Master Summary QUAL-RM
🧩 What is Qualitative Research?
● Explores how people make sense of experiences.
● Focuses on meaning, context, and participant perspectives.
● Features:
○ Researcher as instrument.
○ Inductive, flexible design.
○ Rich, thick descriptions.
🔨 Research Designs
● Case Study → in-depth, bounded system, real-world context.
● Ethnography → immersion, participant observation, uncovering cultural meaning.
● Grounded Theory → theory built from data through systematic coding.
● Design Principles → flexible, iterative, purposeful sampling.
🎤 Data Collection
● Observation → participant/nonparticipant, routines, interactions.
● Interviews → informal, semi-structured, standardized.
● Key practices → active listening, probing, rapport, ethical reflexivity.
🛠 Data Analysis
● Iterative cycle → immerse, open code, focus code, axial link, theorize.
● Techniques → memos, constant comparison, visual displays, software.
● Goal → develop credible, meaningful themes and insights.
✅ Ensuring Validity
● Core criteria → credibility, authenticity, criticality, integrity.
● Strategies → triangulation, member checks, audit trail, reflexivity.
● Verification tactics → pattern checks, contrasts, negative cases, informant feedback.
📝 Reporting and Ethics
● Reporting → Balance vivid data with theoretical insight; write clearly and coherently.
● Interviewing elites → Manage access, power, and openness with care and reflexivity.
● Ethics → Protect your role, your data, and your participants, especially when power
dynamics are uneven.
💡 Qualitative research = messy but systematic:
It requires careful design, deep engagement with data, and constant reflexivity to create rigorous,
trustworthy insights about complex social phenomena.
, 1. What and Why Qualitative Research?
Merriam (2009) — What Is Qualitative Research?
● Purpose: Understand how people interpret experiences, construct meaning, and make sense
of their world → “Not everything that can be counted counts, and not everything that counts
can be counted” – Albert Einstein
● Core features:
○ Researcher = main instrument.
○ Inductive, flexible design → no rigid plan; you adapt as you learn.
○ Focus on process, meaning, context, not just outcomes.
○ Rich, thick descriptions → deep details, vivid quotes, “thick” context.
● Philosophical roots:
○ Positivist → believes in objective truths, measurable, generalizable.
○ Interpretive → multiple, subjective realities; context matters
○ Critical → focuses on power, inequality.
○ Postmodern → challenges the idea of a single truth; embraces diversity.
Interpretivist (qualitative) Positivist (quantitative)
● Reality is socially constructed; ● Real world data collection;
● data is expressed in language; ● numbers;
● subjective; ● objective;
● linked to context (not generalisable); ● generalizable;
● flexible, evolving, emerging; ● seeking evidence of frequency.
● seeking evidence of meaning.
How to arrive at knowledge?
● Quantitative/Deductive: Observation > pattern > tentative hypothesis > theory
● Qualitative/Inductive: Theory > hypothesis > observation > confirmation
What do we do as qualitative researchers?
1. Interpretivist approach: We interpret an already interpreted world
2. Qualitative data: We observe and question the world to find evidence of meaning
3. Inductive logic: We build understanding from our interpretations of this evidence
✔ Best to remember: Qualitative research is about exploring meaning, not measuring facts.
🧩 What is Qualitative Research?
● Explores how people make sense of experiences.
● Focuses on meaning, context, and participant perspectives.
● Features:
○ Researcher as instrument.
○ Inductive, flexible design.
○ Rich, thick descriptions.
🔨 Research Designs
● Case Study → in-depth, bounded system, real-world context.
● Ethnography → immersion, participant observation, uncovering cultural meaning.
● Grounded Theory → theory built from data through systematic coding.
● Design Principles → flexible, iterative, purposeful sampling.
🎤 Data Collection
● Observation → participant/nonparticipant, routines, interactions.
● Interviews → informal, semi-structured, standardized.
● Key practices → active listening, probing, rapport, ethical reflexivity.
🛠 Data Analysis
● Iterative cycle → immerse, open code, focus code, axial link, theorize.
● Techniques → memos, constant comparison, visual displays, software.
● Goal → develop credible, meaningful themes and insights.
✅ Ensuring Validity
● Core criteria → credibility, authenticity, criticality, integrity.
● Strategies → triangulation, member checks, audit trail, reflexivity.
● Verification tactics → pattern checks, contrasts, negative cases, informant feedback.
📝 Reporting and Ethics
● Reporting → Balance vivid data with theoretical insight; write clearly and coherently.
● Interviewing elites → Manage access, power, and openness with care and reflexivity.
● Ethics → Protect your role, your data, and your participants, especially when power
dynamics are uneven.
💡 Qualitative research = messy but systematic:
It requires careful design, deep engagement with data, and constant reflexivity to create rigorous,
trustworthy insights about complex social phenomena.
, 1. What and Why Qualitative Research?
Merriam (2009) — What Is Qualitative Research?
● Purpose: Understand how people interpret experiences, construct meaning, and make sense
of their world → “Not everything that can be counted counts, and not everything that counts
can be counted” – Albert Einstein
● Core features:
○ Researcher = main instrument.
○ Inductive, flexible design → no rigid plan; you adapt as you learn.
○ Focus on process, meaning, context, not just outcomes.
○ Rich, thick descriptions → deep details, vivid quotes, “thick” context.
● Philosophical roots:
○ Positivist → believes in objective truths, measurable, generalizable.
○ Interpretive → multiple, subjective realities; context matters
○ Critical → focuses on power, inequality.
○ Postmodern → challenges the idea of a single truth; embraces diversity.
Interpretivist (qualitative) Positivist (quantitative)
● Reality is socially constructed; ● Real world data collection;
● data is expressed in language; ● numbers;
● subjective; ● objective;
● linked to context (not generalisable); ● generalizable;
● flexible, evolving, emerging; ● seeking evidence of frequency.
● seeking evidence of meaning.
How to arrive at knowledge?
● Quantitative/Deductive: Observation > pattern > tentative hypothesis > theory
● Qualitative/Inductive: Theory > hypothesis > observation > confirmation
What do we do as qualitative researchers?
1. Interpretivist approach: We interpret an already interpreted world
2. Qualitative data: We observe and question the world to find evidence of meaning
3. Inductive logic: We build understanding from our interpretations of this evidence
✔ Best to remember: Qualitative research is about exploring meaning, not measuring facts.
