lecture 4 Flashcards
ethnography
intensive observational methods focused on participants culture
specific methodology
recording and analysing of researchers observations when immersed in a group
research is closely involved in research setting
general methodology
collect in a field setting
role of the observer
total observation
total participation
observer as non participant or participant
when to use participant observation
wanting to understand how a naturally occurring group, culture operates
when broad observations are appropriate
studying social interaction
possible elements to record in field notes
space- physical layout
time, range of people involved, emotions felt , single actions people undertake
participant observation advantages
rich varied and deep data
, generalisability
participant observation disadvantages
resource intensive- time consuming and expensive
memory distortions , subjective
who came up with grounded theory
glaser abd strauss
grounded theory
theory is ‘grounded’ in actual data , analysis and development of theories AFTER you have collected data
inductively derived theory
analytic ideas dome from the data
not about identifying hypothesis from existing literature
process involved in grounded theory
research familiarise with data, codes small elements - line approach, broader categories and continually compare the data with theory
types of coding
open coding
axial coding
selective coding
open coding
works as closely to original data as possible
axial codling
relating codes together
identification of key concepts
selective coding
identification of core category - major theme
advantages of grounded theory
flexible, hypothesis is not generated from something abstract,
disadvantages of grounded theory
demanding- time and effort
vagueness about procedures for theory testing
unclear how to evaluate theory
thematic analysis
widely used- not theory building approach
analysis of major themes
researcher has an active role
identifies patterns , selects those of interest , reports them
what is a theme
captures something important about data in relation to the research question
what counts as a theme
look at prevalence
but not necessarily mean its a key theme
codes
brief descriptions of small chunks of data
themes are identified and
developed from codes
should be carefully defined, differentiated from other themes
when to use thematic analysis
when themes are not expected to be interlinked, the detailed interpretation is not required, broad brush approach
how to do thematic analysis
familiarise, generate initial codes , search for themes, review, define and name themes.
thematic analysis advantages
flexible, relatively straight forward , accessible, fewer demands in data collection
thematic analysis
subjective, unable to retain continuity ,
