A Step-by-Step Guide to Qualitative Data Coding is a comprehensive qualitative data analysis guide. It is designed to help readers to systematically analyze qualitative data in a transparent and consistent manner, thus promoting the credibility of their findings.

The book examines the art of coding data, categorizing codes, and synthesizing categories and themes. Using real data for demonstrations, it provides step-by-step instructions and illustrations for analyzing qualitative data. Some of the demonstrations include conducting manual coding using Microsoft Word and how to use qualitative data analysis software such as Dedoose, NVivo and QDA Miner Lite to analyze data. It also contains creative ways of presenting qualitative findings and provides practical examples. After reading this book, readers will be able to:

Analyze qualitative data and present their findings
Select an appropriate qualitative analysis tool
Decide on the right qualitative coding and categorization strategies for their analysis
Develop relationships among categories/themes
Choose a suitable format for the presentation of the findings

Ideal for qualitative research instructors, students, and social or health science professionals, this guide helps you combine proven methods with emerging AI capabilities.

New to this edition:

Full-color illustrations for greater clarity and engagement
Additional visualizations to help you learn and apply coding techniques
A new chapter on AI-assisted analysis, covering:

Ethical and effective AI use
Prompting strategies for better outputs
How to create your own AI tool for data analysis

About the Author

Dr. Philip Adu is the founder and methodology expert at the Center for Research Methods Consulting, LLC. He has provided research methodology services to clients for over ten years and has facilitated hundreds of workshops with graduate students, program evaluators, faculty members, and practitioners. He has expertise in using qualitative data analysis software (QDAS) and AI tools to conduct qualitative analyses.

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