key science skills Flashcards
beneficence
maximising benefits and minimising risks
integrity
conducting research in an honest way, and honestly reporting all information
non-maleficence
minimising harm as much as possible
justice
the research is done in a just way
respect
all living things have value
voluntary participation
participants freely choose to participate without any coercion or pressure
informed consent procedures
participants understand the nature and purpose of the experiment, including potential risks
-two parts: informed and consent
-in the case of children, must obtain informed consent of child (where possible) and their parent/guardian(s)
-withdrawal rights and right to confidentiality must be explained
withdrawal rights
participants are able to leave the experiment at any time during or after the experiment
confidentiality
the protection and privacy of participant information
use of deception
only allowed when knowing the true nature of the experiment will affect participant behaviour
debriefing
at the end of the experiment the participant leaves understanding the aim, results, and conclusion, and all questions are answered
ethical concepts
-beneficence
-integrity
-non-maleficence
-justice
-respect
BINJR
ethical guidelines
-voluntary participation
-informed consent procedures
-withdrawal rights
-confidentiality
-use of deception
-debriefing
sample
a group of research participants selected from a larger population of research interest
population
the entire group of research interest from which a sample is drawn
representative sample and how to make a sample representative?
a sample that closely matches the population
-recruiting a large sample
-using random or stratified sampling
random sampling
sampling which ensures that every member of the population of research interest has an equal chance of being selected to be apart of the sample
advantages and disadvantages of random sampling
advantages:
-reduces experimenter bias given how participants are selected
-helps to ensure that a representative sample is obtained
disadvantages:
-need to know everyone in the population
-doesn’t guarantee a representative sample (especially for small samples)
stratified sampling
involves dividing the population to be sampled into different sub-groups (strata), then selecting a separate sample from each subgroup (stratum) in the same proportions as they occur in the population interest
advantages and disadvantages of stratified sampling
advantages:
-more likely to obtain a representative sample compared to random sampling
-useful for comparisons between specific groups
disadvantages:
-need to know proportions within research population
-can be demanding on researcher to select the most appropriate strata
between subjects design
an experimental design in which individuals are divided into different groups and complete only one experimental condition
advantages and disadvantages of between subjects design
advantages:
-no order effects (unwanted effects of the order of a task/practice effect)
disadvantages:
-participant differences may interfere
-needs more participants than within subjects design
within subjects design
an experimental design in which participants complete every experimental condition
advantages and disadvantages of within subjects design
advantages
-fewer participants needed compared to between subjects design
-eliminates participant differences between groups
disadvantages:
-vulnerable to order effects (practice effect)
-participants are more likely to drop out
mixed design
-an experimental design which combines elements of within subjects and between subjects designs
-typically has a pre and post test (within subjects) and a main task (between subjects)
advantages and disadvantages of mixed design
advantages:
-enables experimenters to compare results both across experiment conditions and across participants over time
-allows multiple experimental conditions to be compared to a baseline control group
disadvantages:
-can be more time-consuming and less cost efficient
-harder to conduct
standard deviation
-the average deviation (or distance) of a set of scores from the mean
-the higher it is, the more widely spread the data is
case study
an intensive, in-depth investigation of some behaviour activity, event, or problem of interest in a single person, group, organisation, or situation
how are case studies different from experiments?
-they don’t measure cause and effect relationship between variables
-they involve investigating a single individual or group
advantages of case studies
-reduces artificiality compared to experiment
-enables things to be investigated that may be otherwise infeasible through an experiment
-can provide rich qualitative data
disadvantages of case studies
-no causation
-small sample size
-difficult to generalise
-time-consuming
-susceptible to bias
-may not be repeatable
correlation study
involves investigating whether a relationship exists between variables
direction of relationships in correlation studies
-positive: as one variable increases, so does the other (and vice versa)
-negative: as one variable decreases, the other increases (and vice versa)
-no correlation
advantages of correlation studies
-extra procedures to control for extraneous variables aren’t needed
-observation of real-life behaviours with no manipulation of variables may result in more natural behaviours
disadvantages of correlation studies
-correlation doesn’t equal or imply causation
-the relationship is bi-directional, and you can’t determine which variable has more influence
-large amounts of data required
-low internal validity - can’t determine whether there was influence of third variable
classification and identification
-classification: the arrangement of phenomena, objects, or events into manageable sets
-identification: a process of recognition of phenomena as belonging to particular sets or possibly being part of a new or unique set
advantages of classification and identification
-people identified as having a similar classification can feel a sense of belonging or support
-using classifications can allow for efficient processing of large amounts of info
disadvantages of classification and identification
-labelling through identification can lead to stereotyping, prejudice, or discrimination
-classifications may be based on subjective criteria
-large amounts of info are required to create classifications
fieldwork
based on inquiry or the investigation of an issue, fieldwork involves observing and interacting with a selected environment beyond the classroom, usually to determine correlation, rather than a casual relationship
advantages of fieldwork
-info on sensitive topics can be obtained using fieldwork
