Research Methods Flashcards
Scientific Process
Psychologists use the scientific process to test theories and discover facts about our behaviour
1 make an observation
2 ask a question
3 construct the hypothesis
4 test the hypothesis
5 analyse the results
6 draw a conclusion
Observation and Aim
If you have an observation, you need to make this into an aim
To do this, you can ask a question
This question then gives the basis of an for a piece of research
Hypothesis
After you have an aim, you need to write a hypothesis
A hypothesis is a precise, testable statement about what the researcher thinks/expects will happen
There are 2 different types of hypothesise that we need to write
Types of Hypothesis
H1 (experimental hypothesis) is a testable, predictive statement that says that something WILL happen
The H1 can be directional or non-directional
Directional is also known as a one-tailed hypothesis, is very precise and tells us exactly what the researcher thinks will happen
- contains words like ‘higher or lower’, ‘ moire or less’ and ‘bigger or smaller’
Non-directional is also known as a two-tailed hypothesis, predicts there will be some effect or difference but does not specify what effect or difference will be like
- contains words like ‘there will be a significant difference’
H0 (null hypothesis) says nothing will happen, there will be no significant difference between the two groups in the experiment
- should alway include ‘ any significant difference will be due to chance’
Variables
In an experiment, the researcher changes or manipulates the independent variable and measures the effect of this change on the dependent variable
In order test the effect of the IV, we need different groups to compare
These are known as the two levels of IV:
-Control Condition = the group that doesn’t experience the IV
-Experimental Condition = the group that does experience the IV
Operationalisation of Variables
To be able to test the hypothesis, you need to operationalise the variables
This means to define variables ion a form that can be easily measured and tested
This may be giving one of the variables a number value or a suggestion of how you can measure it to have comparable results
Unwanted Factors
The key to an experiment is that we are looking for a cause and effect relationship
- we want to see if this change in the IV can cause am effect on the DV
However….
Unwanted factors can potentially have an affect in. The IV,DV relationship, distorting the cause effect relationship and threatening the validity
Types of Unwanted Factors
Extraneous variables (EVs)
Confounding variables (CVs)
Demand characteristics
Investigator effect
Extraneous Variable
An extraneous variable is any variable other than the IV, that may affect the DV if we do not control for it
- they are ‘nuisance’ variables, unwanted and extra variables
- they do not vary systematically with IV
- e.g. EVs could affect the participants in either condition of the experiment
Types of EVs
EVs can be subdivided into participant and situational variables
Participant Variables refer to variables to do with the participant that could affect the DV
- eg personality, age, gender, motivation, intelligence and concentration
Situational Variables refer to variables to do with the environment that the research i9s conducted in that could affect the DV
- eg time of day, noise, instructions, weather and temperature
Dealing with EVs
In general, most EVs (both participant and situational) can be managed with a bit of good planning and thinking ahead about what EVs might be present in your research
- you may conduct a……
Pilot Study, which is small-scale of the actual investigation
- this will allow you to identify any potential EVs that you may not have thought of
- e.g the room you are doing the experiment in is noisy due to construction in the building, and in turn, you modify the design or procedure
- so, you may look at this and find a different place to hold the experiment
Dealing with Situational Variables
Situational variables are controlled by using…
Standardised Procedures!
