self report: questionnaires + interviews, exp: lab + field Flashcards
Principles of questionnaire design
Fit for purpose, filler questions, sequence of q, standardised procedures, pilot studies, ethical issues
What’s an advantage/dis of open-ended questions?
Not limited, get to know WHY
it can be difficult to summarise descriptive responses for analysis and to find trends in data
Dis/Ad on close ended questions?
Objective easy to analyse,limit validity as answers only fall into one category, so may oversimplify human behaviour
Dis of Likert scales
low internal reliability-as often several items on the questionnaire may be measuring the same variable so split half method can be used
response bias may occur where ppts just put same response on one side of the scale to avoid this items must be mixed up so ppts will be using both ends of the scale
Adv of questionnaires
reliable, high validity as a researcher isn’t present so no pressure, quantitative data
Dis of questionnaires
closed q limit validity + socially desirable answers,+ not understanding q, the purpose is obvious so is demand characteristics,
Adv of interviews
structured interviews=quantitve data and easy-to-replicate,detailed data
Dis of interviews
Interviews are social interactions so socially acceptable answers may be given, interviewers gender,ethnicity, status and personality may affect it structured interviews held back by a predetermined set of q, cannot est cause and effect as noi way to control all variables that influence a ppt answer
Describe the process of thematic analysis
Familiarisation with data
drawing codes from the data,
searching for themes,
reviewing the themes,
defining and names themes,
writing up report
describe ‘familiarisation with data’
Read through the data corpus
If it is audio data, transcribe it
Note any initial analytical observations
describe ‘coding
Initial codes of labels using words or short phrases to identify important features of the data
It can be done manually or with a software program
Highlighting or post-it notes are a good way to indicate the origin of codes
Code as many potential themes as possible
All the data identified under the same code should be collated
describe ‘searching for themes’
Sort all the codes into broader patterns of meaning of themes
Mind maps and tables are a good way to sort the codes
Some codes may form main themes or sub-themes, or even get discarded
describe ‘reviewing themes’
Refining themes by combining or splitting or discarding on a mind map
The themes should have a relationship and form a coherent pattern, if it doesn’t then the issue may be with the theme itself or the arrangement of data
The themes should reflect the data corpus as a whole and the aim of the research
describe ‘defining themes’
Each theme should be have a concise name and definition to immediately identify the ‘essence’ of each theme
The researcher should conduct a detailed analysis on each theme (e.g. how the theme fits with the data as a whole)
An overall narrative of the data will be formed with a final thematic map
describe ‘finalising report’
Final analysis and writing the report
The audience must be considered to allow for coherent and appropriate language (e.g. writing for a scientific journal or a newspaper)
Evidence for each theme should be provided
Strengths of thematic analysis
Braun and Clarke- data remians rich as it provides an ‘intimate window onto the life worlds of people’, validity remains high as data remains qualitative
Weaknesses of thematic analysis
The researcher may already have themes in mind- researcher effect reducing validity, time-consuming
Low validity - the data corpus is qualitative and so open to interpretation when identifying codes and themes therefore has an element of researcher bias
adv of lab exp
control extraneous variables so we can find causes of the behaviour of ppts in an objective manner, standardisation,
dis of lab exp
artificial settings so tasks are contrived producing artificial behaviour lacking ecological validity, experimenter effects can be high results affected by demand characteristics
adv of field exp
ecological validity since its close to real life, demand charatersictics can be low
dis of lab exp
extraneous variables so internal validity may be low due to other variables than IV, hard to replicate, experimenter effects hard to control variables coming from experimenter influencing ppt, ethics
what is independent group/measures?
dif set of ppt in each condition
strength of IG/M
no order effects,no demand characteristics, same tests can be used in both conditions
weakness of IG/M
ppts variables it may be that any differences could be due to u having some ppts in one condition who were good/bad
what is repeated measures?
same ppt in each conditon
strength of repeated measures
ppt variables-the individual differences are kept constant, and fewer ppt are required
weakness of repeated measures
demand characteristics more obvious and exposed to more cues so they can guess the aim, order effects may confound results
what is matched pairs?
using dif ppt in each condition but making sure certain variables are the same that might affect their performance
strengths of matched pairs
ppt variables are controlled, order effects are not presented, no demand characteristics, same test can be done in both conditions
weaknesses of matched pairs
difficult to match ppt variables, the process may be biased, more ppts
