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What is a hypothesis?
A statement which clearly describes the relationship between variables as stated by the theory (e.g. drinking SevenUp soda causes people to become more talkative)
Directional hypothesis: researcher clearly states the difference anticipated between two conditions (include words like more, less, higher, faster, etc)
Non-directional hypothesis: states a difference between conditions but does not specify the nature of this difference
Operationalisation of variables
ensuring the variables are measurable as possible (e.g. adding units)
Example of an operationalised hypothesis: After drinking 300ml of SevenUp soda, participants will say more words in the next 5 minutes than participants who drink 300ml of water
Laboratory experiments
Laboratory experiments are conducted in highly controlled environments where the scientists manipulate the independent variable
Strength: have high control over extraneous variables so researchers can ensure that any effect of the dependent variable is most likely a result of manipulation of the IV, so lab experiments high internal validity as scientists can demonstrate cause and effect
Limitation: lack generalisability as the environment may not reflect everyday life, so in an unfamiliar context the participant may behave unusually, meaning experiment has low external validity as findings cannot be generalised beyond the controlled research setting. Participants might also exhibit demand characteristics due to awareness of being tested.
Field experiments
Field experiments take place in the participants' usual environment, but the researcher manipulates the IV
Strength: higher mundane realism as the environment is more natural or typical for the participant, so behaviour produced may be more valid, especially since participants are unaware of being studied so this means they have high external validity.
Limitation: induce ethical issues as participants are unaware of being studied, so they cannot provide consent and research might constitute as an invasion of privacy
Natural experiments
Natural experiments are when the researcher measures the effect of an IV on a DV but has no control over the IV, the research setting does not necessarily have to be natural (participants may be tested in a lab)
Strength: provide opportunities for research that could not otherwise be undertaken for practical/ethical reasons (e.g. Rutter's study of institutionalised Romanian adoptees) so have high external validity as they involve studying real-world issues
Limitation: Naturally occuring events may only happen rarely, reducing the opportunity for researching and limiting the scope for generalising findings to other similar situations
Quasi
Quasi experiments have an IV based on existing difference between people (e.g. age, gender) which simply exists and cannot be changed
Strength: happen in controlled conditions so can be replicated easier due to the high level of control, ensuring new extraneous variables are not introduced when repeating the experiment
Limitation: cannot randomly allocate participants to conditions so there may be extraneous variables which are unaccounted for
Extraneous variables
Any other variables (that are NOT the IV) which could potentially influence the DV
Usually identified at the start of the study, researcher tries to minimise their impact
Demand characteristics
Ps attempt to work out aim of experiment by interpreting cues
Behave how they think they will be expected to act based on experimental situation, either over-perform to please experimenter or under-perform to sabotage results of study
So ps behaviour not natural, demand characteristics = extraneous variable that may affect DV
Investigator effect
unwanted inlfuence of investigator on research outcome
Hugh Coolican (2006) points out can include unconscious cues (e.g. smiling more with certain ps) and expectancy effects
Leading questions
Randominsation
Using chance methods to minimise effect of extraneous variables (e.g. researcher’s unconscious biases) on outcome
E.g. in memory experiment where ps recall words from a list, words should be randomly generated
Standardisation
ensure ps subject to same environment, information, experience
list of exactly what will be done in study, e.g. standardised instructions read to ps
Control groups
Comparison group to determine whether IV had effect on DV
Both groups have differing IVs
Independent group design (experimental designs)
All ps experience one level of the IV (Group 1 experiences one IV, group 2 experiences a different IV)
Strength: order effects not problematic, ps less likely to guess aim of study
Limitation: Ps who occupy diff groups not same in terms of ps variables - if researcher finds a mean diff between groups on the DV, may be due to ps variables rather than effects of IV - this could be extraneous v which reduces validity of findings
Repeated measures design (experimental designs)
All ps experience both conditions of the experiment
Each participant experiences condition A, then they all later experience condition B
Mean results from both conditions compared to find differences
