Qualitative Data Analysis with NVivo

Kristi Jackson, Patricia Bazeley

• Publisher: SAGE Publications Ltd
• Year: 2019
• ISBN:
  9781526478474
• Edition: 3
• Topic: Social Sciences
• Subtopic: Social Science Research & Methodology
• Index: Social Sciences

Engaging and accessible, this book offers students a complete guide to using NVivo for qualitative data analysis. Drawing on their wealth of expertise, the authors offer detailed, practical advice that relates to students' own experience and research projects.

Packed with real-world examples and case studies, the book supports students through every stage of qualitative data analysis. The Third Edition:

• Contains fully integrated instructions for using NVivo on both Mac and PC, with screenshots and click-by-click guidance.
• Seamlessly interweaves theory and practice in easy-to-follow steps.
• Empowers students to develop their critical thinking.

Accompanied by video tutorials for both Mac and PC, web links and a host of other helpful online resources, this step-by-step book removes students? anxiety about tackling data analysis. Whether for advanced researchers or those approaching the task for the first time, this clear, yet comprehensive guide is the perfect companion for anyone doing qualitative data analysis with NVivo.

1 Where to Begin?

• Section 1.1: Introduction to qualitative research with NVivo 2
• Section 1.2: Conceptual grounding in qualitative research purposes and NVivo 6
• Section 1.3: Using NVivo to get started on your research 9
• Section 1.4: Chapter 1 Takeaways 34

Maintaining a craft-like approach to research can help to open up critically imaginative ways of working with computers (as techniques of representation) and avoiding the tendency for these programmes to become black-boxes or demonised gadgets. (Hinchliffe, Crang, Reimer, & Hudson, 1997: 1123)

Section 1.1: Introduction to Qualitative Research with NVivo

Before diving into NVivo, it is important to understand the contexts in which this software evolved and the various arguments researchers have made about the role of software in qualitative research. You are likely to hear a range of perceptions about the utility of the software (or problems with using it). Having a background in this debate will help you decide where you stand and will provide some ideas as you start shaping your claims about the use of NVivo in your research. After this introduction, we encourage you to play with your ideas and your data (this could be supplementary data, like literature). You do not need an exceptionally clear idea about where you are going yet. This chapter is simply designed to get you started and get you thinking.

In this chapter you will

• Learn the basic arguments exchanged between camps regarding the utility of software like NVivo (summarized via the metaphors of snake oil, silver bullet, and cart/horse).
• Find out why we advocate a methods-with mantra (Jackson, 2017) rather than a methods-first mantra.
• Consider strategies for getting started and thinking about your data.
• Discover how to install the software.
• Understand how to get familiar with the software by exploring the Sample Project.
• See how to create a Project of your own.
• Learn tactics for reflecting on your ideas with Maps, Memos, See Also Links, and Hyperlinks.

Qualitative research

Qualitative methods are a powerful choice when you want to understand details of a process or experience, need more information to determine the boundaries or characteristics of the issue being investigated, or assess – for a variety of reasons – that the best information available is non-numeric (e.g., text or visual). The questions that could benefit from a qualitative approach emerge from many fields such as criminal justice, education, finance, health care, marketing, organizational development, public policy, sports, and user experience. For example:

• After participating in an alternative drug treatment programme, what do incarcerated young adults think about their opportunities after release?
• How does a customized, after-school biology programme for girls influence their interest in a career in science?
• How do company reports explain ‘negative news’ (e.g., losses, legal challenges, declining share values) to shareholders?
• What are physician perceptions of barriers to diagnosing and treating diabetes among immigrants?
• Why does a specific marketing strategy for fire alarm/smoke detectors work well in urban areas but not in rural areas?
• When organizational leaders incorporate meditation practices into their businesses, how do relationships between employees change?
• What processes need to be in place for health impacts to be considered when infrastructure development is being planned?
• What factors are taken into account before a professional gymnast considers moving away from home for intensive coaching?
• How do NVivo users perceive the relevance of a new software tool?

The diversity of fields and multitude of questions are part of the thrill of qualitative research and you will find questions that invite qualitative data and analysis around every corner as you continue building your expertise.

