CHAPTER 20: Analizing and Interprating Data
Data analysis and interpretation: definition and purpose
involves
summarizing data
requieres
the researcher be patient and reflective
including
field notes
interviews, questionnaires, maps
is an attemp
find meaning in the data
are critical steps
explore every possible angle
techniques outlined
guideposts and prompts
Data analysis during data collection
the researcher
should try to narrow
topic
gathering data, examining data
answer two questions
Is your research question still answerable and worth answering?
Are your data collection techniques catching
the kind of data you want and filtering out
the data that you don’t want?
pausing during the research
allows you to reflect on what you are attending
avoid premature actions
Data analysis after data collection
researcher
examine each piece of information
starts with a large set of data
small and important groups of key data
constructs meaning by identifying patterns
. Avoid premature judgment.
Read and reread
watch and rewatch
Steps in analyzing Qualitative research data
Qualitative data analysis
is a cyclical, iterative process
three iterative steps
reading
memoing
describing
classifying research data
writing notes in the field note
thorough and comprehensive descriptions
Classifying small pieces
into general categories
make sense and find connections
Field notes and transcripts
small pieces of data
pieces are integrated into categories
more general patterns.
Data Analysis Strategies
Identifying themes
identification of ideas
from the review of literature
data collection
Coding
process of marking units
text with codes or labels
indicate
patterns and meaning in data
Asking key questions
seeking answers
organizational review
understand the school
vision and mission, goals and objectives
Concept mapping
create a visual display
identification of consistencies
Analyzing antecedents and consequences
map the causes and effects
Displaying findings
matrixes, charts, concept maps, graphs, etc
Stating what’s missing
reflect and identify any questions
computer programs are available
Data interpretation strategies
Data interpretation
connections, common aspects
Interpretation
cannot
be meaningfully accomplished
aim
answer four questions
What is important in the data?
Why is it important?
What can be learned from it?
So what?
Extending the analysis
data interpretation strategy
raises questions
study, noting implications
Connecting findings
personal experience
personalize interpretations
Contextualizing
findings of the study
related literature
Turning to theory
link their findings
increase levels of abstraction
Ensuring credibility in your study
check the credibility
researchers
ask themselves
Are the data based on one’s own observation or on hearsay?
Are observations corroborated by others?
In what circumstances was an observation made or reported?
How reliable are those providing the data?
What motivations may have influenced a participant’s report?
What biases may have influenced how an observation was made or reported?
YADIRA PILA 4TH "A"