RM Qual 2 Flashcards
Qualitative Data Analysis
- Systematic process of meaning-making. A defined
set of procedures that are used flexibly (i.e. not a
recipe) - Identifies patterns in data. Typically inductive but
can be deductive - Describes and Interprets data
- Aims to understand variation in experience and
considers complexity - Empathetic (or can be critical)
- Requires the active engagement of the researcher
with the data
Transcription:
________ is most common –e.g.
Orthographic
speech is transcribed
verbatim using standard spelling conventions
Transcription
More complex forms take account of different aspects e.g.
_________ system (Landridge & Hagger-Johnson, 2009):
which 3 extra features does it have ?
Jefferson
- Prosody (phonemic aspects of spoken language e.g. intonation,
stress) - Paralinguistics (non-phonemic aspects of language e.g. serious
or jocular) - Extralinguistic (non-linguistic aspects e.g. gesture
Content analysis
aim
uses qualitative data to examine patterns in communication in a replicable and systematic manner. systematic labelling of data allows statistical analysis of non-numerical data
Grounded theory
aim
to generate theories of social phenomena through systematic data analysis. It has inductive and deductive stages (e.g discover new themes, apply preconstructed theme)
Discourse or conversation analysis
aim
identify rules of conversational organisation. Studies recorded, naturally occurring talk-in-interaction to discover how participants understand and respond to one another
Interpretive phenomenological analysis
aim
offer insights into how a given person in a given context makes sense of a given phenomenon. usually these phenomena relate to experiences of some personal significance, such as a major life event or the development of an important relationship. Typically uses small homogenous samples
(whereas case study is on one persons experience. IPAs are interested in multiple peoples experience of a phenomena)
Thematic analysis
aim
a method for identifying, analysing and reporting patterns (themes) within data. It organises and describes your data in (rich) detail. However, frequently it goes further than this and interprets various aspects of the research topic.
advantages of thematic analysis
- A unique feature of TA is it’s Flexibility e.g. sematic or
latent; inductive or deductive, essentialist or
constructionist - Relatively easy and quick to learn and do
Accessible to novice researchers - Summarises key features of a large body of data
- Highlight similarities and differences across a data set.
- Can generate unanticipated insights
- Allows for social and psychological interpretations of
data - Results accessible to educated general public - Useful for
producing qualitative analyses suited to informing policy
development
Six phases of TA
- Data familiarisation – reading the data
- Generating codes – labelling ideas in the data that are relevant to the RQ
- Searching for themes - grouping related codes into candidate themes
- Reviewing themes – checking themes ‘fit’ the data and address the RQ
- Defining and naming themes – describing themes and selecting data extracts
- Producing the report / paper – writing introduction, method, findings and discussion
maybe make more cards on TA
thematic analysis