Introduction to NVivo for Qualitative Data Analysis Course

Course Overview

This course provides comprehensive knowledge and practical skills required to organize, code, and analyze qualitative and mixed-methods data using NVivo. The course bridges the gap between qualitative research theory and hands-on software application, equipping participants to manage interviews, surveys, focus groups, and multimedia data with rigor and confidence.

Participants will gain a strong understanding of coding, case classification, querying and visualization techniques within NVivo, along with best practices for building a transparent and defensible qualitative analysis workflow. Emphasis is placed on hands-on practice, real project scenarios and building analysis skills that transfer directly to academic, research and organizational work.

Course Duration

5 Days

Target Audience

• Postgraduate students and academic researchers conducting qualitative or mixed-methods studies
• M&E and research officers analyzing interview, survey and focus group data
• Public health and social science researchers
• NGO and development sector program staff conducting qualitative evaluations
• Policy analysts and government researchers
• Data analysts transitioning into qualitative research
• Individuals preparing for thesis, dissertation or funded research projects

Personal Impact

• Strong practical skills in organizing, coding and analyzing qualitative data using NVivo.
• Ability to independently manage large volumes of interview, survey and multimedia data.
• Enhanced capacity to identify themes, patterns and relationships within qualitative datasets.
• Improved confidence in producing defensible, well-documented qualitative findings.
• Increased employability and research competitiveness in academic, NGO and public sector roles.

• Organizational Impact

• Improved rigor and credibility of qualitative research outputs.
• Faster turnaround on interview, survey and focus group data analysis.
• Reduced dependency on external consultants for qualitative analysis.
• Enhanced ability to support evidence-based programming and policy decisions.
• Standardized qualitative data management practices across research teams.

Course Objectives

By the end of the training, participants will be able to:

• Explain core concepts of qualitative data analysis and the role of CAQDAS tools like NVivo.
• Import, organize and manage diverse data sources within an NVivo project.
• Develop and apply coding structures using nodes, cases and classifications.
• Use queries, visualizations and matrices to identify patterns and relationships in data.
• Produce clear, well-documented qualitative findings and reports from NVivo projects.

Module 1: Introduction to NVivo and Data Import

• Overview of qualitative research and computer-assisted qualitative data analysis (CAQDAS).
• Introduction to the NVivo interface, workspace and project setup.
• Importing interviews, transcripts, surveys, PDFs, audio and video files.
• Practical Session: Setting up a project and importing sample data.

Module 2: Organizing Data, Cases and Classifications

• Organizing sources into folders, cases and datasets.
• Case nodes and demographic classifications.
• Assigning attributes for comparative analysis.
• Practical Session: Building a classification sheet.

Module 3: Coding Fundamentals

• Understanding nodes and the coding process.
• Creating, organizing and merging nodes.
• Manual and AI-assisted coding techniques.
• Workshop: Coding a sample transcript.

• Module 4: Memos, Annotations and Data Interrogation

• Using memos to capture reflections and emerging ideas.
• Annotating text and linking related content.
• Text search, word frequency, matrix coding and Boolean queries.
• Workshop: Running queries on coded data.

• Module 5: Visualization, Reporting and Capstone Practical

• Creating charts, models and hierarchy charts.
• Exporting codebooks, summaries and reports.
• Team-based project: Coding and analyzing a simulated qualitative dataset.
• Performance review, feedback and course wrap-up.