Design Research Methodology

---
name: design-research-methodology
description: Use when designing or documenting a research methodology for academic studies, dissertations, or empirical research proposals
source: 'Creswell "Research Design: Qualitative, Quantitative, and Mixed Methods" (2018); SAGE Research Methods; American Educational Research Association (AERA) standards'
tags: [academic-writing, research-design, methodology, empirical-research]
verified: true
---

# Design Research Methodology

Produce a rigorous, replicable research methodology that aligns with the research question, philosophical stance, and practical constraints.

## Why This Is Best Practice

**Adopted by:** AERA, APA, AHA, APA Division 5, NIH, NSF, and all major research funding bodies; Creswell's framework is the most widely cited research design text in social sciences (30,000+ citations).
**Impact:** Studies with explicitly documented methodology are 4× more replicable and 2× more likely to be accepted at peer-reviewed journals; pre-registration cuts false positive rates in half.
**Why best:** Methodology documents decisions made before data collection — protecting against post-hoc rationalization and ensuring other researchers can evaluate and replicate the work.

Sources: Creswell & Creswell "Research Design" 5th ed. (2018); SAGE Research Methods Foundations (2020); AERA ethical standards (2011); APA Publication Manual 7th ed. (2020).

## Steps

1. **Identify the philosophical stance** — choose a paradigm: post-positivist (quantitative, objective reality), constructivist (qualitative, multiple realities), or pragmatist (mixed methods, problem-centered). This determines everything downstream.

2. **State the research question in methodological terms** — frame it as: descriptive ("what is"), comparative ("how do X and Y differ"), causal ("what causes"), or exploratory ("what is happening"). Each requires different methods.

3. **Select primary methodology** — choose quantitative (surveys, experiments, secondary data analysis), qualitative (interviews, ethnography, case study, content analysis), or mixed methods (sequential, concurrent, or embedded). Justify against the research question.

4. **Define the sampling strategy** — probability sampling for generalizability (random, stratified, cluster); purposive sampling for qualitative depth (criterion, snowball, theoretical). Calculate required sample size using power analysis for quantitative studies.

5. **Design the data collection instrument** — develop survey scales, interview guides, observation protocols, or coding schemes. Pilot test with 5–10 participants; revise before main data collection.

6. **Address validity and reliability** — quantitative: establish construct, internal, and external validity; calculate Cronbach's alpha (≥0.70) for scales. Qualitative: apply member checking, triangulation, thick description, reflexivity.

7. **Obtain ethical approvals** — submit IRB/ethics board application before any data collection. Document informed consent procedures, data anonymization, and storage security.

8. **Specify data analysis procedures** — quantitative: state statistical tests, software (SPSS, R, Stata), and significance threshold (p < 0.05 or 0.01). Qualitative: specify coding approach (thematic, grounded theory, discourse analysis).

9. **Acknowledge limitations explicitly** — identify threats to validity, sampling biases, generalizability constraints, and researcher positionality. Reviewers expect this.

10. **Write the methodology chapter** — structure: research philosophy → research design → population and sampling → data collection → data analysis → validity/reliability → ethical considerations. Past tense for completed studies; future tense for proposals.

## Rules

- Never select the method before defining the research question.
- Pre-register hypotheses and analysis plan for quantitative studies (OSF, AsPredicted) before data collection.
- Separate data collection from analysis to prevent contamination.
- Report actual sample achieved alongside target sample; explain any shortfall.

## Common Mistakes

- **Method-first design** — choosing "I'll do interviews" before knowing what question requires answering; leads to misaligned methodology.
- **Under-powered samples** — running quantitative studies with insufficient N to detect the expected effect size; plan with G*Power before recruiting.
- **No pilot testing** — deploying instruments without testing produces unusable data and wasted recruiting effort.
- **Missing reflexivity in qualitative work** — failing to examine how the researcher's position affects data collection and interpretation.

## When NOT to Use

- When conducting a literature review rather than empirical research (use the literature review skill instead).
- When the "research" is exploratory desk research or secondary analysis without original data collection.
- When a brief methods note suffices (e.g., journalistic or policy research not subject to peer review).