- this means that all participants are subject to the same environment, information and experience (including the same instructions for the task)
- this controls the environment and ensures that all participants are tested under the same conditions (situations)
Dealing with Participant Variables
Use that same participants in both conditions:
- each group is the same participants so there are fewer variables and differences
- however they may get bored or figure out what is going on
Use different but matched participants in both conditions:
- each group has similar participants so there are fewer participant variables
Use different participants in each condition but randomly allocated participants to each condition:
- the random allocation should mean groups are roughly comparable due to laws of probability
Confounding Variables
Confounding Variables are variables that are not the IV but could end up being a second, unintended IV for some (not all) participants
- only one condition is impacted
E.g. during the experiment of talkativeness, one condition may be exposed to an extreme event which causes them to talk more
It is much harder to control CVs
- it is more likely that you would consider them in the discussion of your research once it has been carried out
Demand Characteristics
Most participants in an experiment will be spending time trying to make sense of what is going on and what the researcher is investigating
They may look for cues (clues) to help them interpret what is happening
- they may use the cues to second guess the researchers intentions and the aim of the research and base to determine how they behave
These cues are the demand characteristics
Presentation of Demand Characteristics
Demand characteristics can result in participants showing:
The Please You Effect
- they act in the way they think is expected
The Screw You Effect
- they deliberately under perform to sabotage the results of the study
- this is a smaller minority but still happens
Either way, participant behaviour is no longer natural and therefore not as valid
Dealing with Demand Characteristics
One way of dealing with demand characteristics is to use a single- blind procedure
- in high information will be kept from the particiapnty at the start of the study
- e.g. the aim of the research, its hypothesis, what the conditions of the study are, which condition they are in etc
This nis an attempt to ensure that any information that might create expectations in the participants are not revealed until the end
- it should be revealed at the end for ethical reasons
Investigator Effects
Investigator effects occur when a researcher unintentionally or unconsciously influences the outcome of research they are conducting
- e.g non-verbal communication in which the researcher communicates their feelings about what they are researching communicates their feeling about what they are observing without being aware they are doing it
- they may cruise an eyebrow showing they are surprised, and the participant may change their response
- e.g 2 bias in interpretation of data where the researcher interprets the data in a way that fits their expectations
- e.g 3 physical characteristics of the researcher such as appearance or gender, which might influence the behavioural response of the participant
- this is harder to control than other, so it will need to be kept in mind during research
Dealing with Investigator Effects
One way to deal with investigator effects is a double-blind procedure where neither the researcher who is carrying out the research and the participant knows the details of the experiment beyond what they need to know
Types of Experiments
- Laboratory
- Field
- Natural
- Quasi
Lab Experiments
Definition - the researcher deliberately manipulates the IV in a controlled environment allowing for control over the EVs
The effects of the IV on the DV are measured
Summary Checklist:
IV manipulated
Conducted in a controlled variable
EVs controlled for
Effects of IV on DV measured
Field Experiment
Definition - the independent variable is deliberately manipulated in a more natural setting (e.g the street, in school, at work) and participants are generally unaware that they are taking part in an experiment
The effects of the IV on the DV are measured
Natural Experiment
Definition - in a natural experiment, the IVs= is not changed by the researcher
Instead, the IV is naturally occurring and the researcher has no control over it
The researcher records the effect of the naturally occurring IV on the DV
Note 1 - the researcher is taking advantage of the natural change
Note 2 - ‘natural’ refers to the IV being natural, not the setting
- you can carry out natural experiments in controlled lab settings
Quasi Experiments
Definition - in a quasi experiment, the IV is based on an existing difference between people (e.g age or gender)
The IV is not manipulated, it simply exists
Note - as with a natural experiment, a quasi experiment can also be carried out in a controlled lab setting
Evaluating Experiments - Generalise
To apply from one situation or group of people to another
- we want to be able to do this so we have a point to the experiment
Evaluating Experiments - Validity
The extent to which the findings from the study are accurate/true
Internal validity - the extent to which the findings from the study actually measure what they claim to measure
- i.e is the experiment ‘true’ to what it is studying
- more control = more internal validity
External validity - they extent to which the findings of the study can be generalised (and are valid/accurate/true) outside of the original context in which the study was conducted
- do the results only show us how those specific participants behaved in that setting at that time
Ecological validity - are they true in the real world
Evaluating Experiments - Reliability
Consistency
Internal reliability - was the research consistent within itself
- e.g. did all the participants have the same experience
- more control the better
External reliability - if the research is repeated, are the results consistent over time?
Evaluating Experiments - Establishing cause and effect relationships n
Does x cause y?
