Research design is the structure and logic of a study, while research methods are the procedures used to generate and analyze evidence within that structure. Understanding the distinction helps you explain not only what you did, but why those procedures can answer your research question.
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Methods are the procedures you use to conduct research; methodology concerns the reasoning, principles, and assumptions that inform how those procedures are selected and used. The distinction matters because rigorous research requires more than reporting what you did.
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Exploratory, descriptive, explanatory, and evaluative are often called research designs, but they more precisely describe what a study is trying to accomplish. The distinction matters because a research purