NORMAN, ELTON_BUS7380-8-62NORMAN, ELTON_BUS7380-8-61.docx

NORMAN, ELTON_BUS7380-8-6 2
Analyze Qualitative Data
BUS-7380 Assignment # 6
Elton Norman
Dr. Vicki Lindsay
9 November 2019
Greetings Elton,
Using the same research design that you selected for the Week 5
assignment, you were to take 2-4 pages and consider the type of
data collected to create procedures for a comprehensive
analysis. Clearly define your approach to: (a) organizing data;
(b) coding and thematic development; (c) triangulation; and (d)
using software applications.
***************

The feedback process consisted of a four-part summary (four-
parts listed below), a few short, location-specific balloon-
comments found within the margins of the text, and the
highlighting of grammar, punctuation, or APA styling errors
found within the text. Make sure that you view your document
with the track changes (review toolbar) set to ALL MARKUP to
be able to see all the comments.
The summary is split into four parts. These four parts consist
of grammar/punctuation, conformity with APA style citations,
conformity with APA style references, and content. The order of
the parts listed does not intend to emphasize the importance of
the parts as the content is always the most important part of the
assignment. Therefore, it is listed in the end because normal
memory concentrates on what was heard / read last.
What was found:
Grammar/ Punctuation
There were a few grammar or punctuation errors found within.
There were problems in spelling, missing punctuation leading to
run on sentences, missing punctuation leading to grammatical
issues, and the agreement issues between words (i.e.,
subject/verb agreement and numerical plural numbers without
plural noun). Make sure that you read your work prior to
submission so that you will not have run on sentences within
your work. Pay attention to the word “and” within your work.
APA style citations
The citations present were in APA format. You seem to be
missing the additional 3 scholarly sources from your field that
were required within this assignment.
APA style references
Not enough information was included within your references to
make them correct APA references. You are missing page
numbers, volume, issue number, and the digital object identifier
for your journal article sources. Your book title should be in
italics. The publisher should not. All of the titles should be in
sentence case not in title case. This is not a problem with the
software program. This is a problem with the keypunch issue.

Your program cannot change lowercase letters into uppercase
letters in vice versa. You must be it incorrectly for it to
properly appear. Many have problems with this thought process.
Do not leave it up to the software program to correct keypunch
errors.
Content
The same problem that you had an assignment 5 appeared in
assignment 6. You are not explaining how these research
designs will fit with your research questions or problems
statement as you move forward through the data collection
process. Without doing this correctly, you will have problems
with your signature assignment, assignment 7. You need to
continue to read your assignment in detail. The assignment
stated that the student should create this assignment in a manner
consistent with the other assignments such as:
your approach must be systematic, logical, fully explained, and
supported with scholarly sources. Use the resources provided,
and at least three other peer-reviewed articles to defend your
research plan.
Note that the statement, " defend your research plan" means that
you should have used your research designs -- grounded Theory
and case study -- to develop a data collection process for your
research questions or problem statement. Do not overlook that
you should have used the required reading as well as three
additional scholarly sources from your field to show that this
happens within your field.
As before a rewrite is not required but it is recommended. You
have the basic information present. You now have to form the
details to show what would occur within your project to collect
data using these research designs.
If you have any questions about any part of this, please feel free
to contact me via Skype or NCU email.
Revise and resubmit. Submit by last date of class.
V. Lindsay, PhD 3.5/10 11/14/19

Research Design and Data Collection
The research design that I am going to use for this assignment is
the qualitative research design, as used in my assignment of
week 5. Qualitative research designs may take various forms as
I had illustrated, the first one being the grounded theory, which
is used as a different approach for the developing theories, as
arising from an established relationship after the process of data
collection and analysis. This theory arises after a systematic
gathering of data (Patten, 2017). The other form of qualitative
data is case studies. This design analyses a set of issues within
the limits of a given organization, situation, environment and so
on. A case study may take the form of explanatory, exploratory
or descriptive design. Comment by Vicki Lindsay, PhD: No
first- or second-person view in an APA style paper written for
NCU. APA only allows the first-person view within certain
areas of the methodology. APA does not allow second person
view within a scholarly paper. NCU does not condone the use of
first- or second-person view within work that is submitted. If I
see any use of these voices, I will highlight them from now
forward. Comment by Vicki Lindsay, PhD: This course is
qualitative research. You are studying the different types of
designs in qualitative research. You need to explain which of
the 5 research designs you are using for your data collection. In

assignment 5, you should have explained 2 different research
designs. This assignment is asking you to use those two designs
and describe the collection of the data as a researcher would go
forward with your research question or problem statement.
Comment by Vicki Lindsay, PhD: This is your research
design that you should be naming at the beginning.
Data collected
Data collection in grounded theory was based on observation
notes by the participant through getting engaged in people's
daily activities and the subjects in question. Data was also
collected through interviewing the subjects. The use of texts
and artifacts was as well used to gather data. In the case of
study, data was collected was on the description of a situation
by a subject, and answered the question of how and why. The
explanation was based on a real-life event, and as well used the
question who and what.
Organizing Data
Qualitative research comes up with a wide range of data that is
derived from various sources like interviews, observation notes,
questionnaires, and official documents. Due to a wide range of
respondents as well as the participants well as a variety of
researchers, it is important to classify and organize data to make
its understanding easier (Creswell, 2013). The following five
steps are the steps involved in organizing data.
1. Reviewing the whole set of data so to bring out themes or
patterns, which are then assigned symbols or numbers to make it
easier for the analysis.
2. Creating a table for the codes to ensure that there is
consistency in the codes and that such codes are accessible from
several researchers.
3. Classifying data into various groups according to various
codes, make easier for the analysis and discussion. This may
focus on themes that are independent as recorded in the data.
4. Organizing the data survey inform of a sub-topic or question
to analyses data easily. This organization may take the form of
question or subtopic

5. Coding the already transcribed data and labeling it to make
data readily evident. In this case, it would be easy for a
researcher to access information which has been analyzed,
grouped and transcribed.
Coding and thematic development
In qualitative research, coding refers to the main method that is
used in the development of themes or the patterns of meaning in
data classification (Saldana, 2015). Thematic development is
concerned with examining themes or general patterns within
data analysis. In this case, coding defines the data being
analyzations process identifies a passage within a text or any
item of data like an image or a photograph, getting the concepts
and looking for the relationship that exists between them.
Coding is therefore seen as the process of linking data to an
idea. In my case, concept and data-driven codes are being used
to getting an idea from the research data. Thematic
development, on the other hand, enroots on identification and
interpretation of the pattern of meaning or themes used in the
research work (Ryan, 2016). In my case, this was done through
discourse analysis after the interviews and interpreting the
observational notes. coding and thematic development make it
easier to understand data.
Triangulation
This is the process of using a variety of data sources to make
data comprehension easier. Triangulation also has found to test
data validity through the convergence of given information from
many sources. In this case, many methods are used to collect
data to ensure data validity. Triangulation also increases a
reader's knowledge as information is availed from different
sources (Rothbauer, 2015). In my example, I have triangulated
my qualitative study in data collection, where I used ground
theory and the case study, to come up with more information on
the research. This has helped widen the scope of research.
Using software applications
It is important to use software for qualitative analysis of data.
This software system helps in processing discourse analysis,

content analysis, text interpretation coding of information and
interpreting information to enable a person to make informed
decisions. In this case, I will use the SPSS software program for
my qualitative research study.
References
Creswell, J. (2013). Qualitative Inquary & Research Design:
Choosing Among the Five Approaches. Thousand Oaks, CA:
SAGE Publications, Inc., 78.
Patten, M. &. (2017). Understanding Research Methods: An
overview of the essentials. Routledge, 52.
Rothbauer, P. (2015). Triangulation: Qualitative Research
Methods. Sage Publications, 891.
Ryan, G. a. (2016). Techniques to Identify Themes. Field
Methods, 95.
Saldana, J. (2015). The Coding Manual for Qualitative
Researchers (3rd edition). SAGE Publications Ltd.
Copyright © 2015. F.A. Davis Company
Chapter 21
Katharine Kolcaba’s Theory of Comfort
Developed by S . Gordon (2010)
Updated by D. Gullett (2014)

*
On completion of this chapter, students will be able to:
Describe Kolcaba’s Theory of Comfort care.
Identify the theorists who influenced the development of
Comfort theory.
Define the terms comfort, comforting care, comfort
management, and comfort interventions from the perspective of
Comfort Theory.
Discuss the meaning of Comfort Theory for practice.
Identify the different tools used to measure comfort.
Discuss the propositions of Comfort Theory and their
application to practice.
Define the theoretical definitions of diagram concepts for the
Comfort Theory.
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Overview of the TheoristKatherine KolcabaBorn/educated in
Cleveland, OhioReceived a diploma in nursingGraduated 1st
RN-MSN class at Case WesternJoined Faculty of University of
AkronAssociate Professor Emeritus at University Akron
*

Overview (continued)Practice focused on gerontology and
dementia careFramework for dementia care (1992)Diagrammed
aspects of comfort (1991)Operationalized comfort as an
outcome of care (1992)Published book Comfort Theory and
Practice (2003)
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Overview of Comfort Theory (CT)Comfort defined
as:NounAdjectiveOutcome of intentional, patient/family-
focused quality care
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Comfort: To strengthen greatly
The need for comfort is basic.Persons experience comfort
holistically.Self-comforting measures can be healthy or
unhealthy.Enhanced comfort leads to greater productivity.
*

Kolcaba Influenced byOrlandoSynthesized reliefNurses relieve
needsHendersonSynthesized ease 13 basic functions of human
beingsPaterson and ZderadTranscendence
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Four Contexts of Patient
ComfortPhysicalPsychospiritualSocioculturalEnvironmental
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Outcome of Comfort“The immediate experience of being
strengthened when needs for relief, ease and transcendence are
met in 4 contexts of experience.”
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Uses of Comfort Taxonomic StructureDetermine the existence
and extent of unmet comfort needsDesign comforting
interventionsCreate measurements of holistic comfort
*

Propositions of Comfort TheoryPart I Effective comforting
interventions result in increased comfort for recipients (patients
and families) when compared to a preintervention baseline.Part
IIIncreased comfort of recipients results in their being
strengthened for their tasks ahead (health-seeking behaviors).
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Propositions of Comfort TheoryPart III:Increased engagement in
health-seeking behaviors results in increased Institutional
Integrity.
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Diagram ConceptsHealth-Care NeedsNeeds for comfort arising
from stressful health-care situations that cannot be bet by
recipients’ traditional support systems
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Diagram ConceptsComfort InterventionsNursing actions

designed to address specific comfort needs of recipients: social,
cultural, financial, psychological, environmental, and physical
interventionsIntervening variablesInteracting forces that
influence recipients’ perception of total comfortPast experience,
age, attitude, emotional state, support system, prognosis ,
finances, education, cultural background and the tonality of
elements in recipients’ experience.
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Diagram Concepts (continued)ComfortThe state that is
experienced immediately by recipients of comfort
interventionsHolistic experience of being strengthenedHealth-
Seeking Behaviors (HSBs)Broad subsequent outcomes related to
the pursuit of health (synthesized by Scholfeldt,
1975).InternalExternal
*
Diagram Concepts (continued)Institutional
IntegrityCorporations, communities, school, hospitals, regions,
states, and countries that possess qualities of being complete,
whole, sound, upright, appealing, ethical, and sincere Best
PracticesHealth-care interventions that provide the best possible
patient/family outcomes based on empirical evidenceBest
Policies Basic protocols from procedures to access and care
delivery systems based on empirical evidence

