alterlab-ieu/alterlab-academic-skills/alterlab-qualitative-methods

What is your primary research interest?
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├── LIVED EXPERIENCE of individuals
│   ├── Focus on meaning-making and interpretation
│   │   └── Interpretative Phenomenological Analysis (IPA)
│   ├── Focus on the essence/structure of experience
│   │   └── Descriptive/Transcendental Phenomenology (Husserl/Moustakas)
│   └── Focus on life stories and identity construction
│       └── Narrative Inquiry
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├── SOCIAL PROCESSES and how they unfold
│   ├── Want to generate theory from data
│   │   └── Grounded Theory (Strauss & Corbin or Charmaz)
│   └── Want to describe a process in context
│       └── Case Study (Yin) or Ethnography
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├── CULTURAL PATTERNS in a group or setting
│   ├── Immersive fieldwork possible (months/years)
│   │   └── Ethnography
│   └── Bounded, focused investigation
│       └── Case Study (Yin)
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├── CONTENT/MEANING in texts or media
│   ├── Seeking patterns and themes across a dataset
│   │   └── Thematic Analysis (Braun & Clarke)
│   └── Systematic categorization of content
│       └── Content Analysis (qualitative or directed)
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└── A BOUNDED SYSTEM (program, event, organization)
    ├── Single case with depth
    │   └── Single Case Study
    ├── Multiple cases for comparison
    │   └── Multiple Case Study
    └── Evaluating a program or intervention
        └── Case Study with evaluation framework

Phase 1: Familiarization with the Data
│   Read and re-read transcripts
│   Note initial observations (not codes yet)
│   Immerse yourself in the data
│   Record preliminary thoughts in a research journal
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Phase 2: Systematic Coding
│   Generate initial codes across the entire dataset
│   Code inclusively (code everything potentially relevant)
│   Codes are semantic (surface meaning) or latent (underlying assumptions)
│   One extract can have multiple codes
│   Use line-by-line or segment-by-segment approach
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Phase 3: Generating Initial Themes
│   Collate codes into potential themes
│   Use visual methods: mind maps, affinity diagrams, tables
│   Themes are patterns of shared meaning organized around a central concept
│   Not every code becomes a theme — some are subthemes, some are discarded
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Phase 4: Reviewing Themes
│   Check themes against coded extracts (Level 1)
│   Check themes against entire dataset (Level 2)
│   Do themes tell a coherent story?
│   Are themes distinct or overlapping?
│   Refine: split, merge, or discard themes as needed
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Phase 5: Defining and Naming Themes
│   Write a detailed analysis of each theme
│   Identify the "essence" of each theme
│   Create concise, vivid theme names
│   Determine how themes relate to each other
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Phase 6: Writing Up
    Weave together analytic narrative and data extracts
    Go beyond description — interpret and contextualize
    Embed extracts as evidence, not illustration only
    Relate findings to literature and research question

OPEN CODING
│   Break data into discrete parts
│   Label phenomena (concepts)
│   Group concepts into categories
│   Identify properties and dimensions of categories
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│   Example:
│   Concept: "Time pressure"
│   Properties: Source (institutional, self-imposed), Intensity, Duration
│   Dimensions: Mild ←──────→ Severe
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AXIAL CODING
│   Reassemble data around categories
│   Use the paradigm model:
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│   Causal Conditions → Phenomenon → Context
│                                    → Intervening Conditions
│                                    → Action/Interaction Strategies
│                                    → Consequences
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│   Example:
│   Causal conditions: Publish-or-perish culture
│   Phenomenon: Research anxiety
│   Context: Early-career faculty, research university
│   Intervening conditions: Mentorship availability, institutional support
│   Strategies: Strategic collaboration, prioritization, avoidance
│   Consequences: Productivity variation, burnout, career trajectory
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SELECTIVE CODING
    Identify the core category
    Systematically relate all categories to the core
    Fill in categories that need further development
    Validate the emerging theory against data
    Write the storyline
 
    Example core category: "Surviving the Tenure Track"
    All other categories (research anxiety, teaching load, institutional
    politics, mentorship) relate to this central phenomenon

Initial data collection (purposive sampling)
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├── Analyze → Emerging categories
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├── Identify gaps in categories
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├── Sample specifically to develop/test categories
│   (Who to interview? What to observe? What documents to examine?)
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├── Analyze new data → Refine categories
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├── Repeat until THEORETICAL SATURATION
│   (No new properties, dimensions, or relationships emerge)
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└── Articulate substantive theory