Qualitative and Quantitative data
· Reductionism allows researchers to control for extraneous variables in order to establish cause and effect on certain variables and outcomes.
· In theory it is easier to study one component rather than several interacting components.
· Focusing on one factor, researchers are able to study that factor in great depth.
· Because it can isolate factors, it does not always give a valid and full account of behaviour.
· Components maybe difficult to isolate and so manipulate. Therefore cause and effect can be questioned.
· Behaviour may not be meaningful if it is studied in isolation from the wider context as this is less useful when applied to real life.
· Reductionist research tends to use quantitative data and objective measures.
· Holistic tends to collect qualitative data and use subjective measures.
· Quantitative easier to analyse, providing objective data (charts and graphs). Make comparisons.
· Challenge: not in-depth data, the interpretation may be subjective.
· Collecting qualitative often uses case studies, spends 1:1 time with researcher to build a rapport, more truthful answers- increased validity.
· Collecting quantitative uses snapshot which can be better than case studies as they’re less time consuming and often use a larger, more representative sample.
· Quantitative data often has a higher reliability as the methods are more replicable and standardised (e.g. galvanic skin response).
· Qualitative often less standardised which reduced reliability.
· However, qualitative methods (e.g. unstructured interviews) are less restricted and so can be more valid by providing insight into unexpected responses.
· If ecologically valid, It can be considered more useful as its applicable to everyday life
· If generalizable, it can be used in many cultures and societies
· Preventative applications -> May allow us to put safeguards in place to prevent certain events occurring
· If treatments within studies are quick and cheap to conduct the study then it can be considered more useful
· If a study is shown to have long term effects it can be more useful
· progresses understanding of a phenomena beyond previous findings
· provokes further research in the field
· provides developments for therapies, interventions, preventative action or treatments
· If it’s not ecologically valid, it’s less applicable to real life
· If theoretical research cannot be carried out in real life situations then it’s less useful (e.g. mock trials)
· If a study isn’t standardised and not replicable then research lacks external reliability
· If a study cannot be applied to other demographics then it can be considered ethnocentric therefore less generalizable and less useful
· If a study takes a long time to conduct it can be considered less useful
· lack of new knowledge or understanding shown about phenomena
· research lacks internal validity and cannot be sure it is testing what set out to
· Experimental design – conditions, counter balancing, double/single blind technique
· Sample & sampling method – generalizability
· Experiment – lab, field quasi
· Self-report – open/closed questions, leading questions, rating scale, interview
· Observation – time/event sampling, coding scheme behaviours
· Data collection – quantitative/qualitative, nominal, ordinal, interval
· Ethics – PADDIWAC
· Longitudinal, snapshot, case study, review article, cross-sectional study
· Is the methodology reliable? – can be improved by a pilot study, inter-rater reliability
· Is the methodology valid? E.g. ecological, internal, external, face, construct, concurrent etc.
· Is the methodology replicable?
· PADDI WAC
· Ethics sometimes need to be broken in order to gain insightful and valid data.
· Do the detrimental effects on a group of individuals outweigh the benefits of the data we collect?
· Research that is unethical can be less useful as it cannot be repeated. Therefore external reliability cannot be assessed.
· Using confidentiality can help to improve validity as they feel like they can be more honest and less judged.
· Research methods such as correlations and quasi-experiments tend to be more ethical, they can be used to study issues that would usually be unethical.
· Some studies find unexpected findings which make it unethical. Milgram never expected to find his high obedience findings. Sometimes it is difficult to predict unethical procedures.
· This can be overcome be stopping studies and having ethics committees involved.
· Being highly ethical means that studies can be easily replicated. High internal and external reliability.
· Being highly ethical can often put constraints on a lot of useful research.
· Deception can be overcome with the use of debriefs and psychological follow up sessions to assess psyche.
· Ecological validity- the environment the study is carried out in may not be natural, or the task their doing may not be realistic.