*
Types of Comforting InterventionsTechnical
Intervention:Specified by other
disciplinesMedicationsTreatmentsMonitoring schedulesInsertion
of lines
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Types of Comforting InterventionsCoachingSupportive nursing
actionsActive listeningReferrals to other members of the health-
care teamAdvocacyReassurance
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Types of Comforting InterventionsComfort Food for the
SoulExtra special, holistic and more time-consuming nursing
interventionsBack or hand massageGuided imageryMusic or art
therapyWalks outsideSpecial arrangements for family members
*

How Comfort Theory Lives in PracticeBest PracticesElectronic
DatabaseBest Policies
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Tools Used to Measure ComfortGeneral Comfort
QuestionnaireComfort Behaviors ChecklistComfort
DaisiesVerbal Rating ScaleMany other tools can be found at the
following website
http://www.thecomfortline.com/webinstruments.html
*
Summary“Comfort Theory provides the language and rational to
once again claim and document essential nursing activities
which are most beneficial to patients and family members in
stressful health-care situations.”
*
References
Kolcaba, K. (1991). A taxonomic structure for the concept

comfort. Image: The Journal of Nursing Scholarship,
23(4), 237–240.
Kolcaba, K. (1992a). The concept of comfort in an
environmental framework. Journal of Gerontological Nursing,
18(6), 33–38.
Kolcaba, K. (1992b). Holistic comfort: Operationalizing the
construct as a nurse-sensitive outcome. ANS
Advances in Nursing Science, 15(1), 1–10.
Kolcaba, K. (2003). Comfort theory and practice: A vision for
holistic health care and research (pp. 113–124).
New York: Springer.
Schlotfeldt, R. (1975). The need for a conceptual framework.
In: P. Verhonic (Ed.), Nursing Research (pp. 3–
25). Boston: Little, Brown.
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Chapter 22

Joanne Duffy’s Quality Caring Model
Developed by S. Gordon (2010)
Updated by D. Gullett (2014)
*
On completion of this chapter, students will be able to:
Describe Duffy’s Quality-Caring Model.
Discuss the progression of the development of the Quality-
Caring Model.
Discuss the role of the nurse in providing quality care using the
Quality-Caring Model.
Identify caring-based nursing interventions.
Discuss the importance of caring relationships in nursing.
Describe Duffy’s used of the term “feeling cared for.”
Explain recent changes in the model.
Describe how the model is being used in nursing practice and
research.
*
About the TheoristJoanne R. Duffy PhD, RN, FAANSt. Joseph’s
Hospital School of Nursing, Providence, RIBSN Salve Regina
College, Newport, RI Master’s and PhD Catholic University in
Washington, DCProfessor at Indiana University School of
NursingAssociate Director of NursingGeorge Washington
University Medical CenterGeorgetown University Medical

CenterDeveloped Cardiovascular Center for Outcome
AnalysisAdminister the Transplant Center at INOVA Fairfax
Hospital in Virginia
*
About the Theorist (Continued)
First to examine the link between nurse caring behaviors and
patient outcomesDeveloped the Caring Assessment
ToolInterested in the hidden value of nursing workDeveloped
the Quality-Caring ModelExplores approaches to relationship
building
*
Quality–Caring Model (2003) PurposeTo guide practice and
researchPrompted during discussions concerning nursing
interventionsInformed from earlier work on caringPatient
perceptions that “nurses just don’t seem to care”
*
Quality Caring ModelThe model has been revised twice (once in
2009 and again in this most recent 2013 version) to meet the

demands of the multifaceted, interdependent and global health
system. In this revised version, the link between caring
relationships and quality care is even more explicit, challenging
the nursing profession to use caring relationships as the basis
for daily practice
*
Quality–Caring Model BackgroundFew nursing theories that
could guideDevelopment of caring-based nursing
interventionsSpeak to the relationship between nurse caring and
qualityInitial testing with a group of patients with heart failure
*
Core Concept
Caring relationshipsHidden in the daily work of nursingNurse
caring different from caring between relatives and friendsNurse
caring requires Specialized knowledge, attitudes, and behaviors
directed toward health and healing
*
Nurse CaringAssists recipients to feel “cared for”Freeing

recipients to:Take risksLearn new healthy behaviorsParticipate
in evidence-based decisions
*
Feeling “Cared For”Necessary to influence outcomesNurse-
sensitive outcomes:Knowledge-SafetyComfort-Anxiety
Adherence-Human DignityHealth-Satisfaction
*
Major Purposes of Quality-Caring ModelGuide professional
practiceDescribe linkages between quality of care and human
caringFoundation for nursing research
*
Quality-Caring ModelDuffy considers the model Middle
RangeViews quality as:DynamicNonlinearEnhanced by caring
relationships
*

Main ConceptsHumans in relationshipHumans are unique,
multidimensional beingsImportant to recognized how humans
are different and the sameSocial beings connected to
othersHumans mature, enhance community, and advance
through human connections
*
Main Concepts (continued)Relationship-centered professional
encountersIndependent between nurse and
patient/familyCollaborative between nurses and members of
health-care teamOutcome is “feeling cared for”“Feeling cared
for”Nurse-sensitive/Positive emotionSignifies to patients and
families that they matterAllows patients/families to relax and
feel secureAntecedent to quality health outcomesNurse-
sensitive outcomes
*
Main Concepts (continued)
Self-advancing systemsIt is a phenomenon that emerges
gradually over time and in space reflecting dynamic positive
progress that enhances the systems’ well-being. Self-advancing
systems are stimulated by caring relationships, but the forward
movement itself cannot be controlled directly; rather, it emerges

over time, driven by caring connections.
*
AssumptionsHumans are:Multidimensional beings capable of
growth and changeExist in relationship to themselves, others,
communities or groups, and natureEvolve over timeInherently
worthyCaring is:Embedded in the daily work of nursingA
tangible concept that can be measuredDone in
relationshipConsists of processes that are used individually or
in combination and often concurrently
*
Assumptions (continued)Caring relationships:Benefit both the
carer and the one being cared forBenefit societyProfessional
nursing work is done in the context of human
relationshipsFeeling cared for is a positive emotion
*
Propositions Human caring capacity can be developedCaring
relationships:Are composed of process or factors that can be
observedRequire intent, choice, specialized knowledge and

skills, and timeEngagement in communities through caring
relationships enhances self-caringIndependent caring
relationships between patients and nurses influence feeling
“cared for”
*
Propositions (continued)Collaborative caring relationships
among nurses and health-care team members influence feeling
“cared for”Caring relationships facilitate growth and
changeFeeling “cared for”:Is an antecedent to self-advancing
systemsInfluence is the attainment of immediate and terminal
health outcomes
*
Propositions (continued)Self-advancement is a:Nonlinear,
complex process that emerges over time and in space Self-
advancing systems are:Naturally self-caring or self-
healingCaring relationships contribute to:Individual, group, and
system self-advancement
*

Role of the NurseAttain and continuously advance knowledge
and expertise in caring processes.Initiate, cultivate, and sustain
caring relationships with patients and families.Initiate,
cultivate, and sustain caring relationships with other nurses and
all members of the health care team.Maintain an ongoing
awareness of the patient/family point of view.Carry on self-
caring activities, including personal and professional
development.Integrate caring relationships with specific
evidenced-based nursing interventions to positively influence
health outcomes.Engage in continuous learning and practice-
based research.Use the expertise of caring relationships
embedded in nursing, to actively participate in community
groups.
*
Role of the nurse (cont)Contribute to the knowledge of caring
and, ultimately, the profession of nursing using all forms of
knowing.Maintain an open, flexible approach.Use measures of
caring to evaluate nursing care
*
Caring RelationshipsRelationship with selfRelationships with
patients and familiesCollaborative relationshipsCaring for the
communities nurses live

*
Caring FactorsMutual problem-solvingAttentive
reassuranceHuman respectEncouraging mannerHealing
environmentAppreciation of unique meaningAffiliation
needsBasic human needs
*
Caring Factors (cont) The caring factors are used “in
relationship” with others and comprise the basis for the
“knowledge and skills” required to practice according to the
Quality-Caring Model.©
*
Applications to PracticeThe Quality-Caring Model© provides
individual clinicians, teams of health professionals, educators,
and leaders with a relationship-centric approach to healthcare.
In doing so, it honors the interdependencies necessary for
human advancement.
*

Many health systems are using the Quality-Caring Model©
to:provide a foundation for patient -centered careenhance
interprofessional practicefacilitate staff-directed practice
changesre-design professional workflowgenerate guiding
principles for human resource practicesguide nurse residency
programsimprove collective relational capacityrenew the
meaning of nursing workextend caring to others FIRSTbuild
relationships with community groupscreate a legacy of
caringsustain professionalismrevise nursing curriculabalance
“doing” with “being”
*
Practice Improvement (Tools)The revised Caring Assessment
Tool© (CAT) (Duffy, Hoskins, & Seifert, 2007; Duffy, Brewer
& Weaver, 2012), a 27-item instrument designed to capture
patients’ perceptions of nurse caring, has been used with
success in several health care institutions (Duffy, 2013).
*
Practice Improvement (Tools, cont)Another instrument that was
adapted from the CAT© is the Caring Assessment Tool for
Administration (CAT-adm) (Duffy, 2002). This tool is a 39-item
questionnaire that assesses how nurses perceive nurse manager

caring behaviors and has become important in the assessment of
caring practice environments.
*
Researching Caring Relationships Because the Quality-Caring
Model© provides a set of concepts, assumptions, and
propositions, questions generated from these theoretical ideas
can provide the basis for research. For example, the proposition,
“feeling ‘cared for’ influences the attainment of intermediate
and terminal health outcomes” (Duffy, 2013, p. 38) could be
tested by linking the results of an instrument measuring caring
with a set of specific patient outcome.
*
References
Duffy, J. (2002). The Caring Assessment Tool – Adm version.
In: J. Watson (Ed.), Instruments for assessing and measuring
caring in nursing and health sciences. New York: Springer.
Duffy, J., Hoskins, L. M., & Seifert, R. F. (2007). Dimensions
of caring: Psychometric properties of the caring
assessment tool. Advances in Nursing Science, 30(3), 235–
245.
Duffy, J. (2009). Quality caring in nursing: Applying theory to
clinical practice, education, and leadership. New
York: Springer Publishing.
Duffy, J, Brewer, B., & Weaver, M. (2010). Revision and

