non- experimental methods

naturalistic observations

An observation carried out in an unaltered setting in which the observer does not interfere in any way and merely observed the behaviour in question as it happens normally.

naturalistic observations pros

Higher level of ecological validity can be achieved. The researcher records naturally occurring behaviour in the original environment in which it ordinarily occurs. The behaviour recorded is likely to be more representative of everyday activities and reflect spontaneous actions that sometimes occur incidentally.

naturalistic observations cons

Issues of ascertaining reliability with naturalistic observations. Since observations of this kind record behaviours which are occurring naturally as they unfold it is difficult for the exact same conditions to be replicated. Consequently the test-retest method of checking reliability cannot be used as the researcher is not in control of variables. Lacks replicability.

controlled observations

Conducted under strict conditions, such as an observation room or lab, where extraneous variables (such as time of day, noise and temperature) can be controlled to avoid interference with the behaviour being observed. Sometimes one way mirrors can be uses.

controlled observations pros

They can be replicated to check for reliability. The variables are highly controlled in this type of observational design. This means that standardised procedures, manipulation of the independent variable and control over extraneous variables can be repeated by the same, or different researchers to assess reliability.

 

controlled observations cons 

Lower level of external validity. The researcher records behaviour in an artificial environment with variables subject to strict manipulation. This means that the setting can feel unnatural and the behaviour may alter in response and so the observation no longer represents real life.

 

 overt observations

An observational technique where the observations are open and the participants are aware that they are being observed.

 overt observations pros 

More ethical since participants are aware that the behaviour is being observed for the purposes of a psychological investigation , it is possible to inform them in advance of the aims and thus obtain informed consent. This method allows participants to exercise their right to withdraw themselves or their data from the investigation.

 overt observations cons

Possibility of investigator effects. It is possible for a bias to occur whereby what the investigator does influences the behaviour of the participants in a way that was not intended. As a result the participants may change their behaviour through demand characteristics and act in accordance with their perception of the research aims. Therefore, authentic and natural behaviour is not being observes and the internal validity is reduced.

covert observations

Consists of observing people without their knowledge, for example using a one way mirror or joining a group as a member. Participants may be informed of their involvement in the study after the observation has taken place.

 

covert observations pros 

Less likely to have investigator effects as they are hidden and their direct or indirect behaviour will be less likely to have an impact. Less likely to result in demand characteristics . Their behaviour will be more natural and representative of every day behaviour.

covert observations cons

Ethical issues as participants are not aware they are taking part in an investigation and so cannot give fully informed consent or exercise the right to withdraw.

 participant observations

The person who is conducting the observation also takes part in the activity being observed. It can either be covert or overt

 participant observations pros

Researcher can obtain in-depth and unique data due to close proximity. They are unlikely to overlook behaviour that an external observer may miss due to nuances only seen by becoming a participant in the activity.

 participant observations

Possibility of investigator effects, the mere presence of the investigator as a member may influence the participants behaviour to change ( demand characteristics) and the internal validity is reduced.

structured observations

Researcher uses coded schedules according to a previously agreed formula to document the behaviour and organise data into behavioural categories. A behaviour category is when psychologists must decide which specific behaviours should be examined. This involves breaking the target behaviour (e.g. aggression) into components that can be observed and measured.

structured observations cons

Problems with high internal validity. This is because the researcher may miss some crucial behaviours during the observation which is pertinent to the aim of the investigation. As a result the findings may not provide the full picture. This could mean what was intended to measure was not achieved in its entirety.

structured observations pros

The researcher can compare behaviour between participants across groups. The use of operationalised behavioural categories makes the coding of data more systematic. When there is more than one observer, the standardised behaviour schedule results in greater inter-observer reliability. It is important for research methodologies to be consistent so that accurate comparisons can be made.

 unstructured observations

Every instance of the observed behaviour is recorded and described in detail. This is useful if the behaviour the researchers are interests in does not occur very often and is more usual with naturalistic observation.

 unstructured observations pros

Richness of data obtained and researchers are able to obtain a comprehensive view of human behaviour. This adds to internal validity of the observational technique.

 unstructured observations pros

Prone to observer bias due to the lack of objective behaviour categories. This is a problem because the observer may then only record behaviour which is of subjunctive value to them. Issues with inter-observer reliability and lack of consistency.