More control = more sure you can be
Lab Strengths
- high control over EVs as the researcher can control the environment and research. It is therefore possible to establish a cause and effect relationship between the IV and the DV
- high reliability as they can be easily repeated due to the controlled conditions and so it is possible to check for consistent results
Lab Weaknesses
- high chance of demand characteristics as participants are aware they are being studied. Therefore they are likely to pick up on clues as to the nature of the research and may change their behaviour to help/hinder, meaning their behaviour is not natural
- low ecological validity as the environment is highly controlled and artificial. It is therefore difficult to generalise the findings to the behaviour in real life situations
Field Strengths
- high ecological validity as the experiment is carried out in a real life environment/setting and therefore it is possible to generalise the findings to real life behaviour
- less chance of demand characteristics ad participants may be unaware they are being studied. They are therefore unlikely to pick up on clued and their behaviour is more likely to be natural
Field Weaknesses
- difficult to establish cause and effect between the IV and the DV as the research is carried out in a real life/natural environment. There is therefore low control over EVs meaning these could be responsible for the effect on the DV
- lacks reliability as there is low control over the research meaning it is difficult to get the same circumstances to repeat the research and check for consistent results
Natural and Quasi Strengths
- high ecological validity as there is no artificial manipulation of the IV. It is therefore possible to generalise the findings to behaviour in real life
- allows researchers to study areas which would be unethical or impractical to manipulate e.g. comparing sighted to non-sighted children. Therefore valuable for studying certain behaviours
Natural and Quasi Weaknesses
- difficult to establish a cause and effect between the IV and the DV as the researcher deoesn’t have control over or directly manipulate the IV. Therefore there could be EVs responsible for the effect on the DV
- lacks reliability as there is low control over the research meaning it is difficultly to get the same circumstances to repeat the research and check for consistent results
Types of Experimental Design
- Independent Group Design
- Repeated Measured Design
- Matched Pairs Design
Experimental Design Defintion
The different ways in which participants are allocated to the different conditions (IV levels) in an experiment
- i.e. how we allocate participants to the experiment and control conditions in our experiment
Notes:
1. You only have an experimental design when you have an experiment (not in experimental research)
2. Don’t mix up ‘experimental design’ with ‘type of experiment’
Independent Group Design
- participants only take part in one condition
- they are randomly allocated to either the control condition OR the experimental condition
- also called independent measures design
Repeated Measures Design
- participant take part in both conditions
- they are in the control condition AND the experimental condition
Matched Pairs Design
- participants only take part in one condition
- however, before being allocated to EITHER the control condition OR the experimental, they are matched with another participant on key variables relevant to the experiment
- e.g. people with similar IQs may be placed in opposite group
Independent MD Strengths
- there will be no order effects - ppts only complete one condition so they will not become bored or get better (practise effect) - increases the internal validity
- less chance of demand characteristics - ppts take part in only one condition so they are less likely to work out then purpose of the study and change their behaviour to help or hinder - this increases the internal validity of the study
Independent MD Limitations
- indiviudal differences/participant variables i.e. the different characteristics of the participants such as age, gender may affect the results - lowers the internal validity
- requires more participants than as the researcher will need to get two separate groups of ppts to end up with the same amount of data
Repeated MD Strengths
- requires fewer participants as ppts take part in all conditions - meaning a potentially larger sample can be used - increasing external (Population) validity
- participant variables are removed e.g. IQ/Age as ppts take part in all conditions - increasing the internal validity
Repeated MD Weaknesses
- results may be affected by order effects - ppts may become bored by the second condition and so do less well or do better (practise effect) - lowers the internal validity
- increased chance of demand characteristics as when ppts do the second condition they may work put the purpose of the study and change their behaviour to help or hinder the experiment - lowers the internal validity
`Matched Pairs D Strengths
- controls for individual differences/participant variables - ppts are matched on characteristics such as age, IQ an d gender that may affect the results - increasing the internal validity
- there will be no order effects - ppts are only in one condition so they will not be more bored or get better (the practiser effect) - increases the internal validity