· Challenge point: it laboratory settings it can be manipulated to be more like real life so in Zimbardo.
· In controlled setting where there is low ecological validity, the setting is more controlled so validity is increased in the sense that extraneous variables are controlled
· Social desirability/demand characteristics can reduce validity; participants may change behaviour because of embarrassment or working out the aims of the study particularly in experiments when using repeated measures design.
· Challenge: independent measures design can be used to help improve validity, as participants only do condition once.
· Population validity- the sample could be small which is a weakness as it doesn’t consider the population as a whole, and therefore doesn’t represent a wide range of people.
· Challenge: for many behaviours will be the same for all people or similar, and therefore they can be applied carefully to other populations as long cultural factors are considered. Ethnocentrism.
· Criterion validity - this is whether a factor measured in one way will relate to, or predict, some other related variable. For example; can your CAT tests in year 7 predict the grades you will get in your GCSE's? This is also known as predictive validity.
· Concurrent validity - whether a measure will produce similar results for a participant as another measure, that measures the same thing. For example; in Baron-Cohen, using the Strange stories task to validate the eyes task.
· Construct validity - is the foundation of the theory you are testing valid? Does it actually exist? For example does Freud's Oedipus complex have construct validity? The answer would be no in this instant, as he had no valid evidence to support his theory.
· External validity - this relates to the issues beyond the investigation, particularly whether the findings will generalise to other populations, locations, contexts and times than the ones investigated i.e. will the findings still be valid if I carried out a study in the UK and I'm trying to generalise it to America, if yes you have high external validity.
· Experiment -Highly controlled? Consistent measures?
· Observation – Inter-rater reliability/ the ways people used the coding scheme / Pilot study
· Interview - Structured or unstructured?
· Questionnaire- Rating scale, different perception for different people?
· Naturalistic observation- Can’t control extraneous variables / lacks consistency of measure due to this lack of control.
· Time Sampling- measure is consistent // Easy to reproduce
· Event sampling - Less consistent, may be administered incorrectly, miss some behaviours
· Field experiment - Difficult to control ex. variables
· Quasi - hard to replicate and lacks external reliability
· Independent Measures design- reduced chance of order effects // may be individual differences that aren’t considered
· Repeated measures design - Increased order effects
· Matched Pairs design - No order effects, less chance of extraneous variables: however presumes the two have a similar experience when they may not
· Internal reliability - this is the consistency of the items within the measure itself i.e. the questions), this shows that items in a self-report tool are measuring the same phenomenon.
· Split-half reliability - is a measure of internal reliability in which scores from two halves of a test are compared, if certain questions do not produce consistent responses, they can be removed in order to improve reliability.
· External reliability - does the measure produce the same results in the same situation with different people.
· Test-retest reliability - if a participant responds to the same test in a similar way, the test has high external reliability.
· Helps the world to be understandable and predictable.
· Often more scientific and so more accepted (e.g. biological)
· Useful applications, if certain factors determine behaviour, it can be prevented
· Having freewill allows us to have a positive influence on our own behaviour, i.e. that we are in control and determine our own future – internal locus of control.
· Having freewill in relation to cognition relates to the idea that we learn from mistakes. We have the ability to make calculations and strategies which help us to make the “right” choices in particular situations.
· Doesn't consider that we are able to make choices
And therefore reductionist
· Ignores humanism- 'people are like flowers, they need the right conditions to grow'
· How can justice be fulfilled if people did not consciously chose to commit crimes.
· Being deterministic promotes the idea that other people and factors are to blame – external locus of control
· Mental illnesses appear to undermine the concept of freewill. For example, individuals with OCD lose control of their thoughts and actions and people with depression lose control over their emotions.
· Collecting A LOT of data over long periods of time; see patterns and could easily establish cause and effect through these type of research studies and connections can be made more clearly.
· More data over longer periods of time allows for better and more concise results.
