Qualitative Research Design Decisions

1. Evaluate the Implications of Qualitative Research Design Decisions

1.1. Designing Qualitative Research

Every successful piece of research begins with a strong foundation. In qualitative research, that foundation is your research design - a flexible but purposeful "blueprint" that guides your project.

Key Benefits:

Saves time
Ensures respect for participants
Produces meaningful findings
Keeps questions, theories, and methods in conversation

1.2. How Design Shapes Knowledge

Design choices in qualitative research are never neutral - they shape:
- What you discover
- How others understand your findings
- The very knowledge you create

Reflective Question: Why is your research important right now? What will it add to knowledge, practice, or society?

2. Philosophical Assumptions and Reflexivity

2.1. Philosophical Assumptions

Behind every research project lie deeper ideas about the world and how we come to know it. These assumptions shape every aspect of qualitative research.

2.2. Ontology - Ideas about the Nature of Reality

Key Questions:

Is reality fixed and discoverable?
Does it depend on human perspective and interpretation?

Ontological Positions:

Realism: Reality exists independently of human understanding
Relativism: Reality is shaped by human understanding and context

2.3. Epistemology - How We Can Know and Understand the World

Epistemological Perspectives:

Quantitative traditions: Positivist/post-positivist - emphasize objective observation to uncover truths
Qualitative traditions: Constructionist - highlight how knowledge is created through interpretation, context, and meaning-making

2.4. Reflexivity in Qualitative Research

The researcher is not a detached observer - who you are shapes how you do research.

Why Reflexivity Matters:

Recognizes researcher influence
Strengthens research process and findings
Creates more thoughtful, transparent, and trustworthy research

Reflexive Strategies:

Journaling
Regular self-reflection
Acknowledging background, assumptions, and choices

Qualitative Data Collection Strategies

2.5. Introduction to Qualitative Data Collection

Qualitative data is rich, detailed, and often consists of words, images, or observations.

Key Principle: Choose approaches that fit your questions, participants, and context.

2.6. Semi-Structured Interviews

Balance between guidance and flexibility
Like guided conversations
Produce deep, detailed insights
Work well face-to-face or online

2.7. Types of Interviews

Type	Description	Commonly Used In	Strengths	Limitations
Structured	Questions fully predetermined	Quantitative research	- Easy to replicate - Standardized data - Easy comparison	- Limited depth - No unexpected issues
Semi-Structured	Key questions with flexibility	Qualitative research (most common)	- Balance consistency/flexibility - Explores unanticipated themes - Accessible	- Requires skill to follow up - Less standardized
Unstructured	Broad themes, participant-led	Some qualitative research	- Rich, in-depth accounts - Participant perspectives - Empowers participants	- Time-consuming - Difficult to analyze systematically

2.8. Focus Groups

Use social interaction to generate data
Powerful for exploring collective views or social meanings
Not ideal for highly personal or sensitive topics

2.9. Textual Data Collection

Sources:

Participant-generated surveys
Media articles
Online forums
Political speeches

Limitations:

No chance to probe further
Less researcher control

3. Qualitative Analytic Approaches

3.1. Introduction to Qualitative Analysis

Process of making sense of gathered data by identifying patterns, themes, and insights.

Aims of Qualitative Analysis:

Explore meaning
Recognize patterns in language
Pay attention to context
Value participants' perspectives

3.2. Content Analysis

Simple, flexible method
Describes and organizes data systematically
Good for large datasets or comparing patterns
Focuses on surface-level content and frequency
Aligns more with quantitative traditions

3.3. Thematic Analysis (TA)

Most widely used approach
Flexible, practical, and accessible
Identifies and reports themes across data
Requires careful use to go beyond description

3.4. Interpretative Phenomenological Analysis (IPA)

Explores individual experiences in depth
Focuses on lived experience
Requires small samples
Demands careful interpretative work

3.5. Grounded Theory (GT)

Builds theory directly from data
Useful for studying processes and social influences
Iterative, systematic process
Time-consuming and complex
Involves constant comparison and memo-writing

4. Planning a Qualitative Research Project

4.1. Project Planning Framework

Start with your research question
Choose an analysis approach
Decide how to collect your data
Identify your sample
Be realistic and practical
Keep everything aligned

4.2. Case Study: First-Year Student Success Project

Research Question: "How do first-year students experience and understand success?"

Breaking Down the Question:

"How do first-year students..." → Specific group: first-year university students
"...experience and understand success?" → Personal experiences + interpretations

4.3. Reflective Questions for Research Design

What kind of knowledge is this project trying to produce?
Rich description of experiences
Testing a hypothesis
Generating a theory
What are the practical constraints of this project?
Time available
Researcher experience
Access to participants
Which type of data collection would be most appropriate, and why?
Which type of qualitative analysis would be most appropriate, and why?

5. Key Takeaways

Research design is your project's blueprint - flexible but purposeful
Philosophical assumptions shape every aspect of your research
Reflexivity strengthens research by acknowledging researcher influence
Choose data collection methods that fit your questions and context
Select analysis approaches based on the knowledge you want to produce
Maintain alignment between questions, methods, and analysis
Consider practical constraints when planning your project