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Coding Qualitative Data, By Dr. Sonja K. Foss and Dr. William Waters [|Previous Page]

THE ALL-BUT-DISSERTATION SURVIVAL GUIDE(tm) Devoted to practical steps for completing your doctoral dissertation. [|www.ecoach.com]. To subscribe, visit [|www.ecoach.com] INDEX 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. SUMMARY 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. Warmly, Ben 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: [|http://www.SonjaFoss.com] E-mail: Sonja.Foss@cudenver.edu 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 resource. 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 rachna@mentorcoach.com 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. RACHNA D. JAIN, Editor, ABDSG I'm a dissertation coach and licensed psychologist based in Maryland, with a doctorate from the University of Denver. I'm the Editor of the ABDSG, as well as the Author of "Get It Done! A Coach's Guide to Dissertation Success" If you'd like to learn more about me or my book, please visit my website: [|www.ExcelWithEaseCoaching.com] If you have questions about this newsletter, you can direct them to me: rachna@mentorcoach.com I'm excited to be working with you to meet your academic goals. You can do it! THE ALL-BUT-DISSERTATION SURVIVAL GUIDE(tm). "The All-But-Dissertation Survival Guide"(tm) focuses on ways to help its readers more readily overcome the roadblocks that often seem to stand in the way of completing the dissertation. It is read throughout the world. VIRTUAL ABD ASSISTANCE Would you like a "virtual assistant" who did whatever you needed to help you move forward on your scholarly work or on other parts of your life. 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