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Qualitative Data Analysis using
NVivo
Dr Helen Dixon
@HelenDixon10
 By the end of this session you should:
 Have an understanding of the nature of qualitative
data
 Be aware of the features of qualitative analysis
 Be aware of the challenges of analysing qualitative
data
 Be able to import and code documents using NVivo
 Be able to produce queries and reports in NVivo
Aims and Objectives
@HelenDixon10
 Non-numerical – converse of quantitative data
 Typically word based – but may include
imagery, video, etc.
 Can record attitudes, behaviours, experiences,
motivations, etc.
 Descriptive – describing events/opinions etc.
 Explanatory – explaining events/opinions etc.
What is Qualitative Data?
@HelenDixon10
•What are the barriers to using
social media as a research tool?What?
•How are researchers using social
media to gather data?How?
•Why are some people reluctant to
take part in social media research?Why?
Use Qualitative Data to Answer
What/How/Why Questions
@HelenDixon10
Examples of Qualitative Data Sources
 Interviews
 Focus groups
 Speeches
 Questionnaires
 Journals/diaries
 Documents
 Observation
 Audio/visual
materials
 Websites
 Social media
@HelenDixon10
Identify
similarities
Extract themes
Identify
relationships
Highlight
differences
Create
generalisations
Analysing Qualitative Data
To draw conclusions
To develop theories
To test hypotheses
Objectives of Qualitative Analysis
@HelenDixon10
 Divide data into meaningful units
 Use words/phrases e.g. ‘physical environment’,
‘interpersonal relationships’
 Codes can be ‘data-driven’ or ‘theory-driven’
 Deductive coding codes are developed before examining
the data
 Inductive coding codes are derived from the data
 In NVivo, codes are stored within Nodes
 Keep a master list of codes used
Coding Data
@HelenDixon10
•What are the
attributes of the
source?
Descriptive
•What are the
topics being
discussed?
Thematic •What is going on?
•How can this be
interpreted?
Analytic
Types of Code
@HelenDixon10
Types of Code
 This took place at Head
Office
 This is about
discrimination against
women
 This is a reflection on
misogyny in the
workplace
Analytic
Descriptive
Thematic
@HelenDixon10
Interpersonal
relationships
Family
Parent-child
Spouse/
partner
Sibling
Non-family
Friends
Work
colleagues
Tree (Hierarchical) Coding
@HelenDixon10
 Large amount of data
 Subjective nature of data
 Validity of data
 Use triangulation to increase reliability
 No standard processes for coding or
extracting themes
 Time constraints
Challenges
@HelenDixon10
• Create database for storing different sources
(text, audio, video, web resources, etc.)Manage data
• Annotate data
• Attach memos to filesManage ideas
• Identify commonly occurring words
• Collate data relating to a theme or conceptQuery data
• Illustrate relationships using models
• Report knowledge developed from dataModel & report
How can NVivo Help?
YouTube Video@HelenDixon10
Qualitative Analysis Using NVivo
Import Code
Query &
Visualise
AnnotateSummarise
@HelenDixon10
 Complex package that can take time to learn
 Can distance researcher from their data
 Researcher can get caught in ‘coding trap’
 Can identify references to phrases but cannot
discern different contexts
 Will not compensate for poor data or weak
interpretive skills!
Limitations
@HelenDixon10
Qualitative data analysis using NVivo
 Source – your data
 Documents, audio, video, images, etc.
 Memo – item in a project linked to a document or node
 Node – a code or concept (theme node) or a component of
your project e.g. participant or location (case node)
 Can be free or tree
 Classification – applied to a case or participant e.g. person,
organisation, etc.
 Attributes – data (demographics) known about a case
(participant) recorded separately from the case
Terminology
@HelenDixon10
 Name documents appropriately
before importing
 Text-based data can be imported in .doc(x), .rtf, .txt or text-
based .pdf format
 For Microsoft Word documents, apply consistent heading styles
to use autocoding
 Multimedia files can be imported in a variety of formats
including: .mp3/4, .wav, .jp(e)g
 Edit videos before importing
Importing Sources
@HelenDixon10
 Can connect to SurveyMonkey to import survey
results
 Import datasets such as Excel spreadsheets or Access
database tables
 Cannot edit datasets after importing – format and
structure datasets before importing
 Use NCapture to import social media data such as
Facebook, Twitter or LinkedIn feeds
Other Datasets
@HelenDixon10
•Descriptive code
•Classification/attribute
What is this?
•Thematic code
•Annotation/memo
Why is this
interesting?
•Analytic code
•Memo
Why is this relevant to
my research question?
Coding in NVivo
@HelenDixon10
Auto-coding based on structure or patterns
Coding based on queries
Manual coding in a source
Coding entire sources to a node
Approaches to coding
 Use a separate node for each element
 Who, what, how, when
 Each node should encompass one concept only
 Data can be coded at multiple nodes
 Move free nodes into trees where appropriate
 Organise trees based on conceptual relationships
 Not observed or theoretical associations
 E.g. events, strategies, attitudes, beliefs, characteristics
 Each concept should appear in only one tree
Creating Nodes
@HelenDixon10
RENEWABLE
ENERGY
Image
Video
DatasetInterview
Website
Coding Sources
Create nodes to link
different sources related
to a specific topic or theme
HELEN
Interview
Video
Blog
article
Photo
Case Nodes
You can classify HELEN
node as a PERSON with
attributes such as:
GENDER, AGE,
OCCUPATION, LOCATION,
etc.
You can create nodes
for other ‘cases’ such
as companies,
locations, etc.
Tree Structures in NVivo
 Use memos to tell the story of your research
 Can help you make sense of your data
 Research memo – goals, assumptions, journal
 Source memo – key points of interview/document,
description information, initial perceptions
 Node memo – why theme is important, links to
literature
 Query memo – what results tell you, further queries
Using Memos
@HelenDixon10
 Find and analyse words or phrases
 Text Search Query – search for a word/phrase
 Create a word tree
 Word Frequency Query –
most frequently occuring words
 Create a tag cloud
 Use memos to record what you learn
Queries
Descriptive coding
•Research design, project outline
•Folders, templates, case nodes
Thematic coding
•Finding obvious themes, autocoding
•In Vivo coding
Analytic coding
•Creating node hierarchies
•Using queries, matrices
Developing an NVivo Project
Structuringphase
Creative/analyticphase
Optionalanalyticiterations
Source: Edhlund, B & Mcdougall, A (2013), NVivo 10 Essentials, p. 14
 Create a source folder called ‘Literature’
 Code articles by themes
 Create nodes for statistics, quotes, definitions, etc.
 Annotate content you want to follow-up
 Use memos to add descriptions or critiques
 Use source classifications for date, author, etc.
 Use queries to find common themes or gaps
 YouTube Video
Literature Reviews in NVivo
@HelenDixon10
 Install NCapture for Internet Explorer/Chrome
 Capture content from:
 Web pages
 Online PDFs
 Facebook
 Twitter
 LinkedIn
 YouTube
 http://help-ncapture.qsrinternational.com/desktop/welcome/welcome.htm
 http://nsmnss.blogspot.co.uk/2014/08/7-ways-nvivo-helps-researchers-
handle.html
Web Pages and Social Media Data
 Code data at multiple nodes
 Use descriptive, thematic and analytic codes
 Keep a record of your codes and the themes that evolve
 Use a Word Frequency query to help you identify key
phrases
 Use Text Search queries to help you explore themes
 Take time to reflect on what you have found and
record ideas using memos
 Absence can be important! Ask why sources are NOT
coded at a node
 Keep a journal of your analysis process
Tips
@HelenDixon10
 Create your project journal
 Use a model to visualise your preliminary ideas
 Create case nodes for the people, organisations,
places etc. in your project
 Identify possible nodes based on your literature
review
 Prepare your sources for importing – format
documents, clean datasets, edit video/audio
Things to consider early!