Psychometric Properties of the Caring Assessment Tool
Clinical Nursing Research. May 17, published ahead of print.
Duffy, J. (2013). Quality caring in nursing and health systems:
Implications for clinicians, educators, and leaders. New York,
NY: Springer Publishing.
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Analyze Qualitative Data
BUS-7380 Assignment # 6
Elton Norman
Dr. Vicki Lindsay
9 November 2019
Greetings Elton,
Using the same research design that you selected for the Week 5
assignment, you were to take 2-4 pages and consider the type of
data collected to create procedures for a comprehensive
analysis. Clearly define your approach to: (a) organizing data;
(b) coding and thematic development; (c) triangulation; and (d)
using software applications.
***************
The feedback process consisted of a four-part summary (four-

parts listed below), a few short, location-specific balloon-
comments found within the margins of the text, and the
highlighting of grammar, punctuation, or APA styling errors
found within the text. Make sure that you view your document
with the track changes (review toolbar) set to ALL MARKUP to
be able to see all the comments.
The summary is split into four parts. These four parts consist
of grammar/punctuation, conformity with APA style citations,
conformity with APA style references, and content. The order of
the parts listed does not intend to emphasize the importance of
the parts as the content is always the most important part of the
assignment. Therefore, it is listed in the end because normal
memory concentrates on what was heard / read last.
What was found:
Grammar/ Punctuation
There were a few grammar or punctuation errors found within.
There were problems in spelling, missing punctuation leading to
run on sentences, missing punctuation leading to grammatical
issues, and the agreement issues between words (i.e.,
subject/verb agreement and numerical plural numbers without
plural noun). Make sure that you read your work prior to
submission so that you will not have run on sentences within
your work. Pay attention to the word “and” within your work.
APA style citations
The citations present were in APA format. You seem to be
missing the additional 3 scholarly sources from your field that
were required within this assignment.
APA style references
Not enough information was included within your references to
make them correct APA references. You are missing page
numbers, volume, issue number, and the digital object identifier
for your journal article sources. Your book title should be in
italics. The publisher should not. All of the titles should be in
sentence case not in title case. This is not a problem with the
software program. This is a problem with the keypunch issue.
Your program cannot change lowercase letters into uppercase

letters in vice versa. You must be it incorrectly for it to
properly appear. Many have problems with this thought process.
Do not leave it up to the software program to correct keypunch
errors.
Content
The same problem that you had an assignment 5 appeared in
assignment 6. You are not explaining how these research
designs will fit with your research questions or problems
statement as you move forward through the data collection
process. Without doing this correctly, you will have problems
with your signature assignment, assignment 7. You need to
continue to read your assignment in detail. The assignment
stated that the student should create this assignment in a manner
consistent with the other assignments such as:
your approach must be systematic, logical, fully explained, and
supported with scholarly sources. Use the resources provided,
and at least three other peer-reviewed articles to defend your
research plan.
Note that the statement, " defend your research plan" means that
you should have used your research designs -- grounded Theory
and case study -- to develop a data collection process for your
research questions or problem statement. Do not overlook that
you should have used the required reading as well as three
additional scholarly sources from your field to show that this
happens within your field.
As before a rewrite is not required but it is recommended. You
have the basic information present. You now have to form the
details to show what would occur within your project to collect
data using these research designs.
If you have any questions about any part of this, please feel free
to contact me via Skype or NCU email.
Revise and resubmit. Submit by last date of class.
V. Lindsay, PhD 3.5/10 11/14/19

Research Design and Data Collection
The research design that I am going to use for this assignment is
the qualitative research design, as used in my assignment of
week 5. Qualitative research designs may take various forms as
I had illustrated, the first one being the grounded theory, which
is used as a different approach for the developing theories, as
arising from an established relationship after the process of data
collection and analysis. This theory arises after a systematic
gathering of data (Patten, 2017). The other form of qualitative
data is case studies. This design analyses a set of issues within
the limits of a given organization, situation, environment and so
on. A case study may take the form of explanatory, exploratory
or descriptive design. Comment by Vicki Lindsay, PhD: No
first- or second-person view in an APA style paper written for
NCU. APA only allows the first-person view within certain
areas of the methodology. APA does not allow second person
view within a scholarly paper. NCU does not condone the use of
first- or second-person view within work that is submitted. If I
see any use of these voices, I will highlight them from now
forward. Comment by Vicki Lindsay, PhD: This course is
qualitative research. You are studying the different types of
designs in qualitative research. You need to explain which of
the 5 research designs you are using for your data collection. In
assignment 5, you should have explained 2 different research

designs. This assignment is asking you to use those two designs
and describe the collection of the data as a researcher would go
forward with your research question or problem statement.
Comment by Vicki Lindsay, PhD: This is your research
design that you should be naming at the beginning.
Data collected
Data collection in grounded theory was based on observation
notes by the participant through getting engaged in people's
daily activities and the subjects in question. Data was also
collected through interviewing the subjects. The use of texts
and artifacts was as well used to gather data. In the case of
study, data was collected was on the description of a situation
by a subject, and answered the question of how and why. The
explanation was based on a real-life event, and as well used the
question who and what.
Organizing Data
Qualitative research comes up with a wide range of data that is
derived from various sources like interviews, observation notes,
questionnaires, and official documents. Due to a wide range of
respondents as well as the participants well as a variety of
researchers, it is important to classify and organize data to make
its understanding easier (Creswell, 2013). The following five
steps are the steps involved in organizing data.
1. Reviewing the whole set of data so to bring out themes or
patterns, which are then assigned symbols or numbers to make it
easier for the analysis.
2. Creating a table for the codes to ensure that there is
consistency in the codes and that such codes are accessible from
several researchers.
3. Classifying data into various groups according to various
codes, make easier for the analysis and discussion. This may
focus on themes that are independent as recorded in the data.
4. Organizing the data survey inform of a sub-topic or question
to analyses data easily. This organization may take the form of
question or subtopic
5. Coding the already transcribed data and labeling it to make

data readily evident. In this case, it would be easy for a
researcher to access information which has been analyzed,
grouped and transcribed.
Coding and thematic development
In qualitative research, coding refers to the main method that is
used in the development of themes or the patterns of meaning in
data classification (Saldana, 2015). Thematic development is
concerned with examining themes or general patterns within
data analysis. In this case, coding defines the data being
analyzations process identifies a passage within a text or any
item of data like an image or a photograph, getting the concepts
and looking for the relationship that exists between them.
Coding is therefore seen as the process of linking data to an
idea. In my case, concept and data-driven codes are being used
to getting an idea from the research data. Thematic
development, on the other hand, enroots on identification and
interpretation of the pattern of meaning or themes used in the
research work (Ryan, 2016). In my case, this was done through
discourse analysis after the interviews and interpreting the
observational notes. coding and thematic development make it
easier to understand data.
Triangulation
This is the process of using a variety of data sources to make
data comprehension easier. Triangulation also has found to test
data validity through the convergence of given information from
many sources. In this case, many methods are used to collect
data to ensure data validity. Triangulation also increases a
reader's knowledge as information is availed from different
sources (Rothbauer, 2015). In my example, I have triangulated
my qualitative study in data collection, where I used ground
theory and the case study, to come up with more information on
the research. This has helped widen the scope of research.
Using software applications
It is important to use software for qualitative analysis of data.
This software system helps in processing discourse analysis,
content analysis, text interpretation coding of information and

interpreting information to enable a person to make informed
decisions. In this case, I will use the SPSS software program for
my qualitative research study.
References
Creswell, J. (2013). Qualitative Inquary & Research Design:
Choosing Among the Five Approaches. Thousand Oaks, CA:
SAGE Publications, Inc., 78.
Patten, M. &. (2017). Understanding Research Methods: An
overview of the essentials. Routledge, 52.
Rothbauer, P. (2015). Triangulation: Qualitative Research
Methods. Sage Publications, 891.
Ryan, G. a. (2016). Techniques to Identify Themes. Field
Methods, 95.
Saldana, J. (2015). The Coding Manual for Qualitative
Researchers (3rd edition). SAGE Publications Ltd.
Linda Amankwaa, PhD, RN, FAAN
Abstract: Experienced and novice researchers, plan qualitative
proposals where evidence o f rigor
m ust be provided within the document. One option is the
creation o f a trustworthiness protocol
with details noting the characteristic o f rigor, the process used
to document the rigor, and then
a timeline directing the planned time for conducting
trustworthiness activities. After reviewing

several documents, an actual plan o f conducting
trustworthiness as not found. Thus, these authors
set out to create a trustworthiness protocol designed not only
for the dissertation, but a framework
for others who m ust create similar trustworthiness protocols for
their research. The purpose o f this
article is to provide a reference for the trustworthiness plan, a
dissertation example and showcase a
trustworthiness protocol that may be used as an example to
other qualitative researchers embarking
on the creation o f a trustworthiness protocol that is concrete
and clear.
K ey Words: Trustworthiness, Research Protocols, Qualitative
Research
C reating P rotocols for
T rustworthiness in Q ualitative
R esearch
Anything perceived as being of low or no value is also
perceived as being worthless, unreliable, or invalid. Research
that is perceived as worthless
is said to lack rigor. This means findings are not worth
noting or paying attention to, because they are unreliable.
To avoid this argument, proof of reliability and validity
in qualitative research methods is required. However,
some researchers have suggested that reliability and
validity are not terms to be used to explain the usefulness
of qualitative research. They believe that those terms are
to be used to validate quantitative research (Altheide &
Johnson, 1998; Leininger, 1994). Morse (1999) expressed
concern about qualitative research losing value by em-
phasizing when qualitative researchers fail to recognize
crucial importance of reliability and validity in qualita-

tive methods, they are also mistakenly supporting the
idea that qualitative research is defective and worthless,
lacking in thoroughness, and of unempirical value.
Guba and Lincoln (1981) stated that, "All research must
have 'tru th value', 'applicability', 'consistency', and
'neutrality' in order to be considered worthwhile. They
concluded that the end result of establishing rigor or
"trustworthiness," (the analogous for rigor in qualitative
research), for each method of research requires a differ-
ent approach. It was noted by Guba and Lincoln (1981),
Linda A m ankw aa, PhD , RN, FAAN, is an Associate
Professor in the Department o f Nursing at Albany State Uni-
versity in Albany, GA31705. Dr. Amankwaa may be reached
at: 229-430-4731 or at: [email protected]
within the rationalistic paradigm, criteria to reach the
goal of rigor are internal validity, external validity, reli-
ability, and objectivity. They proposed use of terms such
as credibility, fittingness, auditability, and confirmability
in qualitative research to ensure "trustworthiness" (Guba
& Lincoln, 1981). Later, these criteria were changed to
credibility, transferability, dependability, and confirm-
ability (Lincoln & Guba, 1985).
Lincoln and Guba (1985) suggested that the value of a
research study is strengthened by its trustworthiness. As
established by Lincoln and Guba in the 1980s, trustwor-
thiness involves establishing:
• Credibility - confidence in the 'tru th ' of the
finding
• Transferability - show ing that the findings have
applicability in other contexts
• D ependability - show ing that the findings are
consistent and could be repeated

