Codebook Generator
A comprehensive qualitative research codebook generator designed to help researchers create structured, hierarchical coding schemes for qualitative data analysis. Build professional codebooks with thematic categories, multiple code types (descriptive, interpretive, pattern, structural, process, in-vivo), parent-child code relationships, detailed definitions, usage guidelines, and data examples with source citations. Perfect for grounded theory, thematic analysis, content analysis, and any qualitative research methodology requiring systematic coding.
Key Features
- Comprehensive project information tracking
- Researcher names and methodology documentation
- Data source specification
- Version control for codebook iterations
- Thematic category creation and management
- Color-coded theme organization
- Theme descriptions and definitions
- 6 code types: descriptive, interpretive, pattern, structural, process, in-vivo
- Hierarchical parent-child code relationships
- Detailed code definitions
- When to use/when not to use guidelines
- Multiple example quotes per code
- Source citation tracking for examples
- Code notes for theoretical connections
- Search and filter by theme
- Filter by code type
- Code statistics and summaries
- Theme-based code grouping
- Parent and child code counts
- Example tracking per code
- Professional preview formatting
- Hierarchical display of codes and sub-codes
- Export to formatted text for documentation
- Export to JSON for collaboration
- Import from JSON
- Browser localStorage persistence
- No login required
- Sub-code management and visualization
- Code type icons and descriptions
- Interactive code detail view
- Example management with add/delete
- Theme-color visualization
- Comprehensive codebook statistics
- Unassigned code tracking
- Print-friendly output format
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Frequently Asked Questions
What are the different types of codes in qualitative research?
Qualitative codes fall into four main types: (1) Descriptive codes - summarize what data is about (e.g., "family conflict"), (2) Interpretive codes - capture meaning or significance (e.g., "coping strategy"), (3) Pattern codes - identify recurring themes across data (e.g., "resilience despite adversity"), (4) In-vivo codes - use participants' exact words (e.g., "walking on eggshells"). This tool helps organize all four types hierarchically with parent-child relationships for comprehensive analysis.
Should I create my codebook before or during data analysis?
It depends on your approach. Deductive coding starts with a preliminary codebook based on theory/literature before analysis begins. Inductive coding develops codes from data during analysis through open coding. Most researchers use a hybrid approach: start with a few theory-based codes, then add emergent codes during analysis. This tool supports both approaches - begin with template codes or build entirely from your data.
How detailed should code definitions be in my codebook?
Code definitions should include: (1) clear name, (2) brief definition (1-2 sentences), (3) inclusion criteria (what belongs in this code), (4) exclusion criteria (what doesn't belong), (5) typical examples from your data, (6) atypical examples showing boundaries. Good definitions enable consistent coding across data and allow multiple coders to achieve high inter-rater reliability. This tool structures all these elements for each code.
Can I export my codebook to use in NVivo or ATLAS.ti?
Yes, this tool exports codebooks in multiple formats including structured text and JSON. While it doesn't export directly to proprietary QDA software formats, you can use the exported text to manually create codes in NVivo, ATLAS.ti, MAXQDA, or Dedoose. The hierarchical structure, definitions, and examples transfer easily. Many researchers use this tool for initial codebook development, then import the structure into their QDA software.