@HelenDixon10
 Import documents into NVivo
 Create nodes and code data
 Create memos and annotate data
 Add classifications to a project
 Define attributes for classifications
 Produce reports
 Create Text Search and Word Frequency
queries
Practical Exercises
@HelenDixon10
 NVivo Toolkit: http://explore.qsrinternational.com/nvivo-
toolkit
 Getting Started Guide:
http://download.qsrinternational.com/Document/NVivo10/
NVivo10-Getting-Started-Guide.pdf
 QSR website:
http://www.qsrinternational.com/support.aspx
 QSR Support - @QSRSup - on Twitter:
https://twitter.com/QSRSup
 QSR on Facebook:
http://www.facebook.com/qsrinternational
 QSR on YouTube:
https://www.youtube.com/user/QSRInternational
Online Resources
 Qualitative Data Analysis with Nvivo
 Bazeley, P & Jackson, K (2013)
 NVivo 10 Essentials
 Edhlund, B & Mcdougall, A (2013)
 Using QSR‐NVivo to facilitate the development of a grounded
theory project: an account of a worked example
 Andrew John Hutchison, Lynne Halley Johnston, Jeff David Breckon
 International Journal of Social Research Methodology
 Vol. 13, Iss. 4, 2010
 Using NVivo to Answer the Challenges of Qualitative Research in
Professional Communication: Benefits and Best Practices Tutorial
 Hoover, R.S.; Koerber, A.L.,
 Professional Communication, IEEE Transactions on
 Vol.54, no.1, pp.68,82, March 2011
doi: 10.1109/TPC.2009.2036896
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=533791
9&isnumber=5718246
Literature

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Qualitative data analysis using NVivo

  • 1. Qualitative Data Analysis using NVivo Dr Helen Dixon @HelenDixon10
  • 2.  By the end of this session you should:  Have an understanding of the nature of qualitative data  Be aware of the features of qualitative analysis  Be aware of the challenges of analysing qualitative data  Be able to import and code documents using NVivo  Be able to produce queries and reports in NVivo Aims and Objectives @HelenDixon10
  • 3.  Non-numerical – converse of quantitative data  Typically word based – but may include imagery, video, etc.  Can record attitudes, behaviours, experiences, motivations, etc.  Descriptive – describing events/opinions etc.  Explanatory – explaining events/opinions etc. What is Qualitative Data? @HelenDixon10
  • 4. •What are the barriers to using social media as a research tool?What? •How are researchers using social media to gather data?How? •Why are some people reluctant to take part in social media research?Why? Use Qualitative Data to Answer What/How/Why Questions @HelenDixon10
  • 5. Examples of Qualitative Data Sources  Interviews  Focus groups  Speeches  Questionnaires  Journals/diaries  Documents  Observation  Audio/visual materials  Websites  Social media @HelenDixon10
  • 7. To draw conclusions To develop theories To test hypotheses Objectives of Qualitative Analysis @HelenDixon10
  • 8.  Divide data into meaningful units  Use words/phrases e.g. ‘physical environment’, ‘interpersonal relationships’  Codes can be ‘data-driven’ or ‘theory-driven’  Deductive coding codes are developed before examining the data  Inductive coding codes are derived from the data  In NVivo, codes are stored within Nodes  Keep a master list of codes used Coding Data @HelenDixon10
  • 9. •What are the attributes of the source? Descriptive •What are the topics being discussed? Thematic •What is going on? •How can this be interpreted? Analytic Types of Code @HelenDixon10