• Confirmability - a degree of neutrality or the ex-
tent to w hich the findings of a stu d y are shaped
by the respondents and not researcher bias,
motivation, or interest.
For purposes of this discussion, this classic work is
used to frame trustworthiness actions and activities to
create a protocol for qualitative studies. Nursing faculty
and doctoral nursing students who conduct qualitative
research will find this reference useful.
Journal of C ultural Diversity • Vol. 23, No. 3 Fall 2016
mailto:[email protected]
Credibility Activities
Lincoln and Guba (1985) described a series of techniques
that can be used to conduct qualitative research that at-
tains the criteria they outlined. Techniques for establishing
credibility as identified by Lincoln and Guba (1985) are:
prolonged engagem ent, persistent observation, triangula-
tion, peer debriefing, negative case analysis, referential
adequacy, and member-checking. Typically member check-
ing is view ed as a technique for establishing the validity
of an account. Lincoln and Guba posit that this is the most
crucial technique for establishing credibility.
Transferability Activities
One strategy that can be em ployed to facilitate transfer-
ability is thick description (Creswell & Miller, 2000; Lincoln
& Guba, 1985). Thick description is described by Lincoln
and Guba as a w ay of achieving a type of external valid-

ity. By describing a phenom enon in sufficient detail one
can begin to evaluate the extent to which the conclusions
d raw n are transferable to other times, settings, situations,
and people. Since, as stated by M erriam (1995) it is the
responsibility of the consum er of research to determ ine
or decide if and how research results m ight be applied
to other settings, the original researcher m u st provide
detailed inform ation about the phenom enon of study to
assist the consum er in m aking the decision. This requires
the provision of copious am ounts of inform ation regard-
ing every aspect of the research. The investigator will
include such details as the location setting, atm osphere,
climate, participants present, attitudes of the participants
involved, reactions observed that m ay not be captured on
audio recording, bonds established betw een participants,
and feelings of the investigator. One w ord descriptors will
not suffice in the developm ent of thick description. The
investigator in essence is telling a story w ith enough detail
that the c o n su m er/read er obtains a vivid picture of the
events of the research. This can be accom plished through
journaling and m aintaining records w h eth er digital or
handw ritten for review by the consum er/reader.
Confirmability Activities
To establish confirmability Lincoln and Guba (1985)
suggested confirmability audit, audit trail, triangulation,
and reflexivity. An audit trail is a transparent description of
the research steps taken from the start of a research project
to the developm ent and reporting of findings (Lincoln &
Guba). These are records that are kept regarding w hat was
done in an investigation. Lincoln and Guba cite H alpern's
(1983) categories for reporting inform ation w hen develop-
ing an audit trail:
"1) Raw data - including all raw data, written field

notes, unobstrusive measures (documents); 2) Data
reduction and analysis products - including sum -
maries such as condensed notes, unitized information
and quantitative summaries and theoretical notes; 3)
Data reconstruction and synthesis products - includ-
ing structure o f categories (themes, definitions, and
relationships), findings and conclusions and a final
report including connections to existing literatures
and an integration o f concepts, relationships, and
interpretations; 4) Process notes - including method-
ological notes (procedures, designs, strategies, ratio-
nales), trustworthiness notes (relating to credibility,
dependability and confirmability) and audit trail notes;
5) Materials relating to intentions and dispositions -
including inquiry proposal, personal notes (reflexive
notes and. motivations) and expectations (predictions
and intentions); 6) Instrum ent development informa-
tion - including pilot forms, preliminary schedules,
observation form ats" (page#).
Using m ultiple data sources w ithin an investigation to
enhance understanding is called triangulation. Researchers
see triangulation as a m ethod for corroborating findings
and as a test for validity (Lincoln & Guba, 1985). Rather
than seeing triangulation as a m ethod for validation or veri-
fication, qualitative researchers generally use this technique
to ensure that an account is rich, robust, comprehensive
and well-developed (Lincoln & Guba, 1985).
D enzin (1978) and Patton (1999) identify four types of
triangulation: m ethods triangulation, source triangulation;
analyst triangulation; th eo ry /p ersp ectiv e triangulation.
They suggested that m ethods triangulation involves check-
ing out the consistency of finding generated by different
data collection m ethods. Triangulation of sources is an

exam ination of the consistency of different data sources
from w ithin the same m ethod (i.e. at different points in
time; in public vs. private settings; com paring people w ith
different viewpoints).
A nother one of the four m ethods identified by Denzin
and Patton includes analyst triangulation. This is the use
of m ultiple analysts to review findings or using m ultiple
observers and analysts. This provides a check on selective
perception and illum inate blind spots in an interpretive
analysis. The goal is to understand m ultiple ways of see-
ing the data. Finally, they described th eory/perspective
triangulation as the use of m ultiple theoretical perspectives
to examine and interpret the data.
According to Lincoln and Guba (1985) reflexivity is,
"A n attitude of attending system atically to the context
of know ledge construction, especially to the effect of the
researcher, at every step of the research process." They
suggested the following steps to develop reflexivity: 1)
Designing research that includes m ultiple investigators.
This fosters dialogue, leads to the developm ent of comple-
m entary and divergent understandings of a study situation
and provides a context in w hich researchers' (often h id -
den) - beliefs, values, perspectives and assum ptions can be
revealed and contested; 2) Develop a reflexive journal. This
is a type of diary w here a researcher m akes regular entries
during the research process. In these entries, the researcher
records methodological decisions and the reasons for them,
the logistics of the study and reflection u p o n w hat is h a p -
pening in term s of one's ow n values and interests. Diary
keeping of this type is often very private and cathartic; 3)
Report research perspectives, positions, values and beliefs
in m anuscripts and other publications. Many believe that it
is valuable and essential to briefly report in m anuscripts, as
best as possible, how one's preconceptions, beliefs, values,

assum ptions and position m ay have come into play during
the research process.
Dependability Activities
To establish dependability, Lincoln and Guba (1985) sug-
gested a technique know n as inquiry audit. Inquiry audits
are conducted by having a researcher that is not involved in
the research process examine both the process and product
of the research study (Lincoln & Guba, 1985). The purpose
is to evaluate the accuracy and evaluate w hether or not the
findings, interpretations and conclusions are supported by
the data (Lincoln & Guba, 1985).
Journal of Cultural Diversity • Vol. 23, No. 3 Fall 2016
Creating a Protocol for Qualitative Researchers
The creation of a protocol for establishing trustwor-
thiness within qualitative research is essential to rigor.
Further, we note that researchers rarely document how
or w hat their trustworthiness plan or protocol consisted
of within research documents. Thus, we posit here that
creating such a protocol prior to initiation of the research
study is essential to revealing trustworthiness within the
research process. By creating this plan a priori, the rigor
of qualitative research is apparent.
This history and purposed need for this article heralds
from a doctoral dissertation search to find examples of
trustworthiness protocols for direction to complete trust-
worthiness within doctoral qualitative research. Since none
could be found, discussions lead the researcher to create a
table that could used by those who are planning qualita-

tive studies. Another interesting point is that qualitative
researchers, unlike quantitative researchers, rarely create
protocol guidelines.
The establishment of trustworthiness protocols in quali-
tative research requires the use of several techniques. This
protocol will be detail specific so those researchers have
a guideline for trustworthiness activities. Such a protocol
guides prospective qualitative researchers in their quest
for rigor. Several tables are presented here. The first table
outlines the main topics within the trustworthiness proto-
col. The remaining tables outline the suggested activities
within trustworthiness protocol and for those creating a
trustworthiness protocol.
Table one is the basic criteria for a trustworthiness pro-
tocol using Lincoln and Guba (1985). However, researchers
may use other models of rigor. Creating a table aligned with
the planned model of rigor is the recommendation. The
following five table are examples of a "created" protocol
w ith examples of very specific activities related to each
trustworthiness criteria.
Summary
In summary, trustw orthiness is a vital com ponent
within the research process. Attending to the language of
trustworthiness and the important activities of reliabil-
ity, add to the comprehensiveness and the quality of the
research product. This discussion heralds the new idea
that trustworthiness must be planned ahead of time with
a protocol. This protocol must include dates and times
trustworthiness actions. We contend that researchers can
use the protocol by adding two columns which specify the
date of the planned trustworthiness action and the date the
action was actually completed. This information can then
be included in the audit trail thus authenticating the work

qualitative researcher and the rigor of the research.
REFERENCES
Altheide, D., & Johnson, J. (1998). Criteria for assessing
interpre-
tive validity in qualitative research. In N. K. Denzin, & Y. S.
Lincoln (Eds.), Collecting and interpreting materials, 283- 312.
Creswell, J. & Miller, D. (2000). D eterm ining validity and
qualita-
tive inquiry. Theory Into Practice, 39(3), 125-130.
Denzin, N. (1978). Sociological Methods. N ew York: M
cGraw-Hill.
Guba, E. & Lincoln, Y. (1981). Effective evaluation: improving
the
usefidness of evaluation results through responsive and
naturalistic
approaches. San Francisco, CA: Jossey-Bass.
Leininger, M. (1994). Evaluation criteria and critique of
qualitative
and interpretive research. Qualitative Inquiry, 1, 275-279.
Lincoln, Y. S. & Guba, E. G. (1985). Naturalistic Inquiry. N ew
bury
Park, CA: Sage Publications.
Morse, J. (1999). Myth #3: Reliability and validity are n ot
relevant
to qualitative mquiry.Qualitative Heath Research, 9, 717.
Patton, M. Q. (1999). "Enhancing the quality and credibility of
qualitative analysis." HSR: Health Services Research. 34(5),

Part II, 1189-1208.
BIBLIOGRAPHY
Bitsch, V. (2005). Qualitative research: A grounded theory
example
and evaluation criteria. Journal of Argibusiness, 23 (1), 75-91.
Carpenter, R. (1995). G rounded theory research approach. In H.
J. Streubert & R. D. Carpenter(Eds-), Qualitative research and
in nursing: Advancing the humanistic imperative, 145-161.
C ohen D., Crabtree, B. (2006). Q ualitative Research
Guidelines
Project. July 2006. http://w w w .qualres.org/H om eRefl-3703.
htm l
Giacomini, M. & Cook, D. (2000). A u s e r's guide to
qualitative
research in health care. In Users' guides to evidence-based
medicine. Journal o f the American Medical Association,
284(4),
478-482.
Morse, J. Barrett, M., Mayan, M., Olson, K., & Spiers, J.
(2002).
Verification strategies for establishing reliability and valid-
ity in qualitative research. International Journal o f Q u a lita -
tive Methods, 1, 2, Article 2. Retrieved April 30, 2010 from
http: / / w w w .u alb erta.ca/-ijq rn /
Neuman, L. (2003). Qualitative and quantitative measurements.
In
Social research methods: Qualitative and quantitative
approaches,
fifth edition, 169-209.

