Research Methodology

Critical Theory

• Belief: Research should challenge power structures
• Methods: Participatory action research
• Knowledge: Emancipatory
• Use when: Social justice research

QUANTITATIVE APPROACHES

Experimental Design

Key Elements:

• Independent variable (what you manipulate)
• Dependent variable (what you measure)
• Control group (baseline comparison)
• Random assignment (reduces bias)

Non-Experimental Designs

Sampling for Quantitative

Sample Size Guidelines:

• Experimental: Minimum 30 per group
• Survey: Minimum 100-300
• Complex analysis: 10-20 participants per variable
• Power analysis: Recommended

QUALITATIVE APPROACHES

Phenomenology

• Focus: Lived experiences
• Data: In-depth interviews
• Sample: 5-25 participants
• Question: "What is the experience of...?"

Grounded Theory

• Focus: Develop theory from data
• Data: Interviews, observations
• Process: Constant comparison
• Question: "What theory explains...?"

Ethnography

• Focus: Culture/context
• Data: Observations, interviews, documents
• Duration: Long-term immersion
• Question: "How do people in this culture...?"

Case Study

• Focus: In-depth single case
• Data: Multiple sources
• Scope: Bounded system
• Question: "How/why does this case...?"

Narrative Inquiry

• Focus: Life stories
• Data: Interviews, documents
• Analysis: Restorying
• Question: "How do people make sense of their lives?"

Sampling for Qualitative

Sample Size Guidelines:

• Phenomenology: 5-25
• Grounded theory: 20-30
• Ethnography: Long-term, not fixed
• Case study: 1 (embedded: multiple units)
• Saturation → Stop when no new themes emerge

MIXED METHODS DESIGNS

Convergent Parallel

QUANT Data ──┐
             ├──→ Integration → Results
QUAL Data ───┘

• Collect simultaneously
• Compare/merge results
• Purpose: Triangulation

Explanatory Sequential

QUANT Data → Results → QUAL Data → Integration

• Quant first, then explain with qual
• Purpose: Explain findings

Exploratory Sequential

QUAL Data → Results → QUANT Data → Integration

• Qual first, then test with quant
• Purpose: Develop instrument

Embedded Design

• One method supports the other
• Primary + secondary questions
• Purpose: Comprehensive understanding

JUSTIFYING YOUR CHOICE

Template for Justification

This study adopts a [quantitative/qualitative/mixed methods] approach because 
[reason aligned with research questions]. Specifically, a [specific design] 
was selected to [purpose].

This approach is appropriate because:
1. The research question asks [alignment with paradigm]
2. Previous studies [cite precedent]
3. Practical considerations [resources, access]
4. Theoretical framework [if applicable]

Example Justifications

Quantitative Example:

A quasi-experimental design with pre-test and post-test was selected to 
examine the effect of AI tutoring on mathematics achievement. This design 
is appropriate because: (a) random assignment was not possible due to 
existing class structures, (b) comparison groups allowed control for 
confounding variables, and (c) pre-test measures established baseline 
equivalence (Shadish et al., 2002).

Qualitative Example:

A phenomenological approach was chosen to explore teachers' lived experiences 
with AI integration in classrooms. This methodology aligns with the study's 
aim to understand subjective meanings rather than measure objective outcomes 
(Creswell & Poth, 2018). Purposive sampling ensured participants had direct 
experience with the phenomenon.

Mixed Methods Example:

An explanatory sequential design was employed. First, survey data quantified 
technology use patterns. Second, interviews explored reasons behind these 
patterns. This design allowed statistical generalization while preserving 
depth of understanding (Creswell & Plano Clark, 2018).

METHODOLOGY CHAPTER STRUCTURE

Standard Outline

1. Introduction
   - Restate research questions
   - Preview methodology approach

2. Research Paradigm (optional for undergrad)
   - Philosophical assumptions
   - Justification

3. Research Design
   - Type of design
   - Justification
   - Visual diagram

4. Participants/Sample
   - Population
   - Sampling strategy
   - Sample size + justification
   - Inclusion/exclusion criteria
   - Recruitment

5. Data Collection
   - Instruments/materials
   - Procedure
   - Timeline

6. Data Analysis
   - Approach (quant/qual/mixed)
   - Specific techniques
   - Software

7. Trustworthiness/Validity
   - Quant: Internal/external validity, reliability
   - Qual: Credibility, transferability, dependability
   - Mixed: Integration quality

8. Ethical Considerations
   - Consent
   - Confidentiality
   - Risk mitigation
   - Approval

9. Limitations
   - Acknowledge constraints
   - Explain mitigation

VALIDITY & RELIABILITY

Quantitative

Reliability Thresholds:

• α ≥ .70: Acceptable
• α ≥ .80: Good
• α ≥ .90: Excellent

Qualitative

COMMON JUSTIFICATION PHRASES

PROCESS FOR WRITING METHODOLOGY

1. State research questions clearly
2. Identify paradigm (positivist/interpretivist/etc.)
3. Select approach (quant/qual/mixed)
4. Choose specific design (experimental/phenomenological/etc.)
5. Justify choices with literature
6. Detail procedures (replicable)
7. Address validity/reliability
8. Discuss ethics
9. Acknowledge limitations

QUICK DECISION TREE

Do you want to measure/test/predict?
├─ YES → Quantitative
│   ├─ Can you manipulate variables?
│   │   ├─ YES → Experimental
│   │   └─ NO → Correlational/Survey
│   └─ Time dimension?
│       ├─ One time → Cross-sectional
│       └─ Multiple → Longitudinal
│
└─ NO → Qualitative
    ├─ Explore experiences?
    │   └─ Phenomenology
    ├─ Build theory?
    │   └─ Grounded Theory
    ├─ Study culture?
    │   └─ Ethnography
    └─ Deep dive into case?
        └─ Case Study