Research Methods Flashcards
Types of Experiments
- Laboratory
- Field
- Natural
Field Experiment
Experimental methods
- An experiment that is carried out in a natural environment where the independant varibale is manipulated
- One strength is they’re often more reliable than lab experiment because they’re conducted in a natural environment, people don’t know their behaviours making their behaviours more natural, field experiments usually have good validity. In lab experiments, participants are usually aware that they are part of a study, which can lead to artificial behavior due to the controlled and unfamiliar setting. This setting enhances the ecological validity of the experiment, as it closely mirrors real-life situations. Because participants act as they normally would, researchers can gather more accurate data that reflects everyday behavior.
Natural Experiment
Experimental methods
- The change in the independent variable is not made by the researcher but are naturally occuring
- Natural experiments are valuable because they allow researchers to study real-world effects in situations where it’s impractical or impossible to manipulate variables. Unlike controlled experiments, where researchers actively intervene, natural experiments use naturally occurring events (e.g., policy changes, natural disasters) to observe their impact. This approach is especially useful when manipulation would be unethical or unfeasible. For example, studying the effects of smoking bans in different regions allows researchers to draw conclusions without directly controlling the behavior of participants. Thus, natural experiments provide important insights into causal relationships in real-life settings.
Laboratory Experiment
Experimental methods
- Sometimes referred to as a ‘true’ experiment. This type of experiment is carried out in a controlled environment where there is direct manipulation of an independent variable and random allocation of participants.
-The controlled environment of a laboratory experiment minimises the risk of other variables outside the researchers’ control skewing the results of the trial, making it more clear what (if any) the causal effects of a variable are. Because the environment is tightly controlled, any changes in outcome must be a result of a change in the variable.
What is included in observation techniques?
- Naturalistic vs Controlled
- Participant vs Non-Participant
- Covert vs Overt
NPC
Naturalistic vs Controlled
Observation techniques
Naturalistic observation:
* Behaviour is studied in a natural environment where everything has been left as it is normally.
* Although it is in a natural environment, the observer might be quite structured in what they are looking for.
AO3:
- No control of variables so difficult to establish cause-and-effect relationships.
- High degree of natural behaviour meaning findings can be generalised to everyday life
Controlled observation:
* Some variables are controlled by the observer.
- E.g. the environment is usually controlled or some items in the environment maybe deliberately chosen
* Participants are likely to know they are being studied
* May be conducted in a lab.
AO3:
- High level of control, easier to establish cause and effect relationship
- The environment is artificial, therefore you may not get natural behaviour
v
Structured vs Unstructured
Observation techniques
Unstructured observation
* The observer records all relevant behaviour, but has no system May be chosen if behaviour is unpredictable.
AO3:
- Because al participants have the same questions it is possible to compare responses and thus identify trends and patterns.
- More time consuming than a questionnaire, often with little obvious additional benefit.
Structured observation
* Before the research begins, the observer decides on the behaviour to be observed, often uses behavioural categories
* Types of structured observations:
- Behavioural categories: Dividing target behaviour (such as attachment) into a subset of behaviours, this can be a behaviour checklist or a coding system
- Event sampling: observers decide on a specific event relevant to the investigation. This event is recorded every time it happens
- Time sampling: when the researcher decides on a time (eg every two minutes) and then records what behaviour is occurring at the time
AO3:
- Allows the interviewee to go into more depth and detail than a structured interview.
- The information gathered is difficult to analyse objectively.
There is an increased risk of investigator bias.
Requires considerable skill on the part of the interviewer to be done well.
Overt vs Covert
Observation techniques
Overt: Patients are aware they’re being observed, their behaviour is recorded
AO3:
- Ethically sound as participants know they are being observed and will have given consent
- Participants may not behave naturally if they are aware of being observed
Covert: Participants are unaware their behavour is being observed and recorded
AO3:
- More valid results from participants because natural behaviour is being observed.
- Lack of informed consent means there are ethical issues, could also be invading the privacy of the participants
Participant vs Non-Participant
Observation techniques
Participant: The researcher actually participates with the group and joins in on their activities
AO3:
- Greater insights into behaviour are gained by being part of the group/situation, increasing validity of findings.