Plack, M. (2005). H um an nature and research paradigm s:
Theory
meets physical therapy practice. The Qualitative Report, 10(2),
223-245.
Polit, D. & Hungler, B. (1999). Research control in quantitative
research. In N ursing research: P rin c ip le s a n d m e th o d s
,
sixth edition, 219-238. Lippincott.
Rubin, H. & Rubin, I. (1995). Qualitative interviewing: The art
of
hearing data. Thousand Oaks, CA: Sage Publications.
Siegle, D. (2002). Principles and m ethods in educational
research:
A web-based course from the University of Connecticut. Re-
trieved April 30, 2010 from http: / / w w w .gifted.uconn.edu/
siegle / research/qualitative / qualitativeInstructorNotes.html
Tobin, G. & Begley, C. (2004). M ethodological rigour w ithin a
qualitative fram ew ork. Journal of Advanced Nursing, 48(4),
388-396.
Table 1. Basic Trustworthiness Criteria (Lincoln & Guba, 1985)
Criteria Technique
Credibility Peer debriefing, m em ber checks, journaling
Transferability Thick description, journaling
Dependability Inquiry audit with audit trail
Confirm ability Triangulation, journaling

Journal of Cultural Diversity Fall 2016
http://www.qualres.org/HomeRefl-3703
http://www.ualberta.ca/-ijqrn/
http://www.gifted.uconn.edu/
Table 2. Credibility
Credibility R ecom m ended activities/plan
Peer 1. W rite plan within proposal.
debriefing/debriefer
2. Com m ission a peer to w ork with researcher during the tim e
of interviews and data
collection.
3. This person must com plete an attestation form to work with
researcher. Plan to meet
with this person after each interview.
4. During visits with the peer debriefer, research and peer
discuss interviews, feelings,
actions o f subjects, thoughts, and ideas that present during this
time. Discuss
blocking, clouding and other feelings of researcher. Discuss
dates and tim es needed
fo r these activities. W ill meet once a w eek fo r 30 minutes to
an hour.
5. Journal these meetings. W rite about thoughts that surfaced
and keep these dated for
research and evaluation during data analysis.

6. Need to be com puter files so that you may use this inform
ation within data analysis.
M em ber Checks 1. Outline different tim es and reasons you
plan to conduct m em ber checks or collect
feedback from m em bers about any step in the research process.
2. M em ber checks will consist o f com m unication with mem
bers after significant
activities.
3. These activities may include interviews, data analysis, and
other activities.
4. W ithin two weeks o f the interview, send mem bers a copy o
f their interview so that
they can read it and edit for accuracy.
5. W ithin two weeks o f data analysis com pletion, m em ber
will review a copy o f the final
them es.
6. M em bers are asked the question, “ Does the interview
transcript reflect your words
during the interview?”
7. C hoose negative cases and cases that follow pattern.
8. Be sure these check are recorded and are com puter files so
that you may use this
inform ation in data analysis.
Journaling plans 1. Journaling will begin with the writing o f
the proposal.
2. Journaling will be conducted after each significant activity.

These include each
interview, w eekly during analysis, after peer debriefing visits,
and them e production.
3. Journals will be audited by research auditor.
4. Journals will include dates, times, places and persons on the
research team.
5. Journals need to be com puter files so that you may use them
in data analysis.
Protocol Create a tim eline with planned dates fo r each activity
related to credibility before
com m encing the study. This protocol with dates and activities
should appear in the
appendix.
Table 3. Transferability
Thick Description Actions for this activity include:
1. Reviewing crafted questions with Peer reviewer for clarity.
2. Planning questions that call for extended answers.
3. Asking open ended questions that solicit detailed answers.
4. Interviewing in such a way as to obtain a detailed, thick and
robust response.
5. The object is to reproduce the phenomenon of research as

clearly and as detailed as
possible.
6. This action is replicated with each participant and with each
question (sub-question)
or statement.
7. This continues until all questions and sub-questions are
discussed.
8. The peer reviewer along with the researcher review responses
for thickness and
robustness.
9. There are two issues related to thick description here. The
first is receiving thick
responses (not one sentence paragraphs). The second is writing
up the responses of
multiple participants in such a way as to describe the
phenomena as a thick
response.
Journaling Actions for this activity include:
1. Planning journal work in advance is an option. Such that the
researcher could decide
what dates and how often the journal will occur.
2. Journaling after interview is common.
3. Journaling after peer-review sessions.
4. Journaling after a major event during the study.
5. Journal entries should be discussed with peer reviewer such
that expression of

thoughts and ideas gleaned during research activities can be
connected to
participants’ experiences.
6. Journals can be maintained in various formats. Information
for the journal can be
received in the form of emails, documents, recordings, note
cards/note pads. We
recommend that the researcher decide on one of the options.
7. Journaling includes dates of actions related to significant and
insignificant activities of
the research.
8. Journal may start on the first date a decision is made to
conduct the research.
9. Journaling ends when the research is completed and all
participants have been
interviewed.
10. As with each of the concepts here, create a timeline with a
date-line protocol for each
activity before commencing the study.
Protocol Create a timeline with planned dates for each activity
related to transferability before
commencing the study. This protocol with dates and activities
should appear in the appendix.
Journal of Cultural D iversity • Vol. 23, No. 3 Fall 2016
Table 4. Dependability

A udit Trail Com ponents o f the audit trail include:
1. Make the list of docum ents planned for audit during the
research work.
2. Com m ission the auditor based on plan for study.
3. Decide audit trail review dates and times.
4. See auditor inform ation below
5. W rite up audit trail results in the journal.
Journaling A ctions for this activity include:
I . Planning journal w ork in advance is an option. Such that
the researcher could decide what
dates and how often the journal will occur.
I I . Journaling after interview is common.
13. Journaling after a m ajor event during the study.
that expression of thoughts
and ideas gleaned during research activities can be connected to
participants’ experiences.
15. Journals can be maintained in various form ats. Information
fo r the journal can be received in
the form of emails, docum ents, recordings, note cards/note
pads. W e recom m end that the
researcher decide on one o f the options.

16. Journaling includes dates o f actions related to significant
and insignificant activities o f the
research.
18. Journaling ends w hen the research is com pleted and all
participants have been interviewed.
Auditor 1. The auditor is reviewing the docum ents fo r
authenticity and consistency.
2. The auditor may be a colleague or som eone unfam iliar with
the research such that activities
can be questioned fo r clarity.
3. The auditor should have som e com prehension o f the
research process.
4. Planning in advance fo r the tim e com m itm ent as an
auditor is crucial.
5. Should provide constructive feedback on processes in an
honest fashion.
6. Auditor, researcher, and participants should speak the same
language.
7. Must be able to create and maintain audit trail documents.
Protocol Create a tim eline with planned dates fo r each activity
related dependability before com m encing the
study. This protocol with dates and activities should appear in
the appendix.

Table 5. Confirmability
Triangulation 1. Determine triangulation methods
2. Document triangulation plans within journal.
3. Discuss triangulation results peer-reviewer
4. Decide if further triangulation is needed
5. Write up the triangulation results.
Journaling Actions for this activity include:
2. Planning journal work in advance is an option. Such that the
researcher could decide what
dates and how often the journal will occur.
19. Journaling after interview is common.
21. Journaling after a major event during the study.
that expression of thoughts
and ideas gleaned during research activities can be connected to
participants
experiences.
23. Journals can be maintained in various formats. Information
for the journal can be received

in the form of emails, documents, recordings, note cards/note
pads. We recommend that
the researcher decide on one of the options.
24. Journaling includes dates of actions related to significant
and insignificant activities of the
research.
Journaling ends when the research is completed and all
participants have been interviewed.
Protocol Create a timeline with planned dates for each activity
related confirmability before commencing the
study. This protocol with dates and activities should appear in
the appendix.
• Vol. 23, No. 3 ( E 9Journal of C ultural Diversity Fall 2016
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Necatibey Eğitim Fakültesi Elektronik Fen ve Matematik
Eğitimi Dergisi (EFMED)
Cilt 11, Sayı 2, Aralık 2017, sayfa 518-544.
Necatibey Faculty of Education Electronic Journal of Science
and Mathematics Education
Vol. 11, Issue 2, December 2017, pp. 518-544.
Computer Assisted Qualitative Data Analysis: A
Descriptive Content Analysis (2011 – 2016)
Melike YAKUT ÇAYIR, Mustafa Tuncay SARITAŞ*
Received : 25.10.2017 Accepted : 10.11.2017
Abstract –Qualitative data analysis process is an exhausting
process that requires time, intensive, and meticulous
study. The use of computer software in this process provide
significant benefits in organizing data collected by
various methods, dividing them into categories, developing
themes, and providing a research report. The purpose
of this study is to examine qualitative research studies that use
a computer software for data analysis and
determine their tendencies. One method to understand
computer-assisted qualitative data analysis beyond a
simple definition is to examine the published articles in

academic journals. Within this scope, 688 articles
published in the SSCI index were analyzed according to
computer usage in qualitative data analysis and it was
aimed to determine the general tendency by different variables.
A computer-assisted qualitative data analysis
was carried out using Atlas.ti software in 28 of the 688 articles
examined. Only 28 of those were coded as the
ones that conduct computer-aided qualitative data analysis. Out
of 28, 14 articles utilized ATLAS.ti, MAXQDA,
Nvivo and HyperRESEARCH as data analysis software designed
to enable researchers to develop coding
schemes, notions and theories.
Key words: qualitative data analysis, content analysis, computer
software
Summary
Purpose and Significance. The number of qualitative and mixed
research studies is
increasing as the positivist/rational paradigm in educational
research has left its place to an
interpretive and critical paradigm over time. The analysis
process in qualitative research
typically begins with the preparation and organization of
qualitative data. Afterwards, the data

is encoded and the themes may be created by employing the
combination of the codes.
Finally, data is interpreted and discussed and presented visually
as in figures and tables.
* Corresponding author: Necatibey Education Faculty, Balıkesir
University, Balıkesir, Turkey
Email: [email protected]
YAKUT ÇAYIR, M. & SARITAŞ, M.T. 519
Eğitimi Dergisi
Necatibey Faculty of Education, Electronic Journal of Science
Qualitative data analysis is an exhausting process that requires
time, intensive, and meticulous
study. The use of computers in qualitative data analysis
provides significant benefits in this
process. The common name for a computer software supporting
qualitative data analysis is
“Computer Aided Qualitative Data Analysis Software.” These

kinds of software are able to
organize data collected by various methods, divide them into
categories, develop themes, and
provide a report for the whole analysis process.
In recent years, academic studies using computer software in
qualitative data analysis have
increased in Turkey. With an increased interest in computer
usage in qualitative research,
universities, academic conferences, and educational institutions
have started to organize
training events and workshops for enabling researchers to
conduct computer-assisted
qualitative analysis in their research studies to easily process,
formulate, and interpret textual
as well as audio-visual data. In addition, several graduate
programs of Turkish universities
offer courses particularly related to the theoretical and
methodological aspects of computer
assisted qualitative data analysis.
Most of the computer-assisted qualitative research studies has
focused on simply the
presentation of computer software used in the study. Those

studies are lacking of
investigating and interpreting the ways and reasons why
computer-assisted qualitative data
analysis was conducted. One method to understand computer-
assisted qualitative data analysis
beyond a definition is to examine the articles published in
academic journals. In this study,
considering the criterion about abstracted and indexed in Social
Science Citation Index,
research articles published in a journal (Education and Science)
were analysed to determine
tendencies by different variables about computer software usage
in qualitative data analysis.
For this purpose, the following research questions were
scrutinized:
1. What research methods have been conducted in studies
between the years of
2011 and 2016?
2. How many studies conducting qualitative data analysis used
computer software?
3. Which software programs have been used for computer-
assisted qualitative data
analysis?

