experimental design Flashcards

1
Q

independent groups design

A

participants only perform one condition of the independent variable

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2
Q

independent strengths

A

no order effects presented

participants are less likely to guess the aims of the study - demand characteristics eliminated

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3
Q

independent limitations

A

no control over participant variables
- different abilities of participants in the various conditions can cause changes to the DV

may need more participants than other designs

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4
Q

independent solution

A

random allocation - solved lack of control - ensures that each participant has the same chance of being in one condition of IV as another

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5
Q

repeated measures

A

the same participants take place in all conditions of the IV

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6
Q

repeated measures strengths

A

eliminates participant variables

fewer participants needed, so not as time consuming finding and using them

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7
Q

repeated measures limitation

A

order effects presented - boredom, fatigue - second condition - participant does not do as well on task

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8
Q

repeated measures solution

A

counterbalancing - half of participants do conditions in one order and other half in opposite order

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9
Q

matched pairs

A

pairs of participants are first matched on some variable that has been found to affect the dependent variable then one member of each pair does one condition and the other does another

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10
Q

matched pairs strength

A

no order effects

demand characteristics less of a problem

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11
Q

matched pairs limitation

A

time consuming and expensive to match participants

large pool of potential participants is needed which can be hard to get

difficult to know which variables are appropriate for the participants to be matched

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12
Q

pilot study

A

small-scale version of an investigation which is done before the real investigation is undertaken - allow potential problems of the study to be identified and the procedure to be modified to deal with these

  • allows money and time to be saved in the long run.
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13
Q

single-blind procedure

A

a researcher method - researcher do not tell the participants they are being given a test treatment or a control treatment - avoids demand characteristics

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14
Q

double-blind procedure

A

neither the participants not the experimenter knows who is receiving particular treatment - prevent bias

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15
Q

naturalistic observation

A

watching and recording behaviour in the setting where it would normally take place

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16
Q

naturalistic strengths

A

high ecological validity

high external validity as done in a natural environment

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17
Q

naturalistic limitations

A

low ecological if participants become aware they are being watch

replications difficult

uncontrolled confounding and extraneous variables are presented

18
Q

controlled observation

A

watching and recording behaviour in a structured environment

eg lab setting

19
Q

controlled obv strengths

A
  • researcher is able to focus on a particular aspect of behaviour
  • more control over extraneous and confounding variables
  • easy replication
20
Q

controlled obv limitations

A

more likely to be observing unnatural behaviour as takes place in an unnatural environment

low mundane realism so low ecological validity

demand characteristics presented

21
Q

overt

A

participants are watched and their behaviour is recorded with them knowing they are being watched

22
Q

overt strengths

A

ethnically acceptable as informed consent is given

23
Q

overt limitations

A

more likely to be recording unnatural behaviour as participants know they are being watched

demand characteristics likely which reduces validity of findings

24
Q

covert

A

the participants are unaware that their behaviour is being watched and recorded

25
covert strengths
natural behaviour recorded hence high internal validity of results removed problem of participant reactivity whereby participants try to make sense of the situation they are in - less likely to guess the aim
26
covert limitation
ethical issues presented as no informed consent given could also be invading the privacy of participants
27
participant observation
the researcher who is observing is part of the group that is being observed
28
participant strength
can be more insightful which increases the validity of the findings
29
participant limitation
possibility that behaviour may change if the participants were to find out they are being watched researcher may lose objectivity as may start to identify too strongly with the participants
30
non-participant observation
the researcher observes from a distance so is not part of the group being observed from a distance is not part of the group being observed
31
non-participant strength
researcher can be more objective as less likely to identify with participants
32
non-participant limitation
open to observer bias for example of stereotypes the observer is aware of researcher may lose some valuable insight
33
unstructured observation
consists of continuous recording where researcher writes everything they see
34
unstructured obv strength
more richness and depth of detail
35
unstructured obv limitations
produces qualitative data is more difficult to record and analyse greater risk of observer bias
36
structured obv
researcher quantifies what they are observing using predetermined list of behaviours and sampling methods
37
structured obv strengths
easier as is more systematic quantitative data is collected which is easy to analyse and compare with other data less risk of observer bias
38
structured obv limitations
not much depth of detail difficult to achieve high inter observer reliability as filling predetermined lists in is subjective
39
time sampling
recording of behaviour within a timeframe that is pre-established before study - reduces number of observations so less time consuming - small data within frame so unrepresentative
40
event sampling
involves the counting of the number of times a particular behaviour is carried out - good for infrequent behaviours that are likely to be missed if time sampling used - complex behaviour, important details may be overlooked - if very frequent then counting errors