Research Paper Writing
Mavis Shang
97年度第二學期
Section VII
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Data Analysis, Interpretation, and Reporting
I. Qualitative analytic strategies:
A. Recursive process:
→ analyze cases→ generate findings→ draw conclusion
→ form grounded theory → write report
B. Nine qualitative data analysis principles:
1. Collect the data at the site and carefully study all the
data to seek similarities and differences, concepts
and reflections
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Data Analysis, Interpretation, and Reporting
2. Saturation and sufficiency of information: Never stop
data analysis until the emergence of regularities; i.e.,
no new information emerges with additional data
analysis
3. Accountability of information: Keep notes or
transcripts if outsiders want to review the data analysis
procedures and results
4. Divide the data (excerpts) into smaller units related to
your major points
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Data Analysis, Interpretation, and Reporting
5. Organize the smaller units into categories (based on
major points)
6. Build conceptual similarities, find negative evidences,
and discover patterns
7. Modify categories as further patterns occur
8. Analyze negative cases to reflect their perceptions
9. Synthesize the patterns into the grounded theory
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Data Analysis, Interpretation, and Reporting
* SHOULD BE:
- connected with what is being discussed in the
major points
- exact wording (excerpts) used in the statement
* SHOULD NOT BE:
- based on interviewer’s personal opinions
- irrelevant to the major points
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Data Analysis, Interpretation, and Reporting
C. Six Steps in Qualitative Data Analysis:
1. Give codes from the notes (transcripts)
2. Note personal reflections or other minority’s comments
3. Sort the notes to identify similar and different
relationships between patterns
4. Identify these patterns, similarities, and differences
5. Elaborate a small set of generalizations that cover the
consistencies
6. Examine those generalizations and form grounded theory
(see “Content Analysis”)
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Data Analysis, Interpretation, and Reporting
Grounded Theory (紮根理論):
→ a process of constructing various data
→ inductive process by collecting, analyzing, and
comparing data systematically
→ theory is grounded on data to explain the
phenomena
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Grounded Theory (by Marlene Pomrenke)
Grounded theory is a method of social inquiry associated
with a qualitative approach to research. This inductive research
process utilizes generalized knowledge that is derived from
specific observations of phenomena from the field. In turn, this
can be used to build theory. For example, grounded theorists
aim to create theoretical categories from collected data and then
analyze relationships between key categories (Charmaz, 1990).
Indeed, the main purpose of using a grounded theory approach
is to develop theory through understanding concepts that are
related by means of statements of relationships (Strauss &
Corbin, 1990). Using the concepts from grounded theory, this
study starts from understanding the experience of the research
participants (i.e., how they construct their worlds). The data
analysis stage focused on finding recurrent themes or issues in
the data, and finally into developing or refining a theory about
the phenomenon.
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Data Analysis, Interpretation, and Reporting
D. Grounded Theory Analysis Strategies:
1. Recur by moving back and forth with the data,
analyzing, collecting more data, and analyzing some
more until reaching conclusions
2. An interactional method of theory building by
comparing and analyzing the data
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Data Analysis, Interpretation, and Reporting
3. Three steps in the grounded theory analytic (coding) process:
(1) Open coding: Break data into small parts → compare for
similarities and differences → explain the meanings of the
data by focusing on “who, when, where, what, how much,
why” (ask questions to get a clear story)
(2) Axial coding: After open coding, make connections (sort)
between categories and confirm or disconfirm your
hypotheses
(3) Selective coding: Select the core category (match
hypotheses) and explain the minor category (against
hypotheses) with additional supporting data
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Coding Process

Open Coding
MP 1

Axial Coding

Selective Coding
MP 2
MP 1
MP 3
MP 3
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Participant #1 Ah…I do not think I improve grammar and
word dictions because my teacher did not correct my
grammar and word dictions. Actually, I know I am not
good at writing, and I really want to improve my writing
ability. Hmm……However, I also wrote articles which
were asked from professors as homework while I wrote
dialogue journal writing. Well, for the first time, I can
accept that I had so many writing mistakes, and I know I
still have room to improve it after teacher’s correction.
Unfortunately, after many times corrections, the articles
which were corrected by professors still appeared many
grammar problems and sometimes had word dictions
problems. This is why I do not think dialogue journal
writing can improve our writing ability. (Shake head)
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Data Analysis, Interpretation, and Reporting
II. Interpretation Issues in Qualitative Data analysis:
A. Triangulating data: Use multiple methods and
data sources to support the strength of
interpretations and conclusion (e.g., semi-
structured interviews, consent form, grounded
theory, etc.)
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Data Analysis, Interpretation, and Reporting
B. Audits: Questions to examine the data for
interpretations and conclusion
1. Is sampling appropriate to ground the findings?
2. Are coding strategies applied correctly?
3. Is the category process appropriate?
4. Do the results link hypotheses?
5. Are the negative cases explained?
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Data Analysis, Interpretation, and Reporting
* Four steps of negative case testing:
1. Make a rough hypothesis
2. Conduct a thorough search
3. Discard or reformulate hypothesis
4. Examine all relevant cases
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Data Analysis, Interpretation, and Reporting
C. Cultural bias: Discuss cultural differences with
different groups of participants (compare the
differences between western and Taiwanese students’
attitudes)
D. Generalization: Not appropriate for qualitative research
1. Case-to-case transferability by providing thick
description to apply to another setting
2. Generalize the result to a broader theory (e.g., use
deviant cases)
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Data Analysis, Interpretation, and Reporting
III. Writing Research Reports:
A. Introduction
B. Literature Review
C. Methodology
D. Results: Tie the results to study purpose
(hypotheses)
E. Discussions and Conclusion: Tie discussions to
the literature; recommendations for practice;
limitations of the study
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Data Analysis, Interpretation, and Reporting
Quantitative reports:
• Report results by the use of tables and graphs
• Avoid first-person pronoun
• Use passive voice
Qualitative reports:
• Look for a deep description (narrative style)
• Look for well-grounded theory
• Seek contextual meaning by understanding demographic
information (different experiences)
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