Workshop 2 using nvivo 12 for qualitative data analysis

1. USING NVIVO 12 FOR
QUALITATIVE DATA ANALYSIS:
HANDS-ON INTRODUCTION
Dr Yaar Muhammad

2. WELCOME

3. LEARNING OBJECTIVES
After this workshop you will be able to:
Understand the various terms associated with NVivo 12 for Windows
and qualitative data analysis,
Import and organize data for analysis within NVivo 12 project,
Code qualitative data using various coding techniques,
Analyse qualitative data by reading, summarizing and interpreting the
patterns in data,
Share the outcomes of qualitative data analysis with others.

4. SEVEN STAGES OF AN INTERVIEW
INVESTIGATION
Source: (Kvale, 1996) 4
No. Stage Steps to be taken
1 Thematizi
ng
Formulate the purpose of an investigation.
Construct conceptual framework.
2 Designing Plan the design of the study (research site, sampling and
recruitment process) taking into account the moral
implications.
Develop interview guide
3 Interviewin
g
Conduct the interviews based on an interview guide.
Record the conversation.
4 Transcribi
ng
Convert oral speech to written text.
5 Analzing Decide methods of analysis.
6 Verifying Ascertain the trustworthiness of the interview findings.
7 Reporting Communicate the findings.

5. ANALYZING (STAGE 5)
EDUC 7741/PARIS/TERRY

6. STEPS IN QUALITATIVE ANALYSIS
THROUGH NVIVO
1. Importing Data (Files)
2. Coding Data
3. Creating framework matrices
4. Reporting findings

7. Start1 QSR2
Nvivo
12
3

8. 8

9. 1. IMPORTING DATA (FILES)

10. 10
Navigation View
List View
Detail View
The NVivo Workspace
Quick Access
Toolbar

11. 11
Can add:
Word documents (doc, docx) and editable
RTF files (.rtf) and editable
PDF files (.pdf)
Audio files (.mp3, .wav)
Movie files (.wmv, .mp4)
Web pages (as pdf via NCapture in IE or
Chrome)
Survey data (spreadsheet format)

12. Right
click
here
1
Select
import
items
2
Select
file3 Open4
Or click here

13. Click Files
1
Double
click
imported
file
2
Document
will be
shown in
Detail
View.
3
Viewing imported documents in
NvivoAfter you have successfully imported the item, go to
List View,
double-click to select the document you imported.
The imported document will be shown in Detail View.

14. 14
List View
Detail View

15. 2. CODING DATA

16. WHAT IS A CODE?
A code is an abstract representation of an object or phenomenon
(Corbin & Strauss, 2008: 66).
Coding is a way of ‘tagging’ text with codes, of indexing it, in order to
facilitate later retrieval.
A way of identifying themes in a text (Bernard & Ryan, 2010).

17. CODING EXAMPLE
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18. APPROACHES TO CODING
Broad-brush or ‘bucket’ coding (Lumping): ‘chunk’
the text into broad topic areas, as a first step to seeing
what is there, or to identify just those passages that
will be relevant to your investigation.
Micro-coding or fine grain coding (Splitting): detailed,
slow, reflective exploration of early texts – doing line-
by-line coding, reading between the lines, identifying
concepts and thinking about all of each concept’s
possible meanings as a way of ‘breaking open’ the
text.
Most end up working with some combination of the

19. FIRST CYCLE CODING METHODS
Coding Type Description Example
Descriptive Coding Descriptive Coding summarizes in a word or short phrase –
most often as a noun – the basic topic of a passage of
qualitative data.
Magnitude Coding To indicate intensity, frequency, direction, presence, or
evaluative content.
L, 4XL
Process Coding Process Coding uses gerunds (“-ing” words) exclusively to
connote action in the data
Reading, playing,
watching TV, drinking
coffee
Emotion Coding Emotion Codes label the emotions recalled and/or
experienced by the participant, or inferred by the
researcher about the participant.
Confusion, Scared,
Crying
Values Coding Values Coding is the application of codes onto qualitative
data that reflect a participant’s values, attitudes, and
beliefs, representing his or her perspectives or worldview.
Future is scary
Versus Coding Versus Codes identify in dichotomous or binary terms the
individuals, groups, social systems, organizations,
phenomena, processes, concepts, etc., in direct conflict
State vs. District
Prescription vs.
AutonomySource: (Saldana, 2013)

20. FIRST CYCLE CODING METHODS
Coding Type Description
In Vivo Coding Refers to a word or short phrase from the actual language found in the
qualitative data record.
Simultaneous
Coding
Application of two or more different codes to a single qualitative datum.

21. 21

22. Click Files
from
navigation
view
1 Select
internals2
From List
View,
double-
click a file
3
Select text,
then Right-
click
4
•Select
Code item
•Or Name
New Node
5 Press OK
6

23. ALTERNATIVE WAYS OF ADDING
CODING
1
• Click Files from
navigation view
2
• Select internals
3
• From List View, double-
click a file
4
• From navigation view,
click node
5
• Select Code item
• Or Name New Node
6
• Drag the text from the
file to drop at the
desired code.