event sampling

Where an observer records the number of times that the target behaviour occurs e.g using a tally

event sampling pros

Every behaviour of interest to the researcher, in theory, will be counted from the beginning through to the end of the observation.

event sampling cons

There is a possibility that some behaviours could be missed if there is too much happening at the same time, resulting ins some not being coded.

time sampling

Where an observer records behaviour at prescribed intervals

time sampling pros

Time sampling allows for a better use of time since fewer observations are made.

time sampling

Not every behaviour of relevance to the investigation will be counted if it occurs in between the time frames allocated.

non-participant observations

The person who is conducting the observation does not participate in the activity being observed. This type of observation is common in educational settings (teacher evaluations). The aim is for the observer to be as unobtrusive as possible and to not engage with any activities happening.

 

non-participant observations pros

Investigator effects less likely as the researcher is observing from a distance. Behaviour observed is more likely to be representative and unaltered human conducted.

non-participant observations cons

A lack of proximity means that the researcher may miss human behaviour being observed and will overlook things.

questionnaires 

 a type of self-report where participants provide information relating to their thoughts, feelings and behaviours. They can be designed in different ways, and can comprise of open questions, closed questions or a mixture of both

 

interviews

 another type of self-report which predominantly takes place on a face-to-face basis, although they can also happen over the phone. There are three different types: structured, unstructured and semi structured.

closed questions

restrict the participant to a predetermined set of responses and generate quantitative data. There are different types of closed questions including: checklist, Likert response scale and ranking scale.

 

Evaluation:

 

• The nature of data collected is quantitative. This is easy to analyse statistically or in a graphical format. This is useful because direct comparisons can be made between groups of individuals. This means the researcher can look for patterns and trends in the data that can lead to further research being conducted.

 

• By sticking to a predetermined list of questions, the researcher is unable to pursue and explore responses that are of particular interest. Additionally, closed questions often produce a response bias. This can happen because the participant doesn’t take the time to read all the questions properly and, for example, selects ' yes ' for each of their answers. This means that the data generated may lack internal validity.

 

open questions

Open questions: allow the participant to answer however they wish and thus generate qualitative data since there is no fixed number of responses to select from. Responses to these types of questions provide rich and detailed data which can provide insight into the unique human condition

 

Evaluation:

 

• Less chance of researcher bias as the participant can answer the questions in their own words, without input from the researcher providing a set number of responses. Consequently there is less chance of the responses being influenced by the researcher expectations.

 

• Participants may answer in a socially desirable way, where they try to portray themselves in the best light possible to the researcher. This means that the open response may lack validity as it is not their natural response

other important considerations when constructing questionnaires

• Keep terminology simple and clear

• Keep it as short as possible

• Be sensitive; avoid personal questions and if you must do this at the end.

• Do not use leading questions

• Do not use questions that make assumptions or sweeping statements

• Pilot and modify the questionnaire

structured interviews 

Structured interviews: have the questions decided on in advance and they are asked in exactly the same order for each interviewee taking part. The interviewer uses an interview schedule and will often record the answers to each question by taking notes/ticking boxes on their schedule.

 

Evaluation:

 

• The quantitative data is easier to strategically analyse. This is useful for direct comparisons between groups so that the researcher can look for patterns and trends in the data. Because the questions are standardised and asked in the same sequence every time to all participants, the interview is easily replicable to test for reliability

 

• Possibility of investigator effects as the interviewer may, unconsciously, bias any response given through tone of voice, intonations and body language.

semi-structured interviews 

Semi structured interviews: comprise of mostly prepared questions that can be supplemented with additional questions as seen fit by the interviewer at the time. as with unstructured interviews, the interviewer can deviate from the original questions and consequently this type of interview produces rich qualitative data

 

Evaluation:

 

• Increases validity. The open questions may encourage the participant to be honest in their answers, thus reducing social desirability bias as participants are able to justify their answers in their own words with opinions.

• However the interviewer still retains control and so investigator effect are likely.

 

• Generate rich and interesting qualitative data as they can ask to clarity and gain further information if required. This provides a unique insight into human behaviour.