· Track long term changes- more useful applications
better representation of behaviour over a long period
increased validity and allows development of theories
· Large sample increases representativeness
· Takes a long time -obviously- which makes it time consuming and expensive
· Need a large sample
· Maybe prevent focussing on individual differences or abnormalities of a few people
· Extensive collection and sample could mean there’s a higher chance of mistakes
· More chance of attrition rates
· Issues of time can be overcome be carrying out cross-sectional studies
Strengths of the debate:
· If psychologists can understand which behaviours are individually determined and which are situationally determined, such findings may be useful for society when trying to understand or change certain behaviours.
· Discovering that behaviours may involve a complex interaction between individual and situational factors opens up new direction for further study.
· Useful applications - Individual explanations of behaviour are those that are centred on the person, whereas situational explanations focus on the situation that the individual is in. Situational or individual explanations are often used in educational settings as they provide a useful focus for helping to improve students’ engagement with learning. If a student regularly underachieves in a subject area there could be two broad reasons for this:
1. Individual – The student has little ability in this area.
2. Situational – The method of teaching does not suit the student.
Weaknesses of the debate:
· It is very difficult to separate the effects of a situation from the individual. This is very similar to the nature/nurture debate, in the sense that it is impossible to study them separately as they will always influence together.
· When situations are studied in a lab environment it is low in ecological validity. Therefore it is often hard to apply findings to real life.
· As with the nature/nurture debate, the situational/individual debate are direct alternatives and therefore there may be a complex interaction between the two.
· Ideographic and nomothetic debate is closely linked.
· Strength of the nurture debate because it is quite holistic it considers a range of factors including upbringing and the environment, this is a strength because you get a wider picture of the cause of behaviour so in turn this is more valid,
· It fails to consider the fact that our biological make up plays a role in how we behave, so the conclusions made by the nurture debate lack validity.
· Weakness of the nature/nurture debate is too simplistic, behaviour cannot be divided into nature or nurture, as the two always combine in complex ways to influence behaviour.
· Challenge: Understanding Individual impacts could help us have a better understanding of the combined impacts on behaviour.
· Weakness is that discovering certain behaviours are inherited may not be helpful it can lead to the assumption that these types of behaviour are difficult to change through the environment, this restricts useful applications.
· Challenge: Understanding the causes of behaviour gets us one step closer to helping individuals and providing them with therapy and treatment, and we can help educate people to reduce discrimination.
· Nature- tends to use objective measure because biological research supports the nature side of the debate this is useful because it reduces the chances of different viewpoints when analysing data
· Whereas nurture debate follows from the social approach which tends to use self-report subjective measures, which allows for different interpretation, reducing validity.
· Challenge: even when objective measures are being used to measure nature arguments, different psychologist may still have different views as to what the findings represent
· Population validity – if it can be generalised to the wider population it will lack ecological validity.
· Use of lab experiments decrease ecological validity
· Breaking ethics such as deception can improve ecological validity
· Suffering from demand characteristics and social desirability, reduce ecological validity.
· Issues with ethnocentrism – will not be ecologically valid when applied to other cultures.
· If the measure lacks internal validity – it will mean that it is not measuring what it intends to measure – therefore when applied to real life – will not be valid.
· Construct validity - is the foundation of the theory you are testing valid? Does it actually exist? For example does Freud's Oedipus complex have construct validity? The answer would be no in this instant, as he had no valid evidence to support his theory. Theories that have a lack of construct validity will also have low ecological validity.
· Field experiments = high ecological validity.
· ‘Mundane realism’ is a useful term to know when considering ecological validity. It simply means that, although the setting is artificial so the participants know they are participating in research, the task they are doing is real and engaging enough that they ‘buy in’ to what they are doing and treat it as if it were a real task e.g. Zimbardo.
· Independent measures design tend to be more ecologically valid compared to repeated.
· Temporal generalisation – does your study apply to any time or just the time your study occurred.