discuss the qualitative data analysis
TASK:
discuss the qualitative data analysis
Qualitative research
is development of concepts which help us to understand social phenomena in
natural (rather than experimental) settings, giving due emphasis to the
meanings, experiences and views of the participants .Many qualitative
researchers operate on an assumption that the empirical evidence they gather is
related to both theoretical ideas and structures that lies beneath observable
reality. But the data from the observable, surface reality are only samples of
what happens on the visible, surface level.
Such
data only partially reflects what goes on unseen, beneath the surface where
deeper social structures or relationships resides but the researcher uses these
data to evaluate theories and make generalizations or conclusions.
Common
Qualitative Research Design
Study
Design Description
Ethnography Study of theory and culture of a group of
people usually to develop cultural awareness & sensitivity.
Phenomenology
Study of individual experiences of events e.g. The experience of AIDS care.
Grounded
theory Going beyond adding to the existing body of knowledge to developing a
new theory about a phenomenon - theory grounded on data.
Participatory
action research Individual & groups
researching their own personal being, socio-cultural setting and experiences.
Case
study In-depth investigation of single or small number of units at a point
(over a period) in time.
Sampling Techniques in Qualitative
Research
Sampling
in qualitative research is mostly purposive with specific criteria in mind! It
seeks conceptual applicability rather than quantitative representativeness. It
also seeks to capture the range of views/experiences, pursue saturation of data
and draw theory from data. The sampling techniques include:
a) Snow
ball/chain sampling
b) Extreme/deviant
case sampling
c) Homogeneous
sampling
d) Maximum
sampling
e) Convenience
sampling
f) Opportunistic
sampling
What
is Qualitative Data?
Transcripts
of individual interviews and focus groups or field notes, copies of documents,
audio and video recordings from observation of certain activities.
Data
that are related to concepts, opinions, values and behaviors of people in a
social context. Data that are not easily reduced to numbers.
Types of Qualitative Data
a) Structured
text (writings, stories, survey comments, news articles, books etc).
b) Unstructured
text (transcription, interviews, conversation etc).
c) Audio
recordings and music.
d) Video
recordings (graphics, art, pictures, visuals).
Qualitative Data Collection Methods
Methods
Brief Explanation
Observation.
The researcher gets close enough to study subjects to observe ( with or without
participation) usually to understand whether people do what they say they do.
Interview this
involves asking questions, listening to and recording answers from an
individual or group on a structured, semi-structured or unstructured format in
a in-depth manner.
Focus Group Discussion.
Focused (guided by a set of questions) and interactive session with a group
small enough for everyone to have chance to talk and large enough to provide
diversity of opinions.
Other
Methods Rapid assessment procedure (RAP), Free listing, Ranking, Life history
(biography) etc.
Questions for Qualitative
Interviews
Types
of question Examples
Hypothetical If you get the chance to be an HIV scientist,
do you think you can discover a vaccine for HIV?
Provocative I have heard people saying most evaluations
are subjective, what do you think?
Ideal In your opinion, what would be the best
solution for eliminating gender-based violence?
Interpretative What do you mean by good?
Leading Do you think prevention is better
than cure?
Loading Do you watch that culturally
degrading TV show on the use of condom?
Multiple Tell me your three favourite authors,
the book you like best by each author and why you like those books?
Focus
of Qualitative Questions
Experience: When you told your manager
that the project has failed, what happened?
Opinion: What do you think about the
role of evaluation for program improvement?
Feelings: When you got to know that the
project was a success, how did you feel?
Knowledge: Tell me about the different
ways of promoting PME?
Input: When you have lectures on
evaluation assessment, what does the instructor tell you?
Preparing
Metadata (Log)
Project/ research title
Date
of data collection
Place of data collection
ID-code of informants
Research team
Method of data collection
Documentation type: Tape record, notes
and observations
Qualitative Data Analysis (QDA)
is the range of processes and procedures whereby we move from the qualitative
data that have been collected, into some form of explanation, understanding or
interpretation of the people and situations we are investigating.
QDA
is usually based on an interpretative philosophy. The idea is to examine the
meaningful and symbolic content of qualitative data.
Approaches in Qualitative Data
Analysis
Deductive Approach
Using
your research questions to group the data and then look for similarities and differences.
Used when time and resources are limited. Used when qualitative research is a
smaller component of a larger quantitative study
Inductive Approach
Used
when qualitative research is a major design of the inquiry. Using emergent
framework to group the data and then look for relationships.