• However as a result analysis of data is more difficult, time consuming and expensive to conduct

unstructured interviews

Unstructured interviews: conducted more like a conversation, with the interviewer only facilitating the discussion rather than asking set questions. Very little is decided in advance and large amounts of rich qualitative data is produced. Answers will be recorded as to write them down as they are spoken would be impossible and would spoil atmosphere.

 

Evaluation:

 

• Increases the validity by significantly reducing the possibility of investigator effects. The open question schedule in unstructured interviews means that the investigator does not control the direction of the conversation to meet there aims. Participants can justify their answers in their own words with opinions instead of trying to guess the aim through clues given. This reduces demand characteristics.

• Unstructured interviews generate large quantities of qualitative data.

correlational technique

non-experimental methods used to measure how strong the relationship is between two or more variables. In a correlational study it is the movement and direction of co-variables in response to each other that is measured and there can be no claim of a cause and effect relationship until after the study has been conducted.

co variable 

one of two or more variables being measured to see if a relationship exists between them

Distinguish correlations from experiments

Whilst experimental research involves manipulation and control, correlational research examines natural relationships between variables. Unlike in an experiment here can be no claim of a cause and effect relationship until after the study has been conducted.

Explain different types of correlation (positive, negative, zero)

Positive- as one variable increases the other also increases

Negative- as one variable increases the other variable decreases

Zero- when a correlational study finds no relationship between variables

Identify and interpret correlation coefficients (-1 to +1)

Correlation coefficients- uses to measure the strength and nature of the relationship between two co-variables.

Correlation coefficient number-represents the strength of the relationship and can range from -1.0 and +1.0. the nearer the number is to +1 or -1 the stronger the correlation. A perfect positive correlation has a correlation of +1 and a perfect negative correlation will be -1.

strengths of correlational technique

Strength- they are an ideal place to begin preliminary research investigations. By measuring the strength of relationships they provide valuable data for future research. It can be used when a lab experiment would be unethical as variables are not manipulated, just correlated.

 

Strength- secondary data can be used in correlational studies which alleviates the concern over informed consent as the information is already in the public domain (government report

weaknesses of correlational technique

Weakness- it is not possible to establish a cause and effect relationship through correlating co-variables. Researchers cannot conclude that there is not a third variable.

 

Weakness- correlations only identify linear relationships and not curvilinear

case studies 

Case studies provide a detailed analysis of an individual, established or real-life event. A case study does not refer to the way in which the research was conducted as they can use experimental or non-experimental methods to collect data.

 They are often used when there is a rare behaviour being investigates which does not arise often enough to warrant a larger study being conducted. A case study allows data to be collected and analysed on something psychologists have very little understanding of, and can therefore be the starting point for further, more in-depth research.

strengths of case studies

• offers the opportunity to unveil rich, detailed information about a situation. These unique insights can often be overlooked in situations where there is only the manipulation of one variable in order to measure it's effect on another.

 

• can be used in circumstances which would not be ethical to examine experimentally.

weaknesses of case studies

• methodological issues as by studying one individual, isolated event or small group it is very difficult to generalise any findings to the wider population. This therefore creates issues with external validity.

 

• the researchers own subjectivity may pose a problem. We cannot be sure that the researcher has objectively reported his findings.

process of content analysis 

Content analysis is a type of observational technique which involves studying people indirectly through qualitative data which can be collected in a range of formats. Content analysis helps to classify responses in a way that is systematic and then clear conclusions can be drawn.

 

• Researchers must make sure that their questions are formulated so that they know exactly what their content analysis will be focused on. They should familiarise themselves with the data before conducting any analysis  so that they are confident that their coding system is appropriate.

 

• Content analysis is helpful when conducting research that would otherwise be considered unethical. Any data that has already been released into the public domain is available to analysis, such as newspaper articles- this means that consent is not required. It is also good for content of sensitive nature.

 

coding

involves the researcher developing categories for the data to be classified. Qualitative data can be extensive in its nature so coding can be helpful in reaching succinct conclusions about the data. These categories provide a framework to convert qualitative data into quantative data which can be used for statistical analysis.

strength of using content analysis

high ecological validity. The analysis is based of observations of real-life behaviour and written and visual communications.

weakness of using content analysis

the content analysis can produce findings that are very subjective. Cultural differences may contribute to an inconsistent interpretation of behaviour coding since language may be translated and interpreted differently. Therefore the validity of findings may be questions.