-participant anonymity in questionnaires can reduced biased or dishonest answers
-natural settings are more likely to show behaviours that reflect real life
-can be used when it would be impossible or unethical to use controlled experimental methods
disadvantages of fieldwork
-observed behaviour is subjective, open to interpretation and bias by researcher
-prone to desirability bias - participants respond in a way they think they should respond, particularly if the researcher is present
-interviews, focus groups, and yarning circles can be time consuming
-minimal control over extraneous variables, results may not be replicable
-ethical concerns with lack of informed consent in some cases
literature review
review of published research
advantages of literature review
-can determine what is already known and whether there is a solid foundation of knowledge, based on multiple sources
-they identify gaps in current understanding and areas for future research
disadvantages of literature review
-a selection bias in chosen studies may result in the review being unrepresentative of current understanding or provide unbalanced conclusions
-only secondary data acquired
modelling
involves the construction and/or manipulation of either a physical model, or a conceptual model that represents a system involving concepts that help people know, simulate, or understand the system
advantages of modelling
-allows unobservable events to be visualised
-can test a product before it is created
disadvantages of modelling
-large amount of valid source data may be need to creation of model
-complex models can be expensive
product, process, or system development
design or evaluation of an artefact, process, or system to meet a human need, which may involve technological applications in addition to scientific knowledge and procedures
simulation
a process of using a model to study the behaviour of real or theoretical systems
advantages of simulation
-can allow use to predict future events and what if situations
-can test a product before it is created
disadvantages of simulation
-not the real thing - people may respond differently in real life, therefore simulations involve assumptions about behaviour that lowers external validity because of artificiality
-complex simulations can be expensive
systematic errors
-affects accuracy
-causes readings to differ from the true value by a consistent amount each time
-all readings are shifted in one direction from the true value
random errors
-affects precision
-present in all measurements except for those which involve counting
-unpredictable variations in the measurement process and results in a spread of readings
personal errors
includes mistakes, miscalculations, and observer errors when conducting research
uncertainty
-something that isn’t accurately or precisely known
-the uncertainty of the result of a measurement reflects the lack of exact knowledge of the value of the quantity being measured
accuracy
how close a measurement is to the true value of the quantity being measured
precision
how closely a set of measurement values agree with each other
extraneous variable
a variable other than the IV that can cause a change in the DV, therefore affecting the experiment in an unwanted way
confounding variable
a variable other than the IV which has had an unwanted effect on the DV
examples of extraneous variables
-participant variables
-situational variables
-demand characteristics
-experimenter effects
-placebo effects
participant variables
the personal characteristics that individual participants bring to an experiment which can influence their response - can be biological, psychological and/or social
eg age, sex, sleep patterns
control of participant variables
-ensuring participants in different experimental conditions are as similar as possible
-using a large sample
-using random allocation
-using the appropriate research design - within-subjects is generally most effective
situational variables
external variables (other than the IV) associated with the experimental setting that may influence participant responses, and therefore the responses
eg order effects
order effects and examples
-when the results of the DV is influenced by the specific order in which the experimental tasks are presented rather than the IV
practice effect: the influence on performance (the DV) that arises from repeating and/or prior experience with a task, including the test materials, procedures and settings
carryover effect: the influences that a particular task has on performance in a task that follows it. They arise simply from experiencing a task.
control of situational variables
-keep situational variables constant
-counterbalancing: systematically changing the order of tasks for participants to reduce/avoid the unwanted effects on performance of any one order
demand variables
cues in an experiment that may influence a participant’s response, which affects the results, eg guessing the hypothesis and changing their responses to support the hypothesis
control of demand variables
-use deception
-single-blind procedure: the participants are unaware of whether they are in the experimental or control group, and therefore unaware whether they have been exposed to the IV. This avoids issues with participant expectations, as all participants equally feel like they are receiving a treatment.
-double-blind procedure: both the participants and the experimenter are
unaware of which is the experimental and which is the control group. This avoid issues with participant expectations and the experimenter effect.
experimenter effect
this can occur if the experimenter is biased because they know which group is receiving is receiving the treatment and which isn’t
control of experimenter effects
-blind procedures
-standardised Instructions and procedure
placebo effect
an improvement in health or wellbeing due to the belief that the treatment given will be effective
how are placebos used?
given to control group, so any behaviours should occur in both groups
validity
the extent to which a measure accurately measures what it is supposed to be measuring
-related to accuracy
internal validity
the extent to which an investigation actually investigated what it set out to investigate
external validity
the extent to which the results obtained for a study can be applied beyond the sample that generated them
reliability
the extent to which a measure produces results that are consistent, dependable, and stable
-reproducibility and repeatability
repeatability
the degree to which a specific research investigation obtains similar results when it is conducted again under the same conditions on all occasions
reproducibility
how close the results are to each other when an investigation is replicated under changed conditions
