The Coding Manual for Qualitative Research: A Review
The Coding Manual for Qualitative Research (Saldana, 2013) is the second edition of Jonny Saldana's international bestseller, providing an in depth sequential guide to numerous qualitative coding approaches for novice and veteran qualitative researchers alike. The second edition differs from the first in that it provides more chapters, coding techniques and an additional glossary. The book is 301 pages long and contains six chapters, a glossary, references and computer assisted qualitative data analysis software (CAQDAS) profiles in the section on analyzing visual data (pp. 25 32) The six detailed chapters (1) "An Introduction to Codes and Coding," (2) "Writing Analytic Memos," (3) "First Cycle Coding," (4) "After First Cycle Coding," (5) "Second Cycle Coding Methods," and (6) "After Second Cycle Coding" elaborately describe how to begin a qualitative research project from start to finish. Chapters 1 2 introduce the reader to qualitative research defining the term "code," what it means to begin "coding," how to code data and how to write analytic memos on data to organize data sets. Chapter 3 outlines first cycle coding methods, detailing twenty five coding approaches. Chapter 4 discusses post coding transitions first cycle coding mapping and landscaping. Chapter 5 outlines six second cycle coding approaches, advanced ways to reorganize and reanalyze the data (if needed) Chapter 6 offers recommendations for post coding and pre writing. Additionally, each of the thirty one qualitative coding methods discussed (in Chapter 3 "First Cycle Coding Methods" and Chapter 5 "Second Cycle Coding Methods" follow the same organizational format, listing sources, descriptions, applications, examples and a detailed analysis section. The book's second edition (Saldana, 2013) takes the reader through the "ins and outs" of qualitative data analysis beginning with an illustrative depiction of the curious mind of the researcher (coding as a heuristic) to codifying and categorizing, recoding and recategorizing and ending with data analysis. Saldana cleverly weaves each chapter to clearly follow the preceding chapter allowing the reader to understand the patience, time, and consecutive revisions entailed by qualitative coding. After reading this text, I felt more assured of my own research and was able to understand, implement and follow my own action plan for coding my data. Most importantly, Saldana provides multiple sources for coding approaches, helping the reader to value the unique attributes of each coding scheme and find the best coding approach for their data. As a novice qualitative researcher, I found the book to be very resourceful and easy to navigate, since each coding approach was followed by examples from Saldana's students or his own research notes. I was able to use these personal examples to connect to my own intentions for my research project, selecting the coding approach best suited for aim of my research. Saldana's second edition is contemporary in its craft, including figures of current qualitative coding software (NVivo, Atlas.ti and Wordle) without neglecting more traditional qualitative coding (Manual Coding and coding approaches using Microsoft Word or Xcel spreadsheets) For example, the CAQDAS section in Chapter 1 helped me understand how to use qualitative coding software like NVivo, but also demonstrated how the same coding processes can be employed using manual coding with pen and paper. Similarly, I found the subsequent chapters surrounding first and second cycle coding approaches (Chapters 4 and 6) to be especially helpful. The figures of code mapping and landscaping presented various ways for researchers to summarize and or present their data findings (e.g. versus coding for code mapping and the use of Wordle for code landscaping) for pre writing ideas. I found myself turning to this text throughout the four years of my graduate studies as a reliable reference and, certainly, recommended it to colleagues.