What is research design?
Research design is concerned with obtaining information to generate key insights and answer questions. The requirements below are used by research + DESIGN to develop a framework that can obtain appropriate and credible data.
- Real-life problem:
The real-life problem is not necessarily addressable and is rather a meta-level background to the research problem.
- Research problem:
The research problem is the primary reason behind the study and, more specifically, what is required to be better understood.
The research can be carried out to prove an idea, or if unknown, to explore a topic in order to develop a range of ideas.
- Research method:
Attitudinal (Qualitative) and/or statistical (Quantitative) data is used to address questions ranging from interpretative to functional.
- Unit of analysis:
The phenomenon being studied is reduced to a unit-of-analysis that can be formally measured and analysed.
- Research sample:
The research sample is representative of the individuals, communities, or users being addressed in the later design phases.
A long-term (Longitudinal) or short-term (Cross-sectional) timeframe is used to correspond with sample behaviour.
Data is gathered using existing and/or new instruments such as surveys, questionnaires, check-lists, Likert-scales, and photographs.
Access to communities and groups is often mediated through a gate-keeper who can make appropriate introductions.
A sample may comprise entirely of, or contain a selection of, key-informants who are individuals with specialist information.
Consideration of sample demographics and fieldworker capabilities can help obtain more in-depth or cleaner research data.
A pilot phase tests the research design and may motivate for refinements before formally implementing the fieldwork.
- Data collation:
Depending on the research method, data can be collated in real-time to ascertain and rectify sample selection bias.
- Data preparation:
Prior to analysis, fieldwork data is reviewed for errors, cleaned without affecting integrity, and collated into datasets.
- Data analysis:
Data is analysed with Qualitative Data Analysis (QDA) or descriptive statistics software to identify trends, anomalies, and insights.
- Reporting method:
Reports outline key findings, recommendations for subsequent design phases, and include datasets as appendices.