Research Methods Evaluations Flashcards
Experimental Design: Independent Groups
Participant variables are a problem (use random allocation to deal with this).
Less economical than repeated measures as more participants needed.
Order effects are not a problem.
Participants are less likely to guess the aim.
Experimental Design: Repeated Measures
Order effects are a problem (counterbalancing is used to deal with this).
Participant variables are not a problem.
Demand characteristics are more likely.
Experimental Design: Matched Pairs
Order effects and demand characteristics are less of a problem.
Participant variables are still a problem (but less so than independent groups).
Matching may be time-consuming and expensive so less economical than other designs.
Laboratory Experiments
Strengths: high control over extraneous variables, high internal validity, replication is more possible.
Weaknesses: May lack generalisability, artificial stimuli, low external validity, demand characteristics, low mundane realism.
Field Experiments
Strengths: higher mundane realism, less demand characteristics, high external validity.
Weaknesses: Loss of control of extraneous variables, cause and effect more difficult to establish, replication is more difficult, important ethical issues.
Natural Experiments
Strengths: high external validity, natural setting, provide opportunities for research that may not otherwise be undertaken for practical or ethical reasons, less chance of demand characteristics.
Weaknesses: Difficult to replicate, random allocation for independent groups is difficult, limited generalisability.
Quasi-Experiments
Strengths: often carried out under controlled conditions so share strengths of lab.
Weaknesses: cannot randomly allocate participants to conditions and therefore there may be confounding variables.
Random Sample
Strengths: free from researcher bias, more representative than some other sample methods.
Weaknesses: difficult and time consuming to conduct, sample may still be unrepresentative, selected participants may refuse to take part.
Systematic Sample
Strengths: avoids researcher bias and is usually fairly representative.
Stratified Sample
Strengths: avoids researcher bias, representative sample, generalisation of results is possible.
Weaknesses: complete representation of the target population is not possible.
Opportunity Sample
Strengths: convenient, more economical.
Weaknesses: researcher bias, unrepresentative of population, not generalisable.
Volunteer Sample
Strengths: easy, less time consuming.
Weaknesses: volunteer bias, unrepresentative of population.
Naturalistic Observations
Strengths: High external validity and so generalisable.
Weaknesses: Lack of control, replication is difficult, extraneous variables.
Controlled Observations
Strengths: extraneous variables are less of a factor, replication is easier.
Weaknesses: results may be less applicable to to real life settings.
Covert Observations
Strengths: No participant reactivity, behaviour is natural, increased validity.
Weaknesses: questionable ethics.
Overt Observations
Strengths: more ethical
Weaknesses: knowledge of being observed may affect their behaviour and so less valid.
Participant Observations
Strengths: researcher has increased insight, potential increased validity.
Weaknesses: researcher may lose objectivity and identify with participants.
Non Participant Observation
Strengths: Maintain objectivity.
Weaknesses: May lose valuable insight.
Observational Design: Structured Observations
Strengths: Recording of data is easier and more systematic, quantitative data and analysing and comparing is easier.
Weaknesses: Less richness and depth of detail.
Observational Design: Unstructured Observations
Strengths: More richness and depth of detail.
Weaknesses: Qualitative data harder to record and analyse, greater risk of observer bias, may only record behaviours that catch the eye.
Questionnaires
Strengths: Cost-effective, can gather large amounts of data, usually produce straightforward data that is easy to analyse and compare.
Weaknesses: social desirability bias, response bias, acquiescence bias.
Interviews: Structured
Strengths: straightforward to replicate, reduces interviewer differences.
Weaknesses: can’t deviate from topic or elaborate on points.
Interviews: Unstructured
Strengths: more flexibility, interviewer more likely to gain insight, interviewer can build rapport with participant.
Weaknesses: Analysis and comparison of data is more difficult, social desirability bias.
Peer Review
Strengths: anonymous so more honest appraisal, establishing validity and accuracy of research.
Weaknesses: anonymity can be used to criticise rivals, publication bias, process may suppress opposition to mainstream theories (burying ground breaking theories).
Qualitative Data
Strengths: more richness of detail, more license to develop their thoughts, feelings and opinions on a given subject, greater external validity, provides researcher with a more meaningful insight.
Weaknesses: difficult to analyse and compare, conclusions often rely on subjective interpretations which may be bias.
Quantitative Data
Strengths: easier to analyse and compare, more objective and less open to bias.
Weaknesses: less depth and richness of detail, may fail to represent real life.
Primary Data
Strengths: authentic data obtained from pps for purpose of the particular investigation.
Weaknesses: requires more time and effort.
Secondary Data
Strengths: inexpensive and quicker.
Weaknesses: may be variation in the quality and accuracy secondary data, may be outdated or incomplete, content may not match researchers needs or objectives.
Correlations
Strengths: provide precise and quantifiable measure of relation between variables, quick and economical to carry out.
Weaknesses: cannot establish cause and effect, third variable problem.
