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Doing Qualitative Data Analysis with NVivo By Dimitri Mortelmans

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Document details

Pages: 289
File size: 7.95 MB
Format: Digital PDF
Course: DATA ANALYSIS
Category: eBook[PDF]

About this ebook

Doing Qualitative Data Analysis with NVivo" by Dimitri Mortelmans is an open-access textbook designed to bridge the gap between qualitative research practice and software utilization. Rather than acting as a simple button-by-button manual, it approaches NVivo from a researcher's perspective, focusing heavily on gaining workflow efficiency. [1, 2, 3, 4]

The book is structured around NVivo’s core strengths—data management, coding, and data retrieval/analysis—and covers the following key topics: [1]

📑 Methodological & Introductory Concepts

The "Code-and-Retrieve" Principle: Understanding the foundational logic behind computer-assisted qualitative data analysis (CAQDAS) software. [1, 2]
Critical Appraisal of Software: Examining misunderstandings, potential pitfalls (like conflating coding with analysis or distancing oneself from the data), and the true capabilities/limitations of NVivo. [1, 2]
Paradigms in Qualitative Research: Navigating how NVivo seamlessly integrates into different methodologies such as Grounded Theory, thematic analysis, and framework analysis. [1, 2]

🛠️ Core & Basic Skills

Data Management & Importation: Preparing and organizing diverse project data.
Handling Multi-Media Formats: Working with standard textual transcripts (interviews, focus groups) as well as audiovisual materials (audio recordings, video, and images).
Working with Memos: Documenting analytical ideas, creative reflections, and the evolution of the research process.
Coding Qualitative Data: Practical pathways for assigning codes to segments of your data, including inductive coding practices. [1, 2, 3]

🚀 Advanced Analysis Tools

Case Coding & Classifications: Structuring units of analysis (like individuals or sites) alongside demographic or attribute data.
Queries: Harnessing NVivo's retrieval capabilities to explore patterns, including text search queries, coding queries, and matrix coding queries.
Matrices and Frameworks: Utilizing cross-tabulation tools to spot relationships and synthesize cross-sections of data.
Models and Maps: Conceptually mapping out relationships and developing visual frameworks directly inside the software.
AI Tools: Leveraging contemporary artificial intelligence features embedded within NVivo for tasks like transcription and pattern exploration.
Mixed Methods Integration: Working with survey data by isolating text variables (such as open-ended questions) and preparing data to link back with statistical software. [1, 2, 3, 4, 5]