Common
Terms Used in Qualitative Data Analysis
Theory: A set of interrelated
concepts, definitions and propositions that presents a systematic view of
events or situations by specifying relations among variables.
Themes:
categorical ideas that emerge from grouping of lower-level data points.
Characteristic:
a single item or event in a text, similar to an individual response to a
variable or indicator in a quantitative research. It is the smallest unit of analysis.
Coding: the process of attaching
labels to lines of text so that the researcher can group and compare similar or
related pieces of information.
Coding sorts: compilation of
similarly coded blocks of text from different sources in to a single file or
report.
Indexing:
process that generates a word list comprising all the substantive words and
their location within the texts entered in to program.
Principles of Qualitative Data
Analysis
a)
People
differ in their experience and understanding of reality (constructivist-many
meanings).
b)
A
social phenomenon can’t be understood outside its own context (Context-bound).
c)
Qualitative
research can be used to describe phenomenon or generate theory grounded on
data.
d) Understanding human behavior emerges
slowly and non-linearly.
e)
Exceptional
cases may yield insights into a problem or new idea for further inquiry.
Features of Qualitative Data
Analysis
a) Analysis
is circular and non-linear.
b) Iterative
and progressive.
c) Close
interaction with the data.
d) Data
collection and analysis is simultaneous.
e) Level
of analysis varies.
f) Uses
inflection i.e. “this was good”. Can be sorted in many ways.
g) Qualitative
data by itself has meaning, i.e. “apple”.
Types of Qualitative Analysis
1) Content analysis
2) Narrative analysis
3) Discourse analysis
4) Framework analysis
5) Grounded theory
1) Content Analysis:
Content
analysis is the procedure for the categorization of verbal or behavioral data
for the purpose of classification, summarization and tabulation. Content analysis
can be done on two levels Descriptive: What is the data? Interpretative: what
was meant by the data?
2) Narrative Analysis
Narratives
are transcribed experiences. Every interview/observation has narrative aspect.
The researcher has to sort-out and reflects up on them, enhance them and
present them in a revised shape to the reader. The core activity in narrative
analysis is to reformulate stories presented by people in different contexts
and based on their different experiences.
3) Discourse Analysis
This
is a method of analyzing a naturally occurring talk (spoken interaction) and all
types of written texts. It focuses on how people express themselves verbally in
their everyday social life i.e. how language is used in everyday situations?
a) Sometimes people express themselves in
a simple and straightforward way
b) Sometimes people express themselves
vaguely and indirectly
c) Analyst must refer to the context when
interpreting the message because the same phenomenon can be described in a
number of different ways depending on context .
4) Framework Analysis
Familiarization:
Transcribing & reading the data
Identifying
a thematic framework: Initial coding framework which is developed both from a
priori issues and from emergent issues
Coding:
Using numerical or textual codes to identify specific piece of data which
correspond to different themes
Charting:
Charts created using headings from thematic framework.
Mapping
and interpretation: Searching for patterns, associations, concepts and
explanations in the data
5) Grounded Theory:
This theory starts with an examination of a single case from a ‘pre-defined’ population.
Afterwards the analyst examines another case to see whether the hypothesis fits
the statement. If it does, a further case is selected but if it doesn’t fit
there are two options: Either the statement is changed to fit both cases or the
definition of the population is changed in such a way that the case is no
longer a member of the newly defined population. Then another case is selected
and the process continues.
In
such a way one should be able to arrive at a statement that fits all cases of a
population-as-defined. This method is only for limited set of analytic
problems: those that can be solved with some general overall statement.
Strategies for Analyzing
Observations
a) Chronology:
describe what was observed chronologically overtime, to tell the story from the
beginning to the end.
b) Key
events: describing critical incidents or major events, not necessarily in order
of occurrence but in order of importance.
c) Various
settings: describe various places, sites, settings, or locations in which
events/behaviors of interest happen.
d) People:
describing individuals or groups involved in the events.
e) Process:
describing important processes (e.g. Control, recruitment, decision-making,
socialization, communication).
f) Issues:
Illuminating key issues – how did participants change?
The Process or Steps of Qualitative
Data Analysis
1. Organize the data
2. Identify framework
3. Sort data into framework
4. Use the framework for descriptive
analysis
5. Second order analysis
1. Organize
the Data
Transcribe
the data (you can use hyper TRANSCRBE software).Translate the data (You can use
language translation software like SYSTRAN).Data cleaning Label the data
(Structuring & Familiarizing).