  • 10. Types of Code  This took place at Head Office  This is about discrimination against women  This is a reflection on misogyny in the workplace Analytic Descriptive Thematic @HelenDixon10
  • 12.  Large amount of data  Subjective nature of data  Validity of data  Use triangulation to increase reliability  No standard processes for coding or extracting themes  Time constraints Challenges @HelenDixon10
  • 13. • Create database for storing different sources (text, audio, video, web resources, etc.)Manage data • Annotate data • Attach memos to filesManage ideas • Identify commonly occurring words • Collate data relating to a theme or conceptQuery data • Illustrate relationships using models • Report knowledge developed from dataModel & report How can NVivo Help? YouTube Video@HelenDixon10
  • 14. Qualitative Analysis Using NVivo Import Code Query & Visualise AnnotateSummarise @HelenDixon10
  • 15.  Complex package that can take time to learn  Can distance researcher from their data  Researcher can get caught in ‘coding trap’  Can identify references to phrases but cannot discern different contexts  Will not compensate for poor data or weak interpretive skills! Limitations @HelenDixon10
  • 17.  Source – your data  Documents, audio, video, images, etc.  Memo – item in a project linked to a document or node  Node – a code or concept (theme node) or a component of your project e.g. participant or location (case node)  Can be free or tree  Classification – applied to a case or participant e.g. person, organisation, etc.  Attributes – data (demographics) known about a case (participant) recorded separately from the case Terminology @HelenDixon10
  • 18.  Name documents appropriately before importing  Text-based data can be imported in .doc(x), .rtf, .txt or text- based .pdf format  For Microsoft Word documents, apply consistent heading styles to use autocoding  Multimedia files can be imported in a variety of formats including: .mp3/4, .wav, .jp(e)g  Edit videos before importing Importing Sources @HelenDixon10
  • 19.  Can connect to SurveyMonkey to import survey results  Import datasets such as Excel spreadsheets or Access database tables  Cannot edit datasets after importing – format and structure datasets before importing  Use NCapture to import social media data such as Facebook, Twitter or LinkedIn feeds Other Datasets @HelenDixon10
  • 20. •Descriptive code •Classification/attribute What is this? •Thematic code •Annotation/memo Why is this interesting? •Analytic code •Memo Why is this relevant to my research question? Coding in NVivo @HelenDixon10
  • 21. Auto-coding based on structure or patterns Coding based on queries Manual coding in a source Coding entire sources to a node Approaches to coding
  • 22.  Use a separate node for each element  Who, what, how, when  Each node should encompass one concept only  Data can be coded at multiple nodes  Move free nodes into trees where appropriate  Organise trees based on conceptual relationships  Not observed or theoretical associations  E.g. events, strategies, attitudes, beliefs, characteristics  Each concept should appear in only one tree Creating Nodes @HelenDixon10
  • 23. RENEWABLE ENERGY Image Video DatasetInterview Website Coding Sources Create nodes to link different sources related to a specific topic or theme
  • 24. HELEN Interview Video Blog article Photo Case Nodes You can classify HELEN node as a PERSON with attributes such as: GENDER, AGE, OCCUPATION, LOCATION, etc. You can create nodes for other ‘cases’ such as companies, locations, etc.