4. What are the features of the computer software used in the
articles?
5. What are the descriptive characteristics of the articles
including computer-
assisted qualitative data analysis processes?
520 Nitel Veri Analizi Sürecinde Bilgisayar Yazılımı
Kullanımına Yönelik İçerik Analizi
A Content Analysis of Using Computer Software in Qualitative
Data Analysis
NEF-EFMED Cilt 11, Sayı 2, Aralık 2017/ NFE-EJMSE Vol.
11, No. 2, December 2017
a. What computer software has been used in the research studies
by year(s)?
b. What research methods and research patterns have been used
in the
research studies?
c. What is the distribution of the research studies by
universities?
Methodology. This study is a descriptive content analysis aimed
at determining the general
tendency in using computer software in qualitative research
studies published in the period of

2011-2016 years. Within this scope, 688 articles in 30 issues of
a journal abstracted and
indexed by SSCI were examined. After thorough analysis, 28
articles employing the
computer-aided qualitative data analysis using a specific
computer software were selected to
examine.
In order to examine the articles, a coding scheme was developed
by researchers to collect and
analyse data accordingly. The collected data uploaded to a
qualitative research software
named ATLAS.ti for analysis process.
Results. 688 articles published between 2011 and 2016 were
examined in the scope of this
research study. 444 of these articles were quantitative study,
185 were qualitative study, 33
were mixed study and 26 were out of these categories. The
number of quantitative studies is
considerably higher than other methods. However, the number
of qualitative studies published
in recent years is increasing and reaching to the number of
quantitative studies on the year

basis.
218 articles including 185 qualitative and 33 mixed research
methods were examined and
only 28 of those were coded as the ones that conduct computer-
aided qualitative data analysis.
Out of these 28 articles, 14 articles utilized qualitative data
analysis software (i.e. ATLAS.ti,
MAXQDA, Nvivo and HyperRESEARCH) designed to enable
researchers to develop coding
schemes, notions and theories in relevant fields.
In terms of computer-assisted qualitative data analysis, 7
different software have been used:
Basic level computer programs - MS Word and Excel, second
group - the statistical program
(SPSS), and the third group - advanced qualitative data analysis
computer programs
(MAXQDA, ATLAS.ti, Nvivo and HyperRESEARCH).

Eğitimi Dergisi
It is found that the Nvivo has been the most preferred coding
and theoretical development
software in the qualitative data analysis. Only 4 of the 14
articles (used software for coding
and theory development) provided visual representation of the
data, for instance, the figures,
maps, and graphical models. The other 10 articles presented
data and findings in tables
without using the visualization features of the software.
The use of computer programs in qualitative data analysis seems
to have increased over the
years. This increase is in direct relation with the increase in
qualitative research studies.
Conclusion. According to the research methods published in
articles since 2011, it is
observed that quantitative methods are superior to other
research methods. However, the
number of qualitative and mixed research studies has rapidly
increased in the last two-three

years.
SPSS and Nvivo have been the most frequently used computer-
assisted qualitative data
analysis software. The extensive use of a statistical software -
SPSS in the analysis of
qualitative data indicates that researchers are still keeping their
habit of doing quantitative
research. Additionally, the reason for the broad use of the
Nvivo program is because many
books and workshops about Nvivo are relatively in the literature
and educational sector.
Out of 218 quality research, only 14 were the ones that used
computer software enabling
coding and theory development. One critique about 14 articles
is that the software was used to
analyse one type of qualitative data - textual data. However, the
software could be used to
analyse other type of data, for instance, video, image, audio
files, etc. The use of computer
software not only facilitates the qualitative data analysis
process for researchers but also
maintains the whole research in a more accurate, concrete, fast,

and comprehensive way. It
also allows researchers to disseminate research results by
visualizing the data in a more
explicable way. On the other hand, the task of making the actual
analysis belongs to the
researcher. It is the researcher who decides how the data will be
encoded and how the results
will be interpreted.
Qualitative data analysis software is not a genuine software that
performs the whole analysis
process and reveals the results as it is in quantitative data
analysis software. Although
Data Analysis
qualitative data analysis software provides such opportunities
for researchers as doing coding,
creating relations between themes, developing visual models,
and creating research reports,

qualitative research should be conducted by a researcher who is
capable and knowledgeable
about the theoretical and methodological fundamentals about
qualitative research.
Eğitimi Dergisi
Nitel Veri Analizinde Bilgisayar Kullanımı: Bir Betimsel
İçerik Analizi (2011-2016)
Melike YAKUT ÇAYIR, Mustafa Tuncay SARITAŞ†
Makale Gönderme Tarihi: 25.10.2017 Makale Kabul
Tarihi: 10.11.2017
Özet –Nitel veri analiz süreci zaman alıcı, yoğun ve kapsamlı
çalışmayı gerektiren yorucu bir süreçtir. Bu süreçte
kullanılan bilgisayar yazılımları, farklı yöntemlerle toplanmış
verileri organize etme, bunları kategorilere ayırma,
yeni temalar oluşturma ve rapor hazırlama işlemlerinde büyük
kolaylıklar sağlamaktadır. Bu çalışmanın amacı,

nitel veri analizi sürecinde bilgisayar yazılımı desteği ile
yapılan araştırmaları incelemek ve bu araştırmaların
betimsel içerik analizi yöntemi ile eğilimlerini belirlemektir.
Bilgisayar destekli nitel veri analizini bir tanımın
ötesinde anlamanın en iyi yollarından biri de yayımlanan
makalelerdeki nitel çalışmaları incelemektir. Bunun
için SSCI dizini kapsamında yayımlanan 688 makale nitel veri
analizinde bilgisayar kullanma ölçütüne göre
incelenmiş ve çeşitli değişkenler açısından analiz edilerek genel
eğilimin belirlenmesi amaçlanmıştır. Araştırma
kapsamında incelenen 688 makalenin 28’inde Atlas.ti yazılımı
kullanılarak bilgisayar destekli nitel veri analizi
yapılmıştır. Bu 28 makalenin 14’ünde nitel araştırmaları analiz
etmek üzere tasarlanmış, araştırmacılara ilgili
alanlarda “kodlama listesi, yeni fikirler ve teoriler oluşturmada”
kolaylık sağlayan programlar olarak ATLAS.ti,
MAXQDA, Nvivo ve HyperRESEARCH kullanıldığı tespit
edilmiştir.
Anahtar kelimeler: Nitel veri analizi, içerik analizi, bilgisayar
yazılımı.
Giriş
Bilimsel araştırmalarda pozitivist/akılcı paradigmanın zamanla
yorumlayıcı ve eleştirel

paradigmaya evrilmesiyle nitel ve karma araştırmaların sayısı
gün geçtikçe artmaktadır. Nitel
verilerin toplandığı nitel ve karma yöntem araştırmalarda, nitel
verilerin analiz süreci genel
olarak verilerin hazırlanması ve organize edilmesiyle başlar
(örneğin; metinlerin yazıya
dökülmesi, fotoğraf ve resim gibi görsel verilerin
düzenlenmesi). Sonra, veriler kodlanır ve
kodların bir araya getirilmesiyle temalar oluşturulur. Son
olarak, veriler şekiller, tablolar, bir
tartışma ve yorumlama halinde sunulur (Cresswell, 2016a).
Nitel veri analizinde bilgisayar kullanımı; zaman alıcı, yoğun
emek ve detaylı çalışma
gerektiren bu süreçte önemli kolaylıklar sağlamaktadır. Ancak
nitel veri analizi süreci elle
† Sorumlu Yazar: Necatibey Eğitim Fakültesi, Balıkesir
Üniversitesi, Balıkesir, Türkiye
Eposta: [email protected]
Data Analysis

kodlama veya bilgisayar kullanımıyla kodlama için benzerlik
göstermektedir: Araştırmacı, bir
metin veya herhangi bir içerik bütününü veya parçasını belirler,
buna bir kod etiketi
kararlaştırır, aynı kod etiketine sahip bütün metin parçaları için
veri tabanını baştan sona
araştırır ve kod için bu metin parçalarının bir çıktısını geliştirir.
Bu süreçte, kodlamayı ve
kategorilendirmeyi, bilgisayar değil, araştırmacı yapar
(Creswell, 2016a). Öte yandan
bilgisayar yazılımlarının fonksiyonları veya gerekli programları
devreye sokulduğu vakit bu
süreç otomatik bir şekilde hızlıca yazılım tarafından
gerçekleştirilebilir.
Nitel veri analizi amacıyla kullanılan ve bilgisayar desteği
veren yazılım kategorisinin
genel adına Bilgisayar Destekli Nitel Veri Analizi Yazılımları
denir. Bilgisayar Destekli Nitel
Veri Analizi Yazılımları 1980’lerin sonlarından bu yana
kullanılmaktadır. Bu yazılımlar;
çeşitli yöntemlerle toplanan verileri organize eden, kategorilere
ayıran, temaları ortaya