2. Identify
a Framework
Framework
will structure, label and define data. Explanatory – Guided by the research
question. Exploratory- Guided by the data. Framework Coding plan.
3. Sort Data into Framework
Code
the data. Modify the Framework. Data entry if use computer package
4. Use
Framework in Descriptive Analysis
Arrange
the responses in categories and Identify recurrent themes. Note: Stop here if
research is exploratory.
5. Second
Order Analysis
Identify
recurrent themes. Notice patterns in the data. Identify respondent clusters
(Search for causality and identify related themes).Build sequence of events Search data to answer research questions.
Develop hypothesis and test.
Traditional Method of Qualitative
Analysis
Traditional
Qualitative data analysis is labor-intensive. After gathering data, the
researcher will:
Transcribe
the source material with a word processor; Make multiple photocopies of the
text,
Painstakingly
read through and assign codes to the material, Cut the pages up into coded
passages and then,
Manually
sort the coded text in order to analyze the patterns they find.
Qualitative
Analysis with Software
With
qualitative software, your workflow will be similar, but each step will be made
easier by the computer’s data storage capability, automated searching and display.
You can use text, picture, video and audio source files directly. You can
assign codes manually (auto-code) to any section of the text, audio or video or
part of a picture. Analysis is easy with the report feature, where you can
select a subset of cases and codes to work with, choose what data to use, and
sort your reports automatically
Uses
of Computer Software in Qualitative Studies
1. Transcribing data
2. Writing/editing the data.
3. Storage of data
4. Coding data (keywords or tags)
5. Search and retrieval of data.
6 .Data linking of related text.
7. Writing/editing memos about the data.
8. Display of selected reduced data.
9. Graphic mapping.
10. Preparing reports .
Common Qualitative Software
1. Atlas ti 6.0 (www.atlasti.com)
2. Hyper RESEARCH 2.8
(www.researchware.com)
3. Max QDA (www.maxqda.com)
4. The Ethnography 5.08
5. QSR N6 (www.qsrinternational.com)
6. QSR Nvivo (www.qsrinternational.com)
7. Weft QDA (www.pressure.to/qda)
8. Open code 3.4 (www8.umu.se)
Basic Steps in using Qualitative
Software
1. Install the program (note the
requirements),
2. Learn the operation using the help
menu)
3. Prepare a source document (in text
format),
4 Open a project/study unit/Hermeneutic
unit,
5. Import text, audio, video, picture
source files ,
6. Read the imported text documents,
7. Select the segment of the text,
8. Insert codes, catégories, memos,
quotation etc,
9. Search, sort, manage categories, manage
quotations etc,
10. Mapping of concepts, layering, linking
etc,
11. Producing reports, matrices, exporting
data, print.
Qualitative Reporting
Writing Qualitative Report
Qualitative
research generates rich information therefore deciding where to focus and the
level of sharing is very challenging.
Choosing
a Style and Focus
Format
Research report .
Scientific research article .
Report to donor .
Field report .
Evaluation report
Focus
Academic: conceptual
framework/theories, methodology and interpretation .
Practitioners: Concrete suggestions for
better practice, policy recommendations.
Lay readers: Problem solving, reform on
practice/policy.
Variations
in the Report Format
Problem-solving
approach (problem-based),
Narrative
approach (chronological),
Policy
approach (evidence-based),
Analytic
approach (Theory/conceptual framework based)
Reporting Qualitative Research
Typically
uses quotes from data Descriptive Direct link with data Credibility
Ways
to use quotes
Illustrative
Range of issues.
Opposing views
Interpretation
Interpretation
is the act of identifying and explaining the core meaning of the data. It is also
the act of organizing and connecting emerging themes, sub-themes and
contradictions to get the bigger picture of what it all means.
Think
how best to integrate data from multiple sources and methods, Make
generalization providing answers to questions of social and theoretical
significance, ensuring credible or trustworthy interpretations.
Standard Report Format
1. Introduction
Literature review.
Purpose of the study.
Brief description of the study (Who did
the study, where and when. Description of relevant cultural and contextual
information).
2. Methods: study design, sampling method,
data collection method, data analysis methods.
3. Results: Presentation, interpretation,
relate to relevant conceptual framework, discuss methodological difficulties
affecting your results.
4. Conclusion: Key findings, logical next
step, implication of findings.
5. Recommendations: Relate to policy or
practice.
6. Acknowledgement
7. References
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