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Abstract

This book review evaluates Johnny Saldaña’s The Coding Manual for Qualitative Researchers (5th ed., 2025) as a pragmatic guide to qualitative data coding across first- and second-cycle methods. The book aims to categorize “coding method profiles” (i.e., sources, descriptions, applications, examples, analytical discussions, notes, and memos) to enhance instructional use while encouraging iterative memo writing and methodological development with applications. Readers should pay particular attention to later chapters on second-cycle coding, including on (1) grounded-theory pathways (i.e., focused, axial, and theoretical pathway) and (2) cumulative approaches (i.e., pattern, elaborative, and longitudinal approaches). In addition, this book offers useful guidelines for translating codes and patterns into findings (i.e., the use of focusing strategies and code writing). This edition’s discussion of computer-assisted qualitative-data-analysis software (CAQDAS) and generative AI is especially contemporary, framing computational tools as supportive while underscoring that interpretation, contextual judgment, theoretical argument, and ethical accountability remain the researchers’ duties.

Keywords

coding, CAQDAS, generative AI, memo, qualitative data analysis

Author Bio(s)

Luis Miguel Dos Santos is an Associate Professor in the Department of Counseling and Psychology at Hong Kong Shue Yan University, Hong Kong. He is a top 2% scientific researcher in social sciences and education from 2021 to 2025, and a career-long scientific researcher in 2025. Please direct correspondence to luismigueldossantos@yahoo.com

Publication Date

6-27-2026

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License.

ORCID ID

0000-0002-4799-8838

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