Research Design
Choosing and justifying a research design — exploratory, descriptive, correlational, causal/experimental, case study, longitudinal and cross-sectional designs — and matching the design to your research questions.
All Research Design guides
5 articles
Case Study Research: Design, Types & Rigour (Yin vs Stake)
Single or multiple case? Holistic or embedded? What makes case study research rigorous — case selection, triangulation, replication logic — and how to defend generalisation in your viva.
Mixed Methods Research Designs: Types, Notation & When to Use Them
Explanatory sequential, exploratory sequential or convergent? The three core mixed-methods designs, the QUAN/qual notation, and how to justify mixing methods in your thesis.
Theoretical Framework vs Conceptual Framework: The Difference, With Examples
The theoretical framework is the established theory you stand on; the conceptual framework is the specific model you build for your study. Here's how they differ, how they connect, and how to construct both.
Types of Research Design: Which One Fits Your Study?
Exploratory, descriptive, correlational, experimental, case study, cross-sectional, longitudinal — what each design can and cannot claim, and a decision path for choosing yours.
Qualitative vs Quantitative vs Mixed Methods: Which Fits Your Study?
Your method should follow your question, not your comfort zone. A clear guide to choosing between qualitative, quantitative and mixed-methods designs.
Put it into practice
Free tools, templates and mentoring connected to research design.
Frequently asked
How do I choose a research design?+
Start from what your questions ask for: to explore meaning you need qualitative designs, to measure and test relationships you need quantitative designs, and to explain mechanism plus measure you may need mixed methods. Feasibility — access, time, sample — then narrows the choice.
What is the difference between cross-sectional and longitudinal design?+
Cross-sectional studies collect data once — a snapshot. Longitudinal studies follow the same subjects across multiple time points, which supports stronger claims about change and causal ordering but costs more time and attrition risk.
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