24. SORTING NODES INTO TREES?
In NVivo, nodes can be structured in a branching tree system with
categories, subcategories and sub-subcategories.
Just as folders and subfolders in your computer filing system help
you to organize your files,
Nodes in ‘trees’ will allow you to organize your categories into
conceptual groups and subgroups.
Source: (Bazeley & Jackson, 2013)

25. SECOND CYCLE CODING METHODS
Coding Type Definition
Pattern Coding Similar codes are assembled together to analyze their commonality and
to create a Pattern Code.
Focused Coding Focused Coding searches for the most frequent or significant codes to
develop “the most salient categories” in the data.
Axial Coding Axial Coding’s purpose is to determine which codes in the research are
the dominant ones and which are the less important ones and to
reorganize the data set: synonyms are crossed out, redundant codes
are removed and the best representative codes are selected.
Source: (Saldana, 2013)

26. Source: (Saldana, 2013) 26
CODES-TO-THEORY MODEL FOR QUALITATIVE INQUIRY

27. EXAMPLE OF CODES-TO-THEORY
MODEL
Source: (Saldana, 2013)

28. CREATE A PARENT TREE NODE
(WITHOUT CODING)
Share> Copy Project.
Nodes can be moved, appended, and merged as needed to create
your structured coding system.
Moving nodes into trees
Nodes can be dragged into a tree, or from one tree to another.
1. Click to select, then click and drag to the parent node.
2. Alternatively, Cut (or Copy) and Paste.

29. 3. CREATING FRAMEWORK
MATRICES

30. First create cases from imported sources
In List View of Data,
Select all of the FILES that you want to turn into cases.
Right-click (on the sources you’ve selected) > Create As > Create As
Cases
Go to your case folder to see the cases you created. Double-click on a
case to
open it, and you will see that 100% of the content in the source has
been coded
to the case node.

31. Create a new classification
In Navigation View for
Classifications, select Node
Classifications.
In List View > Right-click (in the
empty space) > New Classification.
Name your new classification, and
select OK.
Create attributes and values
In List View of Case Classifications
> Right-click on the classification
you created
earlier > New Attribute.
Provide a Name for your new
attribute and determine the
attribute Type

33. Creating the framework
In the Navigation View of Notes, select
Framework Matrices.
In List View, Right-click > New
Framework Matrix > provide a Name.
In the Rows tab, select the case nodes
you want to examine. Optionally select
an attribute with values you want the
cases to be sorted by.
In the Columns tab, select the nodes
for which you want to see and
summarize content.

34. DATA DISPLAY: FRAMEWORK
MATRIXParticipants Node 1 Node 2 Node 3 Node 4
Participant 1
Participant 2
Participant 3
Participant 4
Participant 5
Participant 6…
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35. CROSS-CASE ANALYSIS OF DATA
Cross-case comparisons facilitates interpretations of data patterns and themes
A pattern can be characterized by:
• similarity (things happen the same way)
• difference (they happen in predictably different ways)
• frequency (they happen often or seldom)
• sequence (they happen in a certain order)
• correspondence (they happen in relation to other activities or
events)
• causation (one appears to cause another)
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Source: (Saldana, 2013)

36. 4. REPORTING FINDINGS

37. ASSERTION DEVELOPMENT
Write empirical assertions generated largely through
induction.
Empirical assertions may vary in scope and in level of
inference.
This is done by searching the data corpus- reviewing the
full set of field notes, interview notes or audiotapes, site
documents, and audiovisual recordings.
Establish an evidentiary warrant for the assertions.
This is done by reviewing the data corpus repeatedly to
test the validity of the assertions that were generated,
seeking disconfirming evidence as well as confirming
evidence.
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Source: (Saldana, 2013)

38. ASSERTIONS: EXAMPLE
The findings from the interview data in relation to the teaching of
cultural diversity suggested that most of the teachers – from public
and private schools – had been teaching only the content that was
included in the PS textbooks. Participants provided a variety of
reasons for generally confining themselves to teaching the textbooks’
content. For example, they perceived that they had a duty to follow
the topics in the textbooks. They reported that their teaching
schedules were too tight to add extra content on cultural diversity.
They noted that in order to prepare students for the state
examinations they generally restricted themselves to the textbooks’
content. Some interviewees commented that a lack of cultural
diversity in their school and student population (usually drawn from
single ethnic or religious groups) inclined them to teach the
textbooks’ content as it was.
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Source: (Muhammad & Brett, 2017)

39. REMEMBER!
If systematic evidence to warrant the assertions
is not presented,
the researcher is justly open to criticism of the
analysis as merely anecdotal.
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40. REFERENCESBazeley, P., & Jackson, K. (2013). Qualitative data analysis with NVivo.
London: Sage Publications Ltd.
Kvale, S. (1996). InterViews: An introduction to qualitative research
writing. Thousand Oaks: Sage Publications.
Muhammad, Y., & Brett, P. (2017). Some challenges in teaching
citizenship in an Islamic context: Pakistan Studies teachers’ perspectives
and practices in relation to teaching about Identity. Citizenship Teaching
& Learning, 12(3), 279–298.
Saldaña, J. (2013). The coding manual for qualitative researchers (2nd
ed.). London: Sage Publications Ltd.
Schreier, M. (2012). Qualitative content analysis in practice. London: Sage
Publications.
QRCA. (n.d.). What is Qualitative Research? Retrieved from
http://www.qrca.org/?page=whatisqualresearch
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