations

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Strengths Relatively easy to analyse Quantitative data Easily repeated Can get specific information Can ask extra questions to confirm information Can gain in-depth information Can gain specific information Can ask extra questions to confirm information More detailed qualitative data Highly validity Strengths A correlational study can be conducted on variables that can be measured but not manipulated i.e. when experimentation would be

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Can’t guarantee responses

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Weaknesses No qualitative data Low validity Can only be used to calculate the mean

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No quantitative data Time consuming Subjective interpretation Low inter-rater reliability Observer bias Less generalizable No qualitative data Low validity Could have response bias Cannot measure complex variables

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No qualitative data Low validity Could have response bias Middle value shows no opinion Can be undecisive Value may not be the same for everyone Needs a certain level of intelligence Only appropriate for certain people Can be hard to understand Not everyone will have an opinion Value may not be the same for everyone

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Weaknesses Limited by fixed questions

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Harder to analyse Could be observer bias as responses need interpreting

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Could be observer bias Time consuming Hard to interpret

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Weaknesses A single correlational analysis cannot indicate whether a relationship is casual, so when a relationship is found this might be due to one of the

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impractical or unethical A correlation can demonstrate the presence or absence of a relationship so is useful for indicating areas for subsequent experimental research

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measured variables or alternatively another, unknown variable might be responsible Correlational analysis can be used only with variables that can be measured on a scale...