- Objectivity of observations are affected by being part of the group/situation.
Non-participant: The researcher would observe the group from a distance and not interfere with their activities
AO3:
- Lack of direct involvement ensures greater objectivity.
- Data lacks richness of that provided by participant observation, e.g. feelings and motivations of participants
Questionnares
Open questions: when the questions are phrased in a way that the participant is free to answer however they like, there are no fixed set of responses. This type collects qualitative data.
AO3:
-Useful in sensitive topics as participants can elaborate + go in depth and detail in their answers
- Difficult to convert to statistical data hence more difficult to analyse
Closed questions: Have a fixed set of responses, consists of yes/no or mcq, this type collects quantitative data
AO3:
- Closed questions provide quantifiable data in a consistent format, which enables to statistically analyse information in an objective way, easy to analyse data and compare with data from elsewhere
- There’s lack of depth and detail, questions can be limiting for participants
Interviews
- In an interview, participants are asked questions in person.
Structured interview: Questions are standardised and pre-set. The interviewer asks all participants the same questions in the same order.
AO3:
- Replicability: Structured interviews are easily replicated because participants are all asked the same pre-set list of questions. This replicability means the results can be confirmed by other researchers, strengthening certainty in the findings.
Unstructured interview: The interviewer discusses a topic with the participant in a less structured and more spontaneous way, pursuing avenues of discussion as they come up.
AO3:
- More detail: Interviews – particularly unstructured interviews conducted by a skilled interviewer – enable researchers to delve deeper into topics of interest, for example by asking follow-up questions. Further, the personal touch of an interviewer may make participants more open to discussing personal or sensitive issues.
- Lack of quantifiable data: Although unstructured interviews enable researchers to delve deeper into interesting topics, this lack of structure may produce difficulties in comparing data between participants. For example, one interview may go down one avenue of discussion and another interview down a different avenue. This qualitative data may make objective or statistical analysis difficult.
- Interviews can also be a cross between the two – these are called semi-structured interviews.
Aim vs Hypothesis
The aim of a study is a description of what the researchers are investigating and why; the purpose of their study
The hypothesis is a testable statement with a (specific prediction about the outcome of an investigation, using clearly operationalised variables.. The hypothesis can either be directional or non-directional
- Directional hypothesis states the direction of the relationship that will be shown between the variables; when someone makes a specific prediction ab the relationship between 2 variables
- Null hypothesis is a prediction that changing the IV will have no effect on the DV
Sampling
- Researchers use sampling to select participants for their study
Population: The population is a group of people from whom the sample is drawn
Sample: A part of the population that is representative of the entire group, example children at a certain school
Types of sampling includes;
OPPORTUNITY SAMPLING:
Participants happen to be available at the time when the study is being carried out
AO3:
- Quick and easy: Approaching participants is quick and straightforward. You don’t have to spend time compiling details of the target population (like in e.g. random or systematic sampling), nor do you have to spend time dividing participants according to relevant categories (like in stratified sampling).
- Not very representative of the population. Some members of the population are more likely to take part in the experiment.
RANDOM SAMPLING:
Method involves selecting participants from a target population at random – such as by drawing names from a hat or using a computer program to select them, members have an equal chance of being selected
AO3:
- Unbiased: Selecting participants by random chance reduces the likelihood that researcher bias will skew the results of the study.
- Time consuming: Need to have a list of members of the population (sampling frame) and then contacting them takes time.
Pilot studies
- A pilot study is a prior trial run, uses a small sample and in a pilot study the researcher can check aspects of the study eg if the instructions are clear, its done before the real investigation is undertaken
What are included in experimental designs
Experimental designs are how participants are allocated to the different experimental conditions
* Repeated measures
* Independant groups
* Matched Pairs
RIM
Repeated Measures Designs
Experimental Designs
The SAME participants take part in all conditions of the IV, all participant takes part of each level of the IV
AO3:
- Fewer participants are needed, so not as time consuming finding and using them
- Additionally order effects may be present; which can happen if the participant becomes better in the second condition task due to practice, and also if the participants becomes less good at a second task due to boredom. One way to control this is by using counterbalancing; counterbalancing is when in an repeated measures design, different participants are made to take part in the experimental conditions in different orders, in other words this is when one half of the participants do conditions in one order and the other half do it in the opposite order
Independant Group Designs
Experiment Designs
- When the researcher allocate different participants to each group (control grp and experimented grp) but don’t match the participants for any particular variables.
