pack 2

• 6 main steps of thematic analysis

  familiarisation with the data: researcher must become familiar with data by reading and noting down initial observations

  coding: identifying and grouping the main ideas into categories which are relevant.

  searching for themes: initial ideas from data are considered into themes.

  reviewing themes: researcher checks whether the theme tell a compelling story about the data.

  defining and naming themes: researcher identifies the essence of each theme and constructs a concise name

  writing up: this involves putting main themes found in data and writing a report.
• types of research methods

  experimental method-lab and field experiments

  non-experimental- observations, questionnaires, intervies and case studies
• disadvantages of self reports

  it is difficult to establish a cause and effect link between variables

  demand characteristics might be high which can reduce the validity
• demand characteristics - participants know what is expected from them so change their behaviour
• principles of questionnaire design

  fit for purpose: questions should stick to the original aims of the research

  filler questions: include irrelevant questions to help reduce demand characteristics

  sequence of questions: begin questionnaire with less sensitive questions

  standardised procedures: all participants are all given the same questions in the exact same way

  ethical issues: deception might be necessary to reduce demand characteristics
• writing appropriate questions

  clarity: questions should be concise and clear

  avoid bias

  avoid leading questions
• open questions: allows participants to express themselves.(qualitative data)

  closed questions: gives participants a range of answers to choose from(quantitative)
• strengths of questionnaires

  high reliability: because standardised procedures are used, it is easier to replicate

  researcher does not have to be present to administer the questionnaire

  quantitative is easier to analyse
• weakness of questionnaires

  participants might misunderstand the question which reduces validity

  closed questions can reduce the validity and there is not enough detail

  participants might give socially desired answers if the demand characteristics are high
• types of interviews

  structured- have predetermined questions given in a set order

  unstructured- involves questions that are not in a set format

  semi structured- have set questions but interviewer has a chance to explore some answers further
• good practices in interviews

  no leading questions

  protection of the participant

  understandable questions
• strengths of interviews

  mostly generate qualitative data which gives rich detailed data

  structured interviews have standardised questions which are easy to replicate and increases reliability
• weaknesses of interviews

  unstructured interviews are difficult to replicate which reduces the reliability

  qualitative data analysis is time-consuming
• strengths of thematic analysis

  data remains rich and qualitative

  reduced researcher effects as themes are deprived from the data recorded
• weakness of thematic analysis

  it is time consuming and a high skilled job

  reliability can be a problem as different researchers might identify different theme from the same data
• experimental methods are the overall type of experiment eg. lab or field
• the aim of an experiments is to identify a cause and effect link
• methods in controlling extraneous variables

  counterbalancing-half the participants complete a task in one way and the other half in another

  randomisation- allocating participants randomly to control participant variables
• double blind - neither participant nor researcher knows the aims of the research to reduce demand characteristics and experimenter effects
• single blind- participants do not know the aims of the research to reduce demand characteristics
• lab experiments are conducted in a controlled setting which allows the researcher to deliberately manipulate the IV

  strengths of lab experiments

  they are cheaper and easy to control

  high reliability as they can be replicated (standardised procedures)

  weakness

  they lack ecological validity

  experimenter effects might be high

  they might raise ethical problems
• in field experiments the researcher deliberately manipulates the IV but in a natural setting

  strengths

  demand characteristics may be lowered as participants may not know they are being studied

  greater ecological validity

  quantitative data can be produced

  weakness

  ethical problems might be raised ie lack of informed consent

  they are more difficult to replicate

  all extraneous variables cannot be controlled
• experimental design is how participants are allocated in different conditions of the experiment

  examples are independent groups, repeated measures and matched pairs
• experimental condition is where participants experience the main condition of the IV

  control condition is the condition that gives a researcher the baseline for comparison
• independent groups

  this is where different participants are used in each condition of the experiment

  strengths

  order effects do not cause problems

  demand characteristic are low- high validity

  weakness

  participant variables may affect results

  more participants are needed
• repeated measures

  this involves using the same participants in each condition of the experiment

  strengths

  participant variables are kept constant

  fewer participants are needed

  weakness

  demand characteristics may be high

  order effects may affect the results
• matched pairs

  using different participants in each condition but keeping them the same in some conditions that might affect their performance

  strengths

  participant variables can be controlled

  demand characteristics can also be controlled

  weakness

  matching participants is very difficult

  more participants are required
• case studies are in depth investigations used to gather highly detailed information of an individual or a small group

  strengths

  they can trigger further research on a finding

  data gathered is qualitative

  weakness

  they are difficult to replicate (low reliability)

  a cause and effect link cannot be established because of the lack of control of variables
• correlational research collects data to investigate the extent to which two variables are associated
• co variables are two variables in a correlational study which have been measured
• correlational analysis is s date analysis technique that describes the relationship between two co-variables in statistical terms
• a positive correlation is where values of two variables are directly proportional

  a negative correlation is where high values on one variable are associated with low values on the other variables
• a scatter diagram is a visual representation of a correlational relationship

  the strength of the correlation is indicated by the straightness of the line of dots

  the direction of the correlation is indicated by the slope of the line of dots
• a correlational coefficient can be any number between -1 and +1.

  0.0 to 0.3 is weak, 0.3 to 0.7 is moderate and above 0.7 is strong

  these numbers show the strength and direction of the correlation
• strengths of correlational research

  it serves as a starting point for stimulating further research

  it tends to be objective and replicable

  it allows the identification of relationships
• weaknesses of correlational research

  a cause and effect link cannot be established

  the two co variables might not be measured in a valid manner

  correlations might be misused
• observational research occurs when there is an observation of a person's freely chosen behaviour
• types of observational research

  naturalistic-observations where behaviour is studied in its natural setting with no manipulation from the researcher

  structured- observations where some variables are controlled
• participant observations- when the observer becomes part of the group

  non-participant- where the observer is not involved in the action

  covert- when the participants do not know they are being observed

  overt- when the observer is known to be present by those observed
• strengths of naturalistic observations

  high ecological validity

  validity is increased as data being collected is rich