Research designs organise how evidence will be collected and interpreted. Choose a design because it fits the question, not because its name sounds more rigorous. A useful methodology explains the purpose, data, procedures and limits of the proposed approach.
Distinguish data approaches from designs
Quantitative work uses numerical data and analysis, while qualitative work examines meaning, experience or context through suitable non-numerical material. Mixed-methods work combines approaches with an explained purpose. These labels do not identify a complete design on their own. State what you will examine, how the material will be obtained and how it will answer the question.
Experiments and quasi-experiments
An experiment studies a change under a planned comparison. Random allocation is relevant to some experimental designs but should not be confused with random sampling. A quasi-experimental design investigates an intervention without the same allocation control. Explain possible alternative causes of an observed difference and why the comparison is informative despite its limits.
Observational, correlational and cohort designs
Observational research examines what occurs without assigning the intervention of interest. Correlational analysis examines relationships between variables but does not alone establish causation. A cohort study follows a defined group over time or uses existing records of that group. Specify how participants, timing and measurements fit the question rather than treating all observational work as identical.
Select a feasible and ethical method
Consider access, consent, resources, data quality and the time available. A theoretically attractive design may not be feasible for a student project. Identify what your study can establish and which claims would require a different design. Obtain the approval required by your institution before collecting data; a general guide is not an approval to research people.
Write the methodology as a justified plan
Connect the research question, participant or material selection, collection procedures and analysis. Explain why alternatives were not chosen and how limitations will be handled. Keep tense and scope consistent with whether the assignment proposes a study or reports completed work. Do not claim that using a named method removes every source of bias.
Related study guides
- Experimental Variables and Repeatability: Explain the Design
- Primary Evidence: Meaning, Examples and Source Evaluation
- Qualitative Data Analysis: Methods, Coding and Transparent Interpretation
For general study guidance, visit the knowledgebase. Follow your own course requirements when applying this article to assessed work.