- To control for participant variables, the researcher will usually use RANDOM ALLOCATION
AO3:
- One strength is the participants are less likely to figure out the aim of the study (demand characteristics are eliminated) as they take part in only one condition
- One weakness is there’s no control over participant variables whereby differences found between the groups may be because of the individual differences rather than the IV
Matched Pairs Design
Experiment Designs
- When researchers do match participants in the two groups for a certain participant variable, then they have used a matched pair design, the researcher then allocates one of each pair in the control group and the othr in the experimental group
- One strength is demand characteristics and order effects are less of a problem as they take part in only one condition
- One weakness is its time consuming and expensive to match participants as the researcher has to test people before the study meaning this design is less economic, additionally more participants are required
A variable
- Something that can be changed, such as characteristic, event or value
Independant variable
- IV is the variable the experimenter deliberately changes
Dependant variable
- DV is the variable that’s measured to see whether there’re changes in the IV
Extraneous variable
- Extra variables that can affect the behaviour of participants in a research study is not controlled
- When extraneous variables are not properly controlled for they are known as confounding variables.
- Operationalisation of variables is where researchers clearly and measurably define the variables in their study.
Demand Characteristics
- Subtle clues that make participants aware of what the researcher expects to find or how the participant is supposed to behave, they change what participants do and think
- The participant may be wanting to please the researcher, they may just be nervous
- One way of dealing with them is to use deliberate deception, by telling participants that the study is looking at something other than what it really is.
Correlations
Correlations is a technique used to investigate the relationship between 2 or more co-variables
In correlation there are no cause and effect relationships are found which is why IV and DV terms aren’t used
POSITIVE CORRELATIONS
- As one variable increases, the other variable increases
NEGATIVE CORRELATIONS
- As one variable increases, the other variable decreases
AO3:
- One strength is they can be used as a starting point to assess paterns between co variables before commiting to conduct an experiment
- One weakness is they only demonstrate relationships, its difficult to establish a cause and effect
* Another weakness is there may be a third variable causing the effect
Primary vs Secondary Data
Primary data: Data that the teacher collected first hand
Secondary data: Data that has already been published in some form
Quantitative Data vs Qualitative Data
Qualitative data is…
* Made up of words
* Requires the participants to express themselves
* Can be converted into quantitative data
Quantitative data is…
* A frequency and may be numerical,
* Requires the participants to select an option provided by the researcher
* Cannot be converted into qualitative data.
Ethical Issues
P Diddy Caught Children
Confidentiality – all personal data should be protected and not disclosed unless agreed beforehand
- HOW TO DEAL WITH CONFIDENTIALITY: it will be stressed in the brief that all data will be kept confidential and no names will be identified on the test, ppts should be referred at code numbers instead. The test will have ‘confidential’ on the top right-hand side. There will be no identification/discussion of individual test scores
Consent – researcher should obtain informed consent by asking ppts to sign consent form – the ppts should be told about the aims, procedures etc, how long this experiment takes the ppts are told they can withdraw at any time
Deception – participants should not be misled and should be informed of the true nature of the study ie the link between age and memory.
Debrief – at the end of the study the researcher’s work colleagues should be fully debriefed and informed of any details withheld during the study.
Protection from harm – the participants should not be put at risk, physically or psychologically; in this study some work colleagues may get anxious if they cannot remember many words.
- HOW TO DEAL WITH PROTECTION FROM HARM: it is important that the colleagues are offered a debrief and the opportunity to speak to a counsellor if they feel this might be beneficial.
What are behavioural categories?
Observational Design
- Behavioural categories are a list of clearly defined, unambiguous, observable behaviours to be recorded during an observation.
- These should be agreed and operationalised before recording takes place.
Meta Analysis
- Meta-analysis is a research method where, rather than conducting
new research, the primary data from other studies are re-analysed. - a technique for combining the findings of independent studies.
