There is no universally best research method. A suitable approach is one that can address the research question with evidence you can responsibly access and analyse. Your discipline, project brief, supervisor, and ethics requirements set important boundaries.
1. Clarify what the question asks
Identify whether you want to describe a pattern, compare groups, understand an experience, examine a process, interpret a text, or explore how ideas relate. These are different aims and call for different evidence. If the question contains several aims, consider whether they can be answered in one project with your available time and resources.
2. Name the evidence you need
Ask what information would let you answer the question. It might be numerical measurements, words or observations, documents, existing datasets, or a combination. The evidence should connect directly to the concepts in your question. Do not choose a method just because it is familiar or appears in another dissertation.
3. Understand broad approach options
Quantitative approaches examine numerical data and can be useful for measuring patterns or relationships when the measures and design fit the question. Qualitative approaches examine meaning, experience, interaction, or context through sources such as interviews, observations, or texts. Mixed-methods projects combine approaches when the question genuinely needs complementary forms of evidence and the project can support both. These labels are broad; the exact design and analysis must be explained.
4. Check access and feasibility
List what you would need: participants, permission, a dataset, equipment, software, language skills, or time for transcription and analysis. Confirm whether access is realistic before finalizing the design. Consider the project’s scale, your skills, the sample or corpus, and what you can complete within the programme timeline. A narrower question with accessible evidence is often more workable than an ambitious question with no feasible data source.
5. Check ethics and data handling early
If people, personal data, sensitive records, or restricted materials are involved, check your institution’s ethics and approval process before collection or use. Do not assume that anonymizing a file later makes an unapproved project acceptable. Keep confidential data out of ordinary enquiry messages and use only approved storage and handling procedures.
6. Plan the analysis before collecting evidence
Describe how you would move from evidence to an answer. For example, will you compare measurements, code interview material, analyse documents, or interpret a case? The analysis should match both the evidence and the question. If you cannot yet explain how the results would answer the question, refine the design before gathering data.
7. State limitations honestly
Every design has limits. Note the boundaries of the sample, measures, materials, access, or interpretation. Explain what the findings could support and what they cannot establish. Do not overstate causation, representativeness, or generalizability beyond what the design permits.
Method-fit checklist
- The method addresses the question rather than merely sounding sophisticated.
- The needed evidence is available and permitted.
- The project can be completed with the time and resources available.
- Ethics and data requirements are understood.
- The analysis plan connects evidence to the intended answer.
- Important limits are explicit.
Discuss your proposed design with your supervisor and follow your institution’s research guidance. You can also use the dissertation planning guide and Study Resources.