Matched Pairs D Weaknesses
- the most time consuming experimental design as the researcher needs to identify all important participant variables and spend time matching participants
- impossible to control all participant variables because only key ones can be matched for - there could be others which could effect the research - this lowers the internal validity
- requires more participants as the researcher will need to get two separate groups of ppts to end up with the same amount of data
Addressing Experimental Design Weaknesses
Some of the weaknesses of the experimental designs we can’t do anything about, such as how time consuming the nature of matched pairs
But there are ways we can deal with some of them, through techniques like random allocation and counterbalancing
Random Allocation
Used to reduce participant variables in independent measures designs
It works my reducing the impact of participant variables through random allocation
- the laws of probability suggests groups SHOULD end up reasonably comparable
- not necessarily going to work out like that
- can have an ‘accidental bias’ and groups end up very different, however that is statistically unlikely
Counterbalancing
Reduce order effects
Also known as the ABBA technique
- A stands for condition a (control)
- B stands for condition b (experimental)
Half of the group will do condition a followed by condition b
The other half will do condition b followed by condition b
This cancels out the order effects and balances them out
Sampling Introduction
When carrying out research, most psychologists have a target population
- a group of people that share a set of characteristics about which the researcher wishes to draw conclusions
In an ideal world, you would carry out research on everyone in your target population, but this isn’t actually possible
To solve this, you select a representative sample
- a group typical of the target population
You would then generalise your findings from the sample to the rest of the population
You can only generalise your findings if the sample is representative
Probability Sampling Methods
Every person in the target population has an equal chance of being selected
For this, we need a sampling frame
- a list of every one in the target population
The probability sampling methods are:
Random sampling
Systematic sampling
Stratified sampling
Random Sampling
Each person in a given population stands an equal chance of being selected
This means it is necessary to have the names of every person in the target population
The sample could then be selected by drawing names out of a hair or by entering all the names into a computer random generator and clicking ‘select’ the number of times for participants needed
Systematic Sampling
The researcher first randomly picks the first participant from the population
They will then select each n’th participant from the list (also a randomly generated number)
- e.g. person 3 is randomly selected as the first participant and the n’th is 10
- that means person 13, 23, 33, 43, 53 and so on until enough participants have been selected
Random and Systematic Strengths
A random and systematic sample is potentially unbiased
- as everyone in the target population has an equal chance of being selected, the laws of probability would suggest that the sample should be overall representative of the target population
There is also a reduced researcher bias
- as is is the selection technique itself that selects the participants rather than the researcher themselves, this means that the researcher is not selecting only participants only - they bare objective sampling techniques
Random and Systematic Weaknesses
You may still end up with a biased band unrepresentative sample
- there is always the possibility of accidental bias
- while random and systematic sampling is more likely to produce a representative sample, it is not guaranteed
These sampling techniques can be difficult and time-consuming
- for example, a complete list of the target population scan be difficult to obtain
- selected participants may refuse to take part
Stratified Sampling
It involves dividing the target population into important sub-categories (called strata) and randomly selecting participants within each sub-category in proportion that they occur in the population
- e.g. if 40% of the target population is male and 60% is female, then the sample needs to reflect these proportions
Stratified Sampling Strengths
A stratified sample is going to provide us with the most representative sample
- this is because there is a proportional representation of subgroups
There is also a reduced researcher bias
- as it is the selection technique itself that selects the participants rather than the researcher themselves, this means that the researcher is not selecting certain participants only
- this is another objective sampling technique
Stratified Sampling Limitations
Stratified time sampling is very time consuming
- this is because you have to identify important subcategories, work out the proportions and then you have to select the participants in those proportions
- you also need a sampling frame that can be very hard and time consuming to obtain
It will still not provide your with a fully representative sample