Strength: ps variables are controlled, therefore higher internal validity
Matched pairs design (experimental design)
Ps paired together on similar variables relevant to experiment (e.g. IQ)
Then one p from each pair allocated to a different experimental condition
Controls effect of ps variables
Strength: ps only partake in a single condition so order effects + demand characteristics less of a problem
Limitation: ps can never be matched exactly, some important differences which will affect DV
Random sample
Obtain a list of all members in target population, randomly assign each p a number
Use a lottery method (e.g. random number generator) to select ps in sample
Strength: potentially unbiased, extraneous variables potentially divided equally between groups, enhancing internal validity
Limitation: although probability suggests random sampling likely to produce more representative sample than methods like opportunity, random sample can still be unrepresentative, e.g. select many ps with the same characteristics
Systematic sample
Every nth member of a target population selected (e.g. every 3rd house on a street)
Sampling frame produced where list of target population is organised into
Sampling system nominated (e.g. every 3rd, 6th person etc) then researcher begins from a randomly determined point (reduces bias) then works through sampling frame until sample complete
Strength: Objective, once system for selection established researcher has no influence over who is chosen
Limitation: ps may refuse to take part, resulting in volunteer sample which would be biased
Stratified sample
Composition of sample reflects proportions of people in subgroups (strata) within target population
Identify the different strata that make up population, work out proportions needed for sample to be representative
Select ps that will compose each strata via random sampling
Strength: representative sample, accurately reflects composition of population so findings ca be generalised
Limitation: identified strata cannot reflect all different subgroups/strata of population, cannot completely represent target population
Opportunity sample
Selecting anyone who is nearby and available
Strength: Economical in time and money, does not require list of target population and no need to divide them into strata
Limitation: Ps all selected from same area so will have a certain demographic, reflecting a specific segment of population and not representative so findings cannot be generalised
Volunteer sample
Ps select themselves to be part of the sample
Researcher may advertise experiment, or ps may simply volunteer when researcher asks
Strength: Ps more engaged and motivated so cooperate more, less likely to drop out
Limitation: Volunteer bias, may attract a certain ‘profile’ of person who is curious + likely to please researcher + exhibit demand characteristics which affects generalisability of findings
Informed consent (ethical issues)
Make ps aware of research aims, procedures, rights (including right to withdraw)
So ps can make informed judgement without being coerced or feeling obliged
From researcher POV, informed consent might make study meaningless as ps behaviour will not be natural as they know aims of study
Deception (ethical issues)
Deliberately misleading or withholding information from ps during investigation
Ps not received adequate information when agreeing to take part have not given informed consent
Occasions where deception can be justified if does not cause ps undue distress
Protection from harm (ethical issues)
Ps should not be placed at more risk than in daily lives, protected from physical and psychological harm (e.g. being embarrassed or in undue stress)
Ps reminded that they have right to withdraw at any point in investigation
Privacy and confidentiality (ethical issues)
Ps have right to control personal information
Confidentiality should be protected (right to have any personal data protected)
BPS code of conduct (ways of dealing with ethical issues)
British Psychological Society ethical guidelines/code of ethics
Aim to ensure all ps respected and considered during every reserach phase
Implemented by ethics committees in research institutions who use a cost-benefit approach to see whether proposals are ethically acceptable
Dealing with informed consent (dealing with ethical issues)
Ps should be issued a consent letter/form to sign with relevant info which might affect decision to participate
Ps UNDER 16 require parental consent
Dealing with deception + protection from harm (dealing with ethical issues)
Ps should be fully debriefed after study
Made aware of investigation’s actual aims and details not supplied during study (e.g. existence of other groups or experimental conditions)
Ps informed of what data will be used for, given right to withdraw during study + withhold data, crucial if retrospective consent is a feature of the study
Dealing with privacy + confidentiality (dealing with ethical issues)
If personal details held, must be protected
If details held must maintain anonymity - researcher refers to. ps using numbers/initials
During briefing/debriefing, ps reminded that data will be protected and not shared with other researchers