1. Running head: CODING PROJECT REPORT 1 (version 1.01)
Unit 4 Individual Project
Coding Project Report of Virtual Interview Question Responses
ThienSi (TS) Le
Colorado Technical University
RES 812-1503C-02: Qualitative Research Methods
Professor: Dr. Kathleen Hargiss
August 24, 2015

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Abstract
The paper in Unit 4 Individual Project (U4 IP) bases upon a qualitative data coding
process that includes coding and summarizing the responses from classmates in the
Course RES812 -1503C-02 Qualitative Research Methods. The transcript for an analysis
consists of eleven classmates’ responses to the virtual interview question posed in the
earlier Phase 3 Discussion Board 3: Capturing Qualitative Data Virtually. The virtual
interview question was
“Explain what being a doctoral student means for you. How has your life changed since
starting your doctoral journey?”
This paper is a coding project report that includes:
 Description of the coding process.
 Topical coding scheme (list of topics; code book).
 Diagram of findings (topics and themes).
 Brief narrative summary of findings referring to the graphic diagram (table).
 Appendix with coded transcripts in one of the following formats:
 A Word document showing color-coded codes
 A Word document using the comments function to indicate codes
 An output file from qualitative software
Keywords: Accuracy; central research question; cohort; consistency; data coding
process; dissertation; experience; goal; honor; knowledge; research; reward; time
management.

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Title
Coding Project Report of Virtual Interview Question Responses
This paper is a coding project report of the qualitative data coding process. It
bases on the responses from thirteen participant classmates on the virtual interview
question (stated in the Abstract section above) assigned in Unit 3 Discussion Board.
Following the qualitative data coding process assigned to Unit 3 Discussion Board 3, this
paper provides a coding project report that consists of
A. Description of the coding process.
B. Topical coding scheme.
C. Tables of findings.
D. Brief narrative summary of findings
E. Summary.
F. Appendix with code transcripts in a word document using the comments
function to indicate the codes.
A. Description of the coding process:
The qualitative (Ql) data coding process can be divided into four stages:
- Preparation of data
- An initial coding phase
- A second coding phase
- A method to ensure the reliability of the coding process.
1. Preparation of data:

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To organize and prepare the data for analysis, a researcher needs to transcribe
interviews, optically scan material, type up field notes, catalogue all of the visual
material, and sort and arrange the data into various types of depending on the sources of
information (Creswell, 2014). For example, organizing data types in Big Data bases on e-
commerce, e-government, science and technology, smart health, security and public
safety. A researcher should read all the data for general sense of information and reflect
on overall meaning.
2. An initial coding phase:
This initial phase mostly focuses on topical coding and the recording notes.
Coding is the process of organizing the data by bracketing chunks and writing
word that represents a category in the margins (Rossman & Rallis, 2012). It relates to
- taking text data, pictures, etc.
- segmenting sentences, paragraphs, images into categories.
- labeling these categories with a term based on the actual language (vivo term)
of the participants.
The codes on topics are for readers who would expect to find, based on the
past literature and common sense (Lofland & Lofland, 2006). Codes that are surprising
and were not anticipated at the beginning of the study make readers pay more attention.
Codes that are unusual are conceptual interests to readers.
3. A second coding phase:

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The second phase focuses on themes or pattern identification. The coding
process is used to generate a description of the setting or people as well as categories or
themes for analysis (Bryman & Bell, 2011). A researcher may
- develop the codes on the emerging information collected from the
participants,
- use predetermined codes and then fit data to them.
- use some combinations of emerging information and predetermined codes.
He/she can develop a qualitative codebook that contains a list of predetermined
codes such as code definitions for coding the data.
4. Methods to ensure reliability of the coding process:
A researcher considers taking some steps in the study to check for accuracy
and creditability of the findings. Qualitative validity requires a researcher to check for
validity by using a certain procedure. Validity means trustworthiness, authenticity, and
credibility (Rubin & Rubin, 2011). On the other hand, qualitative reliability requires that
the approach in Ql design is consistent across numerous researchers and different projects
(Gibbs, 2007). Creswell (2014) suggested some methods of the qualitative reliability in
four procedures below:
a. Checking transcripts to make sure that there are no obvious mistakes made
during transcription.
b. Ensure that there is no drift in the definitions of codes, a shift in the
meaning of the codes during coding process by constantly comparing data with the codes
and writing memos about the codes.

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c. For team research, coordinate the communication meetings among the coders
on the analysis.
d. Comparing the results that are independently derived by cross-checking the
codes developed by research members.
The coding process in this report is simplified as follows:
- Create a transcript from captured data in qualitative interviews.
- Carefully read the transcript, take notes, and add comments.
- Analyze qualitative data.
- Do coding on captured interview data.
- Develop a diagram of findings.
- Prepare tables.
- Write the coding project report.
B. Topical coding scheme:
Responses to the virtual interview question on Unit 3 Discussion Board (U3
DB):
This part is a list of topics:
1. Gain knowledge
2. Gain experience
3. Time management
4. Better person
5. Better researcher
6. Cohort

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7. Pride
8. Rewards
9. Contribute the body of the knowledge
10. Hard work
11. Financial problem
12. Personal problems
Data analysis and code definition are listed in section C. Tables of Findings
below.
Responses to qualitative data coding process on Unit 3 Discussion Board 3 (U3
DB3):
The topics are found in four stages as follows:
1. Data preparation:
In this stage, the topics are creating transcripts, identifying data, organizing
data, interpreting data, reducing data, categorizing data, and availability of data.
2. Initial phase coding:
This stage includes finding topical data, understanding data, representing
words on data, corrected data, labeling data, coding definition.
3. Second phase coding:
This stage focuses on themes, identifying the patterns, data characteristics,
data categories, data significance, data stability and codebook.
4. Reliability:

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This stage emphasizes on data validity, credibility, accuracy, consistency,
clarifications, cross-checking codes, using software tools such as Nvivo Atlas.ti.
C. Tables of findings - Themes
The result of the data analysis through data coding process shows that doctoral
students are professionals who motivate themselves toward the doctorate. They are eager
to learn new concepts, up-to-date technologies and do a research study. With number of
counts in each category in the Table 2 below, five themes can be drawn as follows:
1. An ambition of gaining knowledge through the highest level of education with the
highest counts (i.e., 8) in the category of Knowledge Gain.
2. Time management received six counts. Participants know how to manage time well
and appropriately in a research study, family, work and their personal pleasure.
3. A desire of obtaining practical experience to promote themselves in their career
with five counts in the category of Experience Gain.
4. With three counts, a positive reflection on participants’ personality such as well-
educated persons, better researchers, pride, cohort, and reward from the research study.
5. With two counts, a negative feedback on participants’ sacrifice such as lack of
spouse’s support, hardship, spending less time with family during the study.
Topics and themes were found in this coding process are populated in three
primary tables as shown below:
Table 1: The classmates’ responses on the virtual interview question in U3 DB.

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Table 2: Code definition of the responses from the classmates on U3 DB Virtual
interview questions. Some responses to each category are listed in the right-hand side
column. For example, the code GK (Gain Knowledge) receives the most number (8) of
responses by the participants.

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Table 3: The classmates’ responses and codes on virtual interview question in U3 DB.
Table 4: Coding the responses from classmates on qualitative data coding process in
U3 DB3.

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Table 5: The classmates’ responses and codes on qualitative data coding process in U3
DB3.
Table 6: Code definition of the responses from the classmates on data coding process in
U3 DB3

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Table 7: Code definitions for U3 DB3
Table 7:
Code Definitions Ac Accuracy
Av Availability of data
C Categorizing data
Ca Data categories
Cb Codebook
Cd Code definitions
Cc
Cross-checking
codes
Ch
Data
characteristsics
Co Correlated data
Cr Credibility
Cl Clarification
L Labeling data
Id Identifying data
In Interpreting data
O Organizing data
P
Pattern
identification
R Reducing data
Rw Representing words
S Data significance
St Data significance
Sw Software tools
T Transcripts
Th Themes
To Topical data
Tr Traceability
Ty Data types
U Understading data
V Validity

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D. Brief narrative summary of findings
The responses of thirteen participants on the virtual interview question indicate
that
the findings are quite interesting.
1. The highest number of responses is eight on the category of gaining
knowledge. It shows that the doctoral students are hungry for knowledge. They want to
know more about research and technologies.
2. The category of gaining experience receives the response number of five –
the second highest. Participants who are mostly professionals need more practical
application experience.
3. The number of responses is three for four categories: Better educated person,
super researcher, pride, and cohort.
4. Seven categories that receive two responses are
- Positive responses: Contributing to the knowledge body, improving
communication, learning dissertation.
- Negative responses: disease, financial problem, less time spent with family,
less pleasure time,
5. And eight categories receive one response each:
- Positive responses: accomplishing the goal, growth edge, honor, improving
technology, knowing processes, using the new approach, a new opportunity.
- Negative response: divorce.

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Notice that the analysis result of qualitative data coding process in U3 DB3 is not
finished yet due to limited time constraint. It is left open for future completion.
E. Summary
The document of Unit 4 Individual Project presents the results of the coding
process, using matrix format tables to display the qualitative findings graphically. It
consists of
A. Description of the coding process.
B. Topical coding scheme (list of topics; code book).
C. Tables of Findings (topics and themes).
D. Brief narrative summary of findings referring to the graphic diagram
(table).
E. Appendix with coded transcripts in the following formats:
a. A power point document is showing color-coded codes.
b. A Word document using the comments function to indicate codes.
c. An output file from qualitative software
F. Appendix
Appendix section includes coded transcripts in the following formats:
a. A power point document showing color-coded codes:
Refer to Coding Tables.
.

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b. A Word document using the comments function to indicate codes.
Refer to the attachments: RES812U4IP-U3 DB-Document,
RES812U4IP-U3 DB3-Document.
c. An output file from qualitative software:
The NVivo10 project was created as shown below, but the work was
not complete yet.

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REFERENCES:
Bryman, A., & Bell, E. (2011). Planning a research project and formulating
research questions. In Business research methods. Cambridge: Oxford University
Press.
Creswell, J. W. (2014). Research design: qualitative, quantitative, and mixed methods
approaches. Sage publications
Hargiss, K (2015). Qualitative Research. Presentation presented at chat session 7 of the
Course RES812-1503C-02: Qualitative Research Methods. Colorado Technical
University.
Rubin, H. J., & Rubin, I. S. (2011). Qualitative interviewing: The art of hearing data.
Sage.