çıkarmakta ve bütün sürecin raporlaştırılmasında kullanılan özel
amaçlı bilgisayar
yazılımlarıdır.
Weitzman ve Miles (1995), nitel veri analizinde
kullanılabilecek bilgisayar yazılımlarını
fonksiyonlarına göre 3 başlıkta sınıflandırmıştır. Buna göre:
Sözcük İşlemci Yazılımlar: Bu tür yazılımlar verilerin
yazıya dökülmesi, organize
edilmesi ve kodlamaya hazırlanması sürecinde araştırmacıya
önemli kolaylıklar sağlarlar.
Köprüler yoluyla dokümanlar birbirine bağlanabilir ve
ilişkilendirilebilir. Her dosyada yer
alan metinlerin tamamının veya belli bir bölümünün bulunması,
yer değiştirilmesi, yeniden
üretilmesi, görüşmelerin metne aktarılması (transcribing), alan
notlarının yazılması,
metinlerin kodlanması ve raporlaştırılmasında başvurulabilir.
Örneğin, MS Word yazılımı,
yukarıda sözü edilen kodlama ve ilişkilendirmeye olanak
sağlamaktadır.
Kodlama Yazılımlar: Özellikle nitel veri analizini
kolaylaştırmak amacıyla hazırlanan
bu tür yazılımlar yoluyla kodlama süreci daha sistematik ve

pratik hale getirilmektedir. Veri
tabanı içinde anlamlı bir bütün oluşturan kesitler (örneğin;
sembol, sözcük, cümle, paragraf)
kodlanabilir; ilgili bölümler kolayca işaretlenebilir ve kodlar
sistematik bir biçimde
sunulabilir. Kodlara açıklamalar eklenebilir ve kodların
hiyerarşik bağlantıları
görselleştirilebilir. Sistematik, tam, esnek ve hızlı kodlama
yapılabilir. Örnek olarak
Etnograph, HyperQual gibi yazılımlar verilebilir.
Kodlama ve Kuram Geliştirme Yazılımlar: Yalnızca
kodlama yapan yazılımlardan
farklı olarak, bu tür yazılımlarla kodlamaya dayalı kuram
geliştirmek ve bu kurama göre
araştırma raporunu oluşturmak mümkündür. Kuram geliştirme,
kodlar arasında anlamlı
Eğitimi Dergisi

ilişkiler kurma ve bu ilişkilerden yola çıkarak araştırmanın
temel konusunu oluşturan olguyu
açıklama biçiminde gerçekleşmektedir. Bu yazılımlar;
araştırmacıya kodlar arasında ilişki
kurmada sağladığı kuramsal çerçeveler ve görsel ögeler yoluyla
yardımcı olmaktadır. Örnek
olarak, ATLAS.ti ve Nvivo gibi yazılımlar verilebilir (Yıldırım
ve Şimşek, 2006).
Bilgisayar destekli nitel veri analizi araştırmacılara birçok
avantaj sunmaktadır.
Örneğin, bir bilgisayar programı düzenli depolanmış bir dosya
sistemi sağlamaktadır.
Böylelikle araştırmacı veri setlerine hızlı ve kolay bir şekilde
yer bulur ve dijital ortamda
yedekleyebilir. Ayrıca, geleneksel olarak kesip yapıştırarak,
renkli kalemlerle çizilerek
yapılan veri analizi süreci dijital ortamda gerçekleştirilebilir.
Geleneksel yönteme kıyasla
yazılımlar araştırmacıların veriler arasında hypertext ya da
hipermetin denen bağlantılar
kurabilmelerine olanak tanır.
Günümüzde yazılımlara görsel, işitsel ve sosyal medya gibi
çeşitli formatlardaki veriler
de yüklenebilir, işlenebilir ve depolanabilir. Nitel araştırma ve

analiz sürecinin
zenginleştirilmesinde çoklu ortam (örneğin; ses, video, resim)
verilerinin yanında sosyal
medya (örneğin; Blog, Twitter, Facebook) ve farklı belge türleri
(örneğin; pdf, doc, veri
tabanı) kullanılabilmektedir (Birkök, 2008). Farklı türlerde ve
niteliklerdeki verilerin
kullanılması araştırmanın güvenirliğini ve geçerliğini artırabilir
(Creswell, 2016a) ve bütüncül
bir akış açısı kazandırabilir. Buna ilave olarak, bilgisayar
yazılımları kodları, temaları ve
bunlar arasındaki kuramsal bağlantıları görselleştirebilir.
Veriler ana temalar altında yer alan
bağlantılı alt temalar şeklinde yerleştirilerek hiyerarşik bir
biçimde gösterilebilir. Analiz
sürecinde kullanılan kodlar ve temaların yerleri değiştikçe
yeniden düzenlenmesi kolaydır.
Analiz sonuçları da karşılaştırmalı tablolar ve listeler şeklinde
gösterilebilir. Ayrıca, zihin
haritaları (mind maps), sözcük bulutları (word clouds), sözcük
ağaçları (word trees), tablolar
ve grafikler gibi görsel araçlar verilerin çeşitli biçimlerde
somutlaştırılabilmesine olanak
sağlar.

Öte yandan bu yazılımların özelliklerini kullanmayı öğrenmek
nitel veri analizi için
emek ve süre gerektirecektir. Nitel yazılımları kullanmayı ilk
kez deneyen araştırmacılar nitel
analiz yazılımlarının nicel analiz yazılımları gibi analizin
tümünü gerçekleştireceği
beklentisini taşıyabilir. Mevcut birçok yazılımın yaptığı işler
farklı olduğu için doğru yazılımı
bulmak bir inceleme süreci gerektirebilir (Rodik & Primorac,
2015).
Nitel Veri Analizinde Öne Çıkan Bilgisayar Programları
MAXQDA:
Data Analysis
MAXQDA araştırmacıya nitel metinleri sistematik
olarak değerlendirmesi ve
yorumlaması için yardım eden bir bilgisayar yazılım
programıdır. Ayrıca teoriler geliştirmek

ve teorik sonuçları test etmek için güçlü bir araçtır. Ana menüde
dört penceresi vardır: i) veri
bölmesi, ii) kod veya kategori sistemi, iii) analiz edilen metin
ve iv) temel ve karmaşık arama
sonuçları. MAXQDA hiyerarşik bir kod sistemi kullanmaktadır.
Araştırmacı bir metin
parçasına bir ağırlık puanı ekleyebilir. Kısa notlar farklı tipte
notlar olarak (örn. Teorik veya
metodolojik notlar) kolayca yazılabilir ve saklanabilir. Görsel
haritalama özelliğine sahiptir.
Veriler, SPSS veya Excel gibi istatistik programları ile uyumlu
bir şekilde karşılıklı
kullanılabilir. Bu nedenle karma yöntem araştırmalarında da
tercih edilen bir programdır.
Belirli bir proje üzerinde birden fazla kodlayıcı tarafından
kolayca kullanılır. Resim ve video
parçaları bu programda saklanabilir ve kodlanabilir.
HyperRESEARCH:
HyperRESEARCH kaynak materyalden kodlama yapılmasını ve
geri çağırmayı
sağlayan kuram oluşturmakta kullanılabilen, çoklu ortam
verilerini analiz edebilen nitel ve
karma yöntemlerde veri analizi yapabilen bir yazılımdır.
Görünümü ve kullanımı kolay ve

değişik platformlarda kullanılabilen bir yazılımdır. Bu program
aynı zamanda araştırmacının
görsel diyagramları çizmesine olanak tanır ve şimdi
araştırmacının video ve ses verilerinin
transferini yapmasına imkân veren ̏Hyper- Kopyalayıcı̋ adlı bir
modüle sahiptir.
Nvivo:
Bu program araştırmacının kodları özel temalar altında
toplamasına, karşılaştırmasına,
kodlar ve araştırmacının notları arasında ilişki kurarak elde
edilen verilerin görselleştirilip
(örn. model, matris, grafik) raporlaştırılmasına olanak veren bir
programdır (Bacanak, 2013).
Dokümanlar, video ve ses kayıtları, e-mailler, fotoğraflar gibi
farklı formatlardaki veriler ile
çalışılabilir. Birbiriyle ilişkili birçok bilgi ve doküman organize
edilebilir ve yönetilebilir.
Materyalinizi anlamak için dipnot ve yorum yapma, doküman ve
verilerde arama ve
sorgulama yapma ve paylaşma Nvivo ile yapılabilir. Nvivo’da
yer alan dokümanınız diğer
uygulamalarla beraber çalışabilmektedir.
ATLAS.ti:

Atlas.ti yazılımı, Berlin Teknik Üniversitesi bilim insanları
tarafından geliştirilmiştir.
Nitel araştırma sürecini “heurmeneutic unit(s)” olarak
isimlendirerek bir araştırma projesi
olarak kabul eden bu yazılım, büyük ve farklı veri setlerine
(belgeler, alıntılar, notlar, işitsel
ve görsel dosyalar gibi) ve bunların üzerindeki yapılan
kodlarına kolay erişim sağlayan
düzenli bir çalışma alanı sunar (ATLAS.ti - The Knowledge
Workbench: ATLAS.ti -
Eğitimi Dergisi
Qualitative Data Analysis Software). Farklı veri setleri arasında
bir ağ kurup bunlar arasında
ilişkili düzenlemeler, işlemler, kodlamalar ve not almalara
(memos) olanak tanır. Alternatif ve
interaktif kodlama fonksiyonları araştırmacıya program
arayüzünde kolaylık ve seçenekler

sunmaktadır. Herhangi bir veri setine yönelik arama ve tarama
fonksiyonları ile beraber yeni
temalar ve fikirler oluşturulup farklı kategoriler meydana
getirilerek teorik alt yapıya destek
sağlayabilir. Veriler farklı türdeki dosya biçimlerini
desteklemektedir (örneğin; SPSS, Html,
Xml ve CSV). Ayrıca, bu program araştırmacıların işbirlikçi
çalışmalarına imkân vererek
ortak kodlamalar yapılabilir ve kodlamalar arası karşılaştırmalar
neticesinde güvenirlik
işlemleri uygulanabilir. Verilerin kolayca araştırmacılar
tarafından incelenerek hipotezlerin
sınanarak yorumlar yapılmasına olanak sağlar.
Araştırmanın Amacı ve Önemi
Türkiye’de son yıllarda bilgisayar destekli nitel veri analizi ile
ilgili akademik
çalışmalar artmıştır. Üniversiteler, akademik konferanslar ve
eğitim şirketleri araştırmacıların
kendi alanlarındaki çalışmalarını nitel araştırma
paradigmalarına uygun olarak
sürdürebilmelerine; yazılı, işitsel, görsel dosyaları rahatça
işleyebilme, şekillendirebilme ve
yorumlayabilmelerine yardımcı olmak amacıyla bilgisayar
destekli nitel analiz eğitimleri ve