This ‘big tent’ also brings unique challenges, primarily regarding the many choices that need to be made about how to handle the data. Choices will vary depending on whether the research involves, for example, exploration, description, comparison, pattern analysis, theory testing, theory building, or evaluation. Another important choice is the methodology or combination of methodologies used, and these are constantly evolving and sometimes overlapping. They include action research, conversation analysis, ethnography, life history, grounded theory, and phenomenology. Methodologists routinely urge researchers to assess the fit between purpose and method, with the choice to use a qualitative approach being determined by the research question and purpose, rather than by prior preference of the researcher (Maxwell, 2013; Richards & Morse, 2012). The same is true regarding the use of NVivo, where tools used should be informed by the goals of the research rather than just ease of use, visual appeal or familiarity.

Origin and evolution of NVivo

Most researchers engaged in qualitative data analysis have heard of Qualitative Data Analysis Software (QDAS) or Computer Assisted Qualitative Data AnalysiS (CAQDAS) and know that NVivo is one of the options for storing, managing, and analysing qualitative data. However, few qualitative researchers are aware of how long the software has been around or know the ways in which it has been discussed alongside (or in comparison with) ‘manual’ methods. While you need not be an expert in the history of the various camps that debate the dangers and opportunities of using QDAS, it is wise to understand the general lay of the land and the traditions that inform the diverse uses of NVivo. In this chapter we discuss some of this background to help you begin situating yourself amidst the diversity and we provide suggestions to help you clarify your qualitative approach and get excited about your unique research. We end by walking you through some basic steps to write about and map your research plans to help you sort through and frame your early thoughts with your research questions and your data.

The current version of NVivo is based on the work of Lyn and Tom Richards, who began developing the software in 1981. They founded Qualitative Solutions and Research (later becoming QSR International) in 1995 and since that time NVivo has retained the core features of handling text data via coding, writing, linking, adding demographics, searching for patterns, and reporting or exporting data. Since the construction of these early tools, the subsequent software developers incorporated additional capabilities to analyse a wide range of data types (pdf files, audio, video, images, surveys, reference managers, web pages, social media, etc.) with increasingly complex searches and modes of output (textual, numeric, and visual – via graphs, charts, and maps).

Three metaphors

Depending on the people you know who use NVivo, the kinds of research they do and whether you are a novice or have considerable experience with qualitative research, your impressions of the software will vary. Your use and discussion of the software will be influenced by your theoretical frameworks and research questions, the colleagues with whom you work, the types of data you handle, the modes you intend to use for communicating your results, and the stakeholders who are interested in the implications of your research. When you read accounts of QDAS – including arguments about the potential dangers and opportunities of using it – you will become aware of three metaphors in the literature. As with most metaphors, these carry a grain of truth. However, the oversimplification and subsequent strategic use of these metaphors by many authors to justify their own positions have nearly robbed them of their merits and have often turned them into clichés.

The silver bullet

The enthusiasm of the early adopters regarding the potential of QDAS was articulated by Miles and Huberman (1994), who argued that the flexible, recursive, and iterative capabilities of software provided unprecedented opportunities to challenge researcher conceptualizations. The Richards (1994) agreed and stated that as they began developing NUD*IST (subsequently becoming NVivo) their analysis ‘became far surer, with provision for constant interrogation of themes. The processes of building and interrogating themes gave an impression of constant working at theory built up and peeled back in onion skin layers’ (p. 164). Despi...

Table of contents

• Cover
• Half Title
• Publisher Note
• Title Page
• Copyright Page
• Contents
• Illustration List
• Table List
• About the Authors
• Preface to the Third Edition
• Online resources
• Acknowledgements
• 1 Where to Begin?
• 2 Designing an NVivo Project
• 3 Coding Foundations
• 4 Advanced Coding
• 5 Cases, Classifications, and Comparisons
• 6 Surveys and Mixed Methods
• 7 Querying data
• 8 Literature Reviews and pdf Files
• 9 Working with Multimedia Files
• 10 Twitter, Facebook, YouTube, and Web Pages
• 11 Teamwork
• 12 Moving on – Further Resources
• References
• Index