Coding Qualitative Data,
By Dr. Sonja K. Foss and Dr. William Waters

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Devoted to practical steps for completing
your doctoral dissertation.

To subscribe, visit

1. Ben's Note
2. Coding Qualitative Data by
Dr. Sonja K. Foss & Dr. William Waters
3. Words of Wisdom
4. Request for ABDSG articles.

In this issue, Dr. Sonja K. Foss & Dr. William
Waters share some tips for coding and
analyzing qualitative data.

We round it out with Words of Wisdom, and a
request for ABDSG contributions.
Ben's Note

February 6, 2003

Dear ABD Survival Guide Reader,

Thanks to everyone who responded to our request
for contributions- we have many new topics and
unique offerings for future issues. If you'd
like to submit an article, we'd love to read it-
please see below for details.

Many of you have written in appreciation for
articles which focus on technical aspects of
writing the dissertation, so I'm especially
pleased to offer this week's focus on coding
and analyzing qualitative data.

As always, I trust that this will help you
continue to move forward, and get ever closer
to the finish line.

Keep up the great progress, and see you in
two weeks.


Coding & Analysis of Qualitative Data
By Dr. Sonja K. Foss and Dr. William Waters
The process of coding and analyzing data is a critical
part of qualitative dissertations because it is the
unique part--the part that enables you to make an
original contribution to your discipline. The
following system makes the process manageable
and almost insures that you will develop an original
and sophisticated answer to your research question
from your data. This system can be applied to
videotaped observations, interviews, written texts,
visual images, or any interpretable artifacts.

Step 1: Coding the Data

Go through the data looking for things pertinent
to answering the research question. The specificity
and concreteness of the research question tell you
what you're looking for. Your question suggests
what pieces need to be coded and what to leave
by the wayside for another question.

Write a paraphrase, phrase, heading, or label
that describes what you are seeing in that passage
or chunk or quote that is most important. The
label doesn't have to be very precise at this
time--it's just a general indicator. Label the
coded material with labels that don't just come
from the literature review or the research
question. New observations and insights should
produce new labels.

Do not bring in theories from your discipline
that seem relevant to your data at this point.
You should be tied to the data as you code, not
relating it to or categorizing it according to
theories you know about.

Avoid coding according to what you want to find
by remembering that you will have to explain how
you came to your claims and conclusions from the
data. Your claims will have to make sense to
someone else. To help yourself code in this way,
try to code the data as a complete novice--someone
with no extra knowledge, assumptions, or values
besides what's in the data. Also code with
skepticism by asking yourself: Do the data really
say this? Could I explain this to someone else using
only this text?

You might have interesting data that don't have
any bearing on your study. Put those in a "promise file"
--a file where you keep ideas for projects you want to
do later.

There is no one right story you should get out of the
data. Analysis is co-creating a story with the data,
not discovering a story.

Step 2: Developing Themes from the Data

Make another copy of the coded data.

On one of the copies, physically cut out the sections
you have labeled on your transcripts. Save the other
copy for future reference.

Sort the coded data into piles according to topics.
All of the chunks of data that have the same labels
or closely related labels should be put in the same
pile. Label each pile with a word or phrase that
captures the gist of what is going on in that pile.

Create a space where the piles can be laid out and
kept out. If you aren't able to do this, put the
piles into envelopes and label the envelopes.

Assess the piles by asking yourself questions such
as: Does everything in each pile relate to the
label you've given to the pile? Can some piles
be combined? Can some piles be deleted because
they are insignificant, don't relate to the
research question, or have very few pieces of
data in them?

Step 3: Develop a Conceptual Schema from the Data.

The conceptual schema ties the data together,
answers the research question, is coherent,
and goes beyond the obvious. This is the
critical step. This is what will enable you
to make an original contribution to the field.

Play around with different ways to organize your
themes to create a conceptual schema. Are some
of your themes major and some minor components
of a schema? Can you tell an interesting
narrative with your themes? Can you organize
the themes according to some kind of metaphor?
Can you describe the steps in a process and
create a name or acronym for the process?
What you want to avoid is ending the process
of coding with simply a list of themes. You are
aiming to do something with those themes
to make them into a theory.

This is a good place to elicit the help of
others. Talk through your ideas with someone
else to come up with your conceptual schema.

The process of creating a conceptual schema can
take a while. Be patient. Don't settle on the
most obvious schema only because you want to be done
with the process.

Step 4: Writing up the Analysis

Organize the piles in the order in which you
want to talk about the topics (the order in
which you want to explain your schema), then
take each pile in turn and sort it, organizing
and eliminating the data within it. Then lay
out the strips of paper in one pile and write
through the pile, connecting the strips with
your own thoughts and transitions.

The analysis should be written so that it's
driven by your conceptual schema--what you are
saying that is new. Theory and literature
should be used to support your ideas; they
should not be the heart of the conceptual
schema or function as the thesis sentences
of your paragraphs.

About Dr. Sonja K. Foss and
Dr. William Waters
Sonja is chair and professor of the Communication
Department at the University of Colorado at Denver.
William is assistant professor of English and the
Writing Program Coordinator at Northwest Missouri
State University. They are the directors of
Scholars' Retreat (or "dissertation camp"). This
is a week-long retreat that provides the opportunity
for intensive, focused, non-distracting, supervised
writing time so that you may make significant
progress toward the completion of your
dissertation or thesis.

During the retreat, Sonja and William provide
individual coaching to insure maximum productivity,
including assistance in unblocking writing blocks,
developing frameworks or research questions,
writing literature reviews efficiently,
coding qualitative data efficiently, analyzing
data to develop conceptual schemas, and
energizing and motivating.

The next Scholars' Retreat will be held in
June in Denver, Colorado. More information
about Scholars' Retreat is available at:
Web site:

Words of Wisdom from New Ph.D.'s.
** The selection of a thesis advisor is the
most important decision you can make in
graduate school. You can really not care
for your dissertation topic, but your
thesis advisor is the one who can make you
love or hate your life while working on it.
Also, listen to the advice of the more-senior
graduate students. If they say someone
is a bad advisor, they generally have some
good data to back it up. If they suggest
you are taking too many classes, they probably
know from experience. They are an invaluable

Request for ABDSG Articles
Do you have some knowledge or wisdom about the
dissertation process that you'd like to share?
If so, please consider writing an article for
this newsletter. We are currently accepting
articles about the dissertation
process. If you'd like to submit an article,
or would like more information, please email with ABDSG submission in
the subject line. Thank you!

BEN J. DEAN, Publisher, ABDSG
Ben holds a Ph.D. in psychology from the University of
Texas at Austin and is a psychologist in private
practice in Bethesda, Maryland.

In addition to his clinical practice, Ben loves to train
professionals to become virtual coaches. (If you would like
to see Ben's *other* free newsletter, you may subscribe at:

Ben lives in suburban Maryland with his wife and two
young children.


I'm a dissertation coach and licensed psychologist
based in Maryland, with a doctorate from the
University of Denver.

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