- even though it will provide you with the most representative sample compared to all of the sampling techniques, it is still likely that there will be some bias because you can’t know what each important subgroup and some will inevitably be left out
Opportunity Sampling
It involves the researcher selecting anyone who is available at this time
This means it doesn’t require a sampling frame
For example, the researcher uses anyone who is around at the time of their study e.g. in the street
Opportunity Sampling Strengths
It is appropriate to use when the sampling frame is unknown
- for example, if you want to do a field experiment in a high street, you wouldn’t have a sample frame
An opportunity sample is a confident method of gaining participants because:
- it is less costly than random, systematic and stratified sampling because you do not need to source a complete list of your target population
- it is less time consuming than stratified sampling because you do not need to identify subgroups and work out proportions
Opportunity Sampling Limitations
Opportunity sampling is likely to result in a biased sample (an unrepresentative sample) because:
1 - not everyone in your target population will be present when you do your study
- e.g. if you got to a high street at 10am on a Monday, large groups will be issuing, such as people at work or school
2 - you approach p-eople who you want to take part which will inevitably lead to researcher bias
- they are more likely to select people that they believe will fit in with their hypothesis
- this is usually done unconsciously
Volunteer Sampling
Participants select themselves
This means you do not need a sampling frame
For example, in response to an advertisement in a newspaper or a poster
Volunteer Sampling Strengths
A volunteer sample is a convenient method of gaining participants
- this is because you just put the advert up and let people come to you
It is a useful way to locate willing participants
- this means that participants are less likely to drop out of the research
It can be seen as a more ethical sampling technique
- you are surer that you have consent from participants as they behave volunteered
- this is compared to something like random sampling where participants may6 feel obliged to take part because they were selected
Volunteer Sampling Limitations
Volunteer sampling is likely to result in a biased sample
- it is prone to volunteer bias as it may be that certain types of people are likely to volunteer
- e.g. those with the time/specific interest to the area of the study
Volunteer sampling may be more likely to result in demand characteristics
- this is because the participants are so interested in the study, they are thinking really hard about the aim might be
What are Ethics?
“Concerns with what is deemed acceptable human behaviour, with what is good or bad, right or wrong with human conduct in pursuit of goals or aims”
- penguin dictionary of psychology 1985
What are Ethical Issues?
Ethical issues occur when their is conflict between what the researcher need to do to conduct a useful and meaningful research and the rights of the participants
For example, a researcher might not tell the participants the aim of the research to avoid demand characteristic, but is it acceptable to leave the participants in the dark?
Informative Consent
Ensuring that the prospective participants in the study know what they are getting themselves into before they get into it. It involves making participants aware of the aims of the research, the procedures, their rights (including the right to withdraw partway through the study should’ve they wish to) and what their data will be used for
From the researcher’s point of view, asking for this may make the study meaningless as participant’s behaviour will not be ‘natrual’ as they know the aims of the study
From a participant’s point of view, they should be able to make an informed judgement about whether or not to take part without being coerced of feeling obliged
Deception
This involves deliberately misleading or withholding information from participants at any stage in the investigation
From a researcher’s point of view, there will be times where deliberately misleading or withholding information about the study is necessary
From a participant’s point of view, lying is wrong. Not only does it prevent them from giving full valid consent, it can also lead to them to see psychologists as untrustworthy, which might mean they are less likely to take part in psychological research in the future
Protection from Harm
Participants should be protected psychologically (e.g. stress, humiliation or anxiety) and physically (pain). They must not be placed at more risk than they would be in every day life
From the researcher’s point of view, studying some of the more important questions in psychology may involve a degree of risk or harm (psychological or physical) to participants. It can be hard to predict what this harm might include, so it is difficult to guarantee protection from any risk of harm
From a participant’s point of view, nothing should happen to them during a study that causes harm and they should leave the study in the same state as they ere before hand
Privacy
This refers to the right participants have to control information about themselves. This extends to the area that the study took place.