  • 26.  Use memos to tell the story of your research  Can help you make sense of your data  Research memo – goals, assumptions, journal  Source memo – key points of interview/document, description information, initial perceptions  Node memo – why theme is important, links to literature  Query memo – what results tell you, further queries Using Memos @HelenDixon10
  • 27.  Find and analyse words or phrases  Text Search Query – search for a word/phrase  Create a word tree  Word Frequency Query – most frequently occuring words  Create a tag cloud  Use memos to record what you learn Queries
  • 28. Descriptive coding •Research design, project outline •Folders, templates, case nodes Thematic coding •Finding obvious themes, autocoding •In Vivo coding Analytic coding •Creating node hierarchies •Using queries, matrices Developing an NVivo Project Structuringphase Creative/analyticphase Optionalanalyticiterations Source: Edhlund, B & Mcdougall, A (2013), NVivo 10 Essentials, p. 14
  • 29.  Create a source folder called ‘Literature’  Code articles by themes  Create nodes for statistics, quotes, definitions, etc.  Annotate content you want to follow-up  Use memos to add descriptions or critiques  Use source classifications for date, author, etc.  Use queries to find common themes or gaps  YouTube Video Literature Reviews in NVivo @HelenDixon10
  • 30.  Install NCapture for Internet Explorer/Chrome  Capture content from:  Web pages  Online PDFs  Facebook  Twitter  LinkedIn  YouTube  http://help-ncapture.qsrinternational.com/desktop/welcome/welcome.htm  http://nsmnss.blogspot.co.uk/2014/08/7-ways-nvivo-helps-researchers- handle.html Web Pages and Social Media Data
  • 31.  Code data at multiple nodes  Use descriptive, thematic and analytic codes  Keep a record of your codes and the themes that evolve  Use a Word Frequency query to help you identify key phrases  Use Text Search queries to help you explore themes  Take time to reflect on what you have found and record ideas using memos  Absence can be important! Ask why sources are NOT coded at a node  Keep a journal of your analysis process Tips @HelenDixon10
  • 32.  Create your project journal  Use a model to visualise your preliminary ideas  Create case nodes for the people, organisations, places etc. in your project  Identify possible nodes based on your literature review  Prepare your sources for importing – format documents, clean datasets, edit video/audio Things to consider early! @HelenDixon10
  • 33.  Import documents into NVivo  Create nodes and code data  Create memos and annotate data  Add classifications to a project  Define attributes for classifications  Produce reports  Create Text Search and Word Frequency queries Practical Exercises @HelenDixon10
  • 34.  NVivo Toolkit: http://explore.qsrinternational.com/nvivo- toolkit  Getting Started Guide: http://download.qsrinternational.com/Document/NVivo10/ NVivo10-Getting-Started-Guide.pdf  QSR website: http://www.qsrinternational.com/support.aspx  QSR Support - @QSRSup - on Twitter: https://twitter.com/QSRSup  QSR on Facebook: http://www.facebook.com/qsrinternational  QSR on YouTube: https://www.youtube.com/user/QSRInternational Online Resources
  • 35.  Qualitative Data Analysis with Nvivo  Bazeley, P & Jackson, K (2013)  NVivo 10 Essentials  Edhlund, B & Mcdougall, A (2013)  Using QSR‐NVivo to facilitate the development of a grounded theory project: an account of a worked example  Andrew John Hutchison, Lynne Halley Johnston, Jeff David Breckon  International Journal of Social Research Methodology  Vol. 13, Iss. 4, 2010  Using NVivo to Answer the Challenges of Qualitative Research in Professional Communication: Benefits and Best Practices Tutorial  Hoover, R.S.; Koerber, A.L.,  Professional Communication, IEEE Transactions on  Vol.54, no.1, pp.68,82, March 2011 doi: 10.1109/TPC.2009.2036896 URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=533791 9&isnumber=5718246 Literature

Hinweis der Redaktion

  1. Sort through data to identify similar phrases Extract themes based on phrases Identify relationships between themes Highlight differences between subgroups Identify patterns and processes Build on consistencies to create generalisations Iterative process – need to review initial findings to inform further analysis
  2. Usually need to explain how coding was carried out and present a table of codes for thesis or journal articles
  3. Does not prescribe a method but rather supports a range of methodological approaches Emphasis on storage and retrieval rather than analysis Automated or keyword searches are no substitute for interpretive coding
  4. Make sure you use Heading Styles in Word to create headings – just making the text bold or larger won’t work! Check them in Outline View. Heading 1 for topics and Heading 2 for speakers Text that includes embedded objects cannot be imported. Create hyperlinks after importing a document. Autocoding cannot be applied to a table.
  5. Place an underscore at the beginning of a document name e.g. _Journal so that it will appear at the top of any alphabetical list