Research

Insights from data

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.

  1. Real-life problem:
    The real-life problem is not necessarily addressable and is rather a meta-level background to the research problem.
  2. Research problem:
    The research problem is the primary reason behind the study and, more specifically, what is required to be better understood.
  3. Methodology:
    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.
  4. Research method:
    Attitudinal (Qualitative) and/or statistical (Quantitative) data is used to address questions ranging from interpretative to functional.
  5. Unit of analysis:
    The phenomenon being studied is reduced to a unit-of-analysis that can be formally measured and analysed.
  6. Research sample:
    The research sample is representative of the individuals, communities, or users being addressed in the later design phases.
  7. Timescales:
    A long-term (Longitudinal) or short-term (Cross-sectional) timeframe is used to correspond with sample behaviour.
  8. Instruments:
    Data is gathered using existing and/or new instruments such as surveys, questionnaires, check-lists, Likert-scales, and photographs.
  9. Gate-keepers:
    Access to communities and groups is often mediated through a gate-keeper who can make appropriate introductions.
  10. Key-informants:
    A sample may comprise entirely of, or contain a selection of, key-informants who are individuals with specialist information.
  11. Fieldworker:
    Consideration of sample demographics and fieldworker capabilities can help obtain more in-depth or cleaner research data.
  12. Piloting:
    A pilot phase tests the research design and may motivate for refinements before formally implementing the fieldwork.
  13. Data collation:
    Depending on the research method, data can be collated in real-time to ascertain and rectify sample selection bias.
  14. Data preparation:
    Prior to analysis, fieldwork data is reviewed for errors, cleaned without affecting integrity, and collated into datasets.
  15. Data analysis:
    Data is analysed with Qualitative Data Analysis (QDA) or descriptive statistics software to identify trends, anomalies, and insights.
  16. Reporting method:
    Reports outline key findings, recommendations for subsequent design phases, and include datasets as appendices.
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