From a researcher’s point of view, it may be difficult to avoid invading this when studying participants without their awareness, like asking about personal thoughts and opinions in a field experiment
From a participant’s point of view, they do not expect to be observed by others in certain situations, like in their home, nor do they expect to be forced into revealing information about themselves that they do not wish to share
Confidentiality
This refers to our right, enshrined in law under the General Data Protection Regulation, to have any personal data protected and kept anonymous
From the researcher’s point of view, it may be difficult to protect this because they may wish to publish the findings. Even if the researcher can guarantee anonymity, by withholding the names of participants ect, it may still be obvious who has been involved in the study, like if has been filmed or if it is a very specific group of participants
From a participant’s point of view, this is a legal right and it is only acceptable for personal data to be recorded if it is not available in any format that identifies the participants
Dealing with Ethics - Informed Consent
Participants should be issued with a consent form that details all relevant information that might affect their decision to participate
If they agree to this, they need to sign a form
If children under the age of 16 are required for the investigation, they need parental consent too
However, using a consent form for informed consent might cause issues because not many people actually read terms and conditions
What should be in a Consent Form?
- thank the participants
- the aim of the research (if you are withholding the aim you may not include this - in this case you will be gaining consent but it won’t be valid)
- an outline of the procedure and how much of their time it will take
- explain the ethical issues which have been accounted for, especially the right to withdraw (who they should speak to if the feel uncomfortable or want to withdraw) and confidentiality
Remind them they can ask questions
Include space where they can sign and date to show they consent (this is essential, it is your record that valid consent was sought)
Other forms of Consent
There are alternative ways of getting consent to over come getting consent to overcome the problem that getting people to sign a consent form might make the study meaningless if they know the aim
Presumptive Consent
Rather than getting consent from the participants themselves, a similar group of people are asked if the study is acceptable
If this group agrees, then consent of the original group is presumed
This might be a problem though because everyone has different ethics and morals
The group asked might not have gone through a certain traumatic event that someone in the other group has - everyone has different triggers
Prior General Consent
Participants give their permission to take part in a number of different studies, including one that will involve deception
By consenting, participants are effectively consenting to be deceived
However, they may have consented to an experiment that had minor levels of deceit, whereas the actual study might have very high levels of deception
Consent should be given every time
Participants may be expecting deception, which could lead to demand characteristics
Retrospective Consent
Participants are asked for their consent after the study, during the debrief
They may not have been aware of their participation or they may have been subject to deception
However, they might not have been happy with being lied to
They also might not have taken part if they knew the real aim
What should happen at the end of a study to ensure deception is avoided?
where possible, deception should be avoided completely
At the end of the study, participants should be given a full debrief
This should involve:
Making the participants aware of the true aims of the study and any details they were not supplied with/deceived about
In addition, the debrief should also tell participants what their data will be sued for and give them the right to withhold their data if they so wish
Dealing with Protection from Harm
Research should be planned to ensure participants are not exposed to any more harm than they would be exposed to in everyday life
If harm is inevitable participants should be made aware of this from the start of the research
The participants should be reminded they have the right to withdraw from the investigation at any point
In the debrief, they should be reminded that their behaviour is normal
In extreme cases, counselling may be needed after the investigation, which the researcher should provide access to
Dealing with Privacy
Research should be planned to ensure participants are not being studied in locations in which they could reasonably expect privacy
- e.g. their homes, changing rooms, shops, public toilets etc
Participants should be reminded they have the right to withdraw from the investigation at any time
Dealing with Confidentiality
Researches should maintain anonymity in their research
- this means recoding no personal details that could potentially indentify the participants
- e.g. name, location
- you should refer to participants using numbers or initials when writing up the investigation
Participants should be reminded of the fact that their data will be preceded throughout the process and told that identifying information will not be shared to others
The British Psychological Society
The BPS have published the ‘Code of Human Research Ethics’
These tell psychologists which behaviours are acceptable and give guidance on how to deal withy certain ethical issues that may arise in research
