Introducing Qualitative Data Analysis with Nvivo

Keep the route back to the data

Early coverage addresses qualitative computing, project beginnings, database design and coding, including cases, sources, memos, annotations and links. These components serve different purposes: collecting material, preserving interpretive reasoning and maintaining participant context.

A tidy project can still be analytically weak when those connections are absent. Read the organizational sections before the code list becomes too large, even if you already know several commands.

Practice one complete analytical cycle

Keep the research question visible while classifying material. Existing projects can be reviewed for distinctions among sources, cases and attributes, which may matter for later comparisons.

Exercise created by Lê Minh: code a theme across several illustrative excerpts, write a memo explaining the grouping and retain the original context. Then examine an excerpt that does not fit comfortably. Consider whether the theme’s definition should change. The exercise is for learning, not an empirical finding.

In a team, compare interpretive reasons before comparing code counts. Agreement is not automatically the sole quality criterion; assessment must fit the project’s methodological orientation.

Edition and related books

This is the 2013 second edition by Bazeley and Jackson, not Woolf and Silver’s Five-Level QDA book. The latter focuses on translating purposes into tools; this volume can accompany the organization and development of a data-rich project. Its interface examples need checking against current NVivo versions. The lasting goal is an analytical record that shows how interpretation developed from the material, rather than merely naming the software used.

Choose a companion reading

Continue with: Qualitative Analysis Using NVivo (First edition · English).

Source and edition