çalıştayları düzenlemektedir. Ayrıca, bilgisayar destekli nitel
veri analizi dersi üniversitelerin
yüksek lisans ve doktora programlarında okutulan dersler
arasındadır.
Bilgisayar destekli nitel veri analizi ile ilgili yapılan birçok
çalışma kullanılan paket
programları tanıtan niteliktedir. Örneğin, Birkök (2008)
çalışmasında bilgi işlem yazılımların
araştırma tekniklerine katkısını incelemektedir. Bu çalışmasında
daha sonra Atlas.ti
yazılımının önemli bulunan işlevleri örnek olarak açıklanmıştır.
Kuş (2006b) ise, bilgisayar
destekli veri analizi ile ilgili doktora çalışmasında Nvivo
yazılımını tanıtmıştır. Ayrıca, aynı
yazar 2011 yılında Nvivo ve MAXQDA yazılımlarını
karşılaştırdığı bir çalışma daha
yayımlamıştır. Baş ve Akturan (2013)’ün kitabında
araştırmacıların bilgisayar destekli nitel
veri analizi yapmalarını sağlayacak NVivo programının
kullanımı son derece ayrıntılı olarak
açıklanmıştır. Coşgun, İlgar ve İlgar (2014) nitel veri analizinin
bilgisayar programları
aracılığıyla nasıl yapılacağının betimlenmesi ve genç
araştırmacılara tanıtılması amacıyla bir

makale yayımlamışlardır. Yalçın, Yavuz, İlgün Dibek (2015)’in
çalışmasına göre eğitim
bilimleri alanında yapılan araştırmalarda en çok nitel veri analiz
programlarından Nvivo ve
ATLAS.ti yazılımının kullanıldığını belirtilmiştir. Arık ve
Türkmen (2009) ise, Türkiye’de
eğitim bilimleri alanındaki nicel araştırmalarda en fazla SPSS
programının ardından LISREL
programının sık kullanıldığını söylemektedir.
Data Analysis
Öte yandan, bilgisayar destekli nitel veri analizinin yapıldığı
çalışmaları inceleyen bir
araştırmaya rastlanmamıştır. Bilgisayar destekli nitel veri
analizini bir tanımın ötesinde
anlamanın en iyi yollarından biri, akademik dergilerde
yayımlanan çalışmaları incelemektir.
Bunun için bu çalışmada, uluslararası indeksler tarafından
dizinlenen (SSCI) bir dergide

(Eğitim ve Bilim dergisinde) yayımlanan makaleler nitel veri
analizinde bilgisayar kullanma
ölçütüne göre incelenmiş ve çeşitli değişkenler açısından analiz
edilerek bu araştırmaların
genel eğiliminin belirlenmesi amaçlanmıştır.
Bu amaç doğrultusunda aşağıdaki sorulara yanıt aranmıştır:
1. 2011-2016 yılları arasında yayımlanan makalelerin araştırma
yöntemlerine göre
dağılımları nasıldır?
2. Nitel veri analizinin yapıldığı makalelerde bilgisayar-destekli
veri analizi
yapılmış mıdır?
3. Bilgisayar-destekli nitel veri analizi için hangi bilgisayar
paket programları
kullanılmıştır?
4. Kullanılan bu bilgisayar programlarına ait özellikler
makalede yer almış mıdır?
5. Bilgisayar-destekli nitel veri analizinin yapıldığı makalelerin
betimsel özellikleri
nelerdir?
a. Makalelerin yıllara ve kullanılan bilgisayar programlarına
göre dağılımı

nasıldır?
b. Araştırma yöntemi ve araştırma desenleri nelerdir?
c. Makalelerin üniversitelere göre dağılımı nasıldır?
Yöntem
Araştırmanın Modeli ve Kapsamı
Bu araştırma tarama modelinde bir araştırmadır. 2011 - 2016
yılları arasında
yayımlanan makalelerin nitel veri analizinde bilgisayar
kullanma ölçütüne göre incelendiği ve
çeşitli değişkenler açısından analiz edilerek genel eğilimin
belirlenmesinin amaçlandığı bu
çalışmada betimsel içerik analizi yöntemi kullanılmıştır (Çalık
& Sözbilir, 2014). Çünkü
içerik analizi çalışması birbirine benzer verileri belirli
kavramlar ve temalar çerçevesinde bir
araya getirmek ve bunları okuyucunun anlayabileceği bir forma
göre düzenleyerek
yorumlamaktır (Creswell, 2016b).

Eğitimi Dergisi
Son yıllarda nitel araştırmaların artmasıyla beraber nitel veri
analizinde bilgisayar
programlarının kullanımında da artış olmuştur. Bu nedenle 2011
- 2016 yılları arasında
yayımlanmış makaleler bu araştırmanın kapsamına alınmıştır.
Verilerin Toplanması
Veri toplama aşamasında, yılda dört kez yayınlanmakta olan
Eğitim ve Bilim dergisinin
2011 yılının ilk sayısından (159. Sayı) 2016 yılının son sayısına
(188. Sayı) kadar olan tüm
sayıları araştırmaya dâhil edilmiştir. Duyuruları önceden
yapılmak koşulu ile 2014 yılından
itibaren yılda iki özel sayı çıkarılmaktır. Bu kapsamda 30
sayıda yer alan 688 makale
araştırma kapsamında incelenmiştir. Bu makalelerin
yöntemlerine göre dağılımları
belirlendikten sonra nitel ve karma yöntem araştırmaları
incelenerek nitel veri analizinde
bilgisayar programı kullanan makaleler belirlenmiştir.
Makalelerin seçimindeki ölçüt;

bilgisayar destekli nitel veri analizi yapılması ve kullanılan
paket programın belirtilmiş
olmasıdır. Bu ölçütlere göre çalışmanın amacına uygun 28
makale belirlenmiştir.
Veri Toplama Aracı
Makalelerin kodlanması ve değerlendirilmesi aşamasında
araştırmacılar tarafından alan
yazındaki içerik analizi çalışmalarında kullanılan formlardan da
yararlanılarak çalışmaya özgü
bir form geliştirilmiştir (Boztunç Öztürk; Eroğlu & Kelecioğlu;
2015, Aztekin & Taşpınar
Şener; 2015). Veri toplama aracı olarak kullanılan bu form 3
ana bölümden oluşmaktadır. İlk
bölümde araştırmanın künyesi (başlığı, yazarları, yayın yılı,
dili, üniversite, konu alanı), ikinci
bölümde araştırmanın yöntem bölümü (araştırma modeli,
örneklem türü, örneklem büyüklüğü
ve özellikleri, veri toplama araçları, verilerin kaydedilmesi, veri
analizi, veri analizinde
kullanılan paket programlar, araştırmanın geçerlik ve
güvenirliği) yer almaktadır. Son
bölümde ise, ‘makalede veri analizinde kullanılan bilgisayar
programının bir çıktısı (tablo,

şekil, grafik) var mı?’ sorusuna yanıt aranmaktadır (Tablo 1).
Verilerin Analizi
2011-2016 yılları arasında yayımlanan makalelerden elde edilen
verilerin
değerlendirilmesinde içerik analizi tekniği kullanılmıştır. Bunun
için öncelikle araştırmaya
dâhil edilen bütün makaleler dikkatlice okunmuş ve veriler veri
toplama aracı olarak
kullanılan forma kaydedilmiştir. Tüm makaleler incelenip
veriler forma kaydedildikten ve
form son şeklini aldıktan sonra veriler nitel araştırma yazılımı
olan ATLAS.ti kullanılarak
analiz edilmiştir. ATLAS.ti programının seçilmesinin nedeni
araştırmacıların bu programın
kullanımı konusunda bilgi sahibi olmalarıdır. Araştırmanın
başlığı, yazarları, üniversite, konu
Data Analysis
alanı, örneklem türü, örneklem büyüklüğü ve özelliklerinin

kodlanmasında açık kod
kullanılırken; araştırmanın yayın yılı, dili, araştırma modeli,
veri toplama araçları, verilerin
kaydedilmesi, veri analizi, veri analizinde kullanılan paket
programlar, araştırmanın geçerlik
ve güvenirliği için kod listesi oluşturulmuştur. 12 temel
kategori altında incelenen her bir
çalışma M1, M2, … M28 şeklinde kodlanmış ve araştırmada bu
kodlar kullanılmıştır (Ek.1).
Son olarak analiz edilen veriler tablo ve grafikler halinde
sunulmuştur.
Geçerlik ve Güvenirlik
Araştırmanın iç geçerliğinin sağlanması amacıyla, İçerik
Analizi Veri Formu, bilgisayar
ve öğretim teknolojileri eğitimi alanında uzman biri tarafından
incelenmiş ve alınan dönütlere
Tablo 1 İçerik Analizi Veri Toplama Formu
BÖLÜM 1
ARAŞTIRMANIN
Başlığı:
Yazarlar:

Yayın yılı:
Yayın dili: Türkçe () İngilizce ()
Üniversite:
Konu alanı:
BÖLÜM 2
ARAŞTIRMA YÖNTEMİ:
Nitel () Karma ()
Örneklem yöntemi:
Örneklem Büyüklüğü:
Katılımcı türü:
İlkokul öğrencisi()
Ortaokul öğrencisi ()
Lise öğrencisi ()
Lisans öğrencisi ()
Yüksek lisans öğrencisi ()
Stajyer öğretmen ()
Öğretmen okul müdürü ()
Bireysel ()

Grup ()
Bireysel ve grup ()
Diğer ()
VERİ TOPLAMA ARAÇLARI:
Doküman incelemesi () Görüşme () Yarı yapılandırılmış
görüşme () Yapılandırılmış görüşme ()
Odak grup görüşme () Gözlem () Açık uçlu anket ()
VERİ TOPLANIRKEN: Ses kaydı () Video
kaydı () Not alma ()
VERİ ANALİZİ: Betimsel analiz () İçerik analizi
()
VERİ ANALİZİNDE KULLANILAN PAKET PROGRAMLAR:
MS Word ()
MS Excel ()
Nvivo ()
Atlas.ti ()
SPSS ()
MaxQDA ()

HyperResearch ()
ARAŞTIRMANIN GEÇERLİK VE GÜVENİRLİĞİ:
Geçerlik ile ilgili bilgi: Var () Yok ()
Geçerlik ile ilgili bilgi varsa;
Uzun süreli katılım ()
Üçgenleme ()
Akran incelemesi ()
Üye kontrolü ()
Zengin ve yoğun betimleme ()
Dış denetimler ()
Güvenirlik ile ilgili bilgi: Var () Yok ()
Güvenirlik ile ilgili bilgi varsa;
Kodlayıcılar arası görüş birliği ()
Verinin kayıt cihazı ile kaydedilip yazıya aktarılması ()
Doğrudan alıntılar yapma ()
BÖLÜM 3
Bilgisayar destekli veri analizinde kullanılan paket programın
özelliklerinden yararlanılarak elde edilen

NORMAN, ELTON_BUS7380-8-62NORMAN, ELTON_BUS7380-8-61.docx

NORMAN, ELTON_BUS7380-8-62NORMAN, ELTON_BUS7380-8-61.docx

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