Psychologists are to consider these ethical issues when planning and conducting research
The BPS regularly updates its guidelines:
1st edition - 1978
3rd edition - 2017
If these guidelines are not followed they can be punished by the BPS can decide to ban the person from practising as a psychologist
- expelled from the BPS
- however it is not a legal issue
The BPS are based on the 4 main principals as:
- respect
- competence
- responsibility
- integrity
Ethics Committees
Nowadays, before any type of research can take place, there must be an ethics document submitted to an ethics committee for approval
What are they? - set up in research institutions to assess the cost-benefit analysis of research proposals
Who is on them? - members of the committee include experts and lay people
How do they manage risk of ethical issues? - request that the researcher changes the study’s design or procedure, or in some cases deny approval for the study
What are the benefits of them? - a second check on ethical issues (and BPS guidelines), ensure rights are met and involve individuals who represent the participants (the lay people, aka non psychologists)
Observations in Research
non-experimental research
An experiment is not always the most suitable way of stuffing human behaviour
There are a number of non-experimental research methods available to psychologists
- i.e. research methods that do not have an IV
One important non-experimental research methods are observations
An observation involves watching a participant. And recording behaviour for later analysis
General Strengths and Weakness of Observations
Regardless of the type of observation we might use, all observations have the following general strengths and weaknesses:
S - they capture what’s people actually do
- what people say vs do is actually very different
W - Thor is the possibility of observer bias
- our interpretation of what we can see can be influenced by our expectations
W - you cannot establish cause and effect with observations
Naturalistic Observations
Naturalistic observations involve watching and recording of spontaneously occurring behaviour in the participant’s own natural environment
- there is no interference by the observer
- they avoid intrusion
For example, Anderson, in the 70s, was interested how far young children would run from their parents in a park, before they returned to them (max 15ft)
Controlled Observations
Controlled observations involve the watching and recoding of behaviour within a structured environment in which the conditions are manipulated by the researcher
For example, Ainsworth and the strange situation used to discover the quality of attachment between a child and their caregiver
Naturalistic Observations Strength
Naturalistic observations have higher external validity because they record real behaviour in a natural environment
Controlled Observations Weakness
Controlled observations have lower external validity because they observe behaviour in a highly manipulated setting, and so there is no guarantee that they would behave like this in the real world
Controlled Observations Strength
Controlled observations are very replicable as the situation is very controlled, so the experiment can be easy easily replicated to prove the reliability of the data
It allows you to check for consistency and outliers
Naturalistic Observations Weakness
Naturalistic observations are not very replicable as they are naturally occurring events, so the environment is very hard to be repeated to prove the reliability and consistency of the data
You can’t control the real world
Covert Observations
Covert observations involve watching and recoding of behaviour without the knowledge or awareness of the participants and the observations is hidden from the participants
For example, you may observe a therapy session or police investigation behind a one-way mirror, under cover
Overt Observations
Overt observations involve watching and recording of behaviour with the knowledge or awareness of the participants and the observer is clearly visible to the participant
For example, a classroom observation from a higher up member of staff from the school
Overt Observations Weakness
Overt observations are more likely to produce demand characteristics as the person will want to behave desirably towards the observer, and therefore decrease internal validity as the behaviour isn’t true
Covert Observations Strength
Covert observations are less likely to produce demand characteristics as the person does not known they are being observed and can’t know to change their behaviour, increasing internal validity
Covert Observations Weakness
Covert observations are more likely to produce ethical issues as you do not know you are being watched, and therefore you cannot give consent. This may cause privacy issues too, as you may be being observed in a place you would expect privacy, such as a therapy session, which should also be confidential
Overt Observations Strength
Overt observations are loess likely to cause ethical issues as you know you are being watched and therefore you can give consent
Participant Observations
Participant observations involve the watching and recording of behaviour with the observer becoming a member of the group whose behaviour they are watching and recording
For example, someone joined in with a group of football hooligans
“On being sane in insane places’ - seeing how staff treat patients in psychiatric hospitals in the 70s
Non-Participant Observations
Non-participant observations involve the watching and recording of behaviour bewitch the observer remaining outside of the group whose behaviour they are watching and recording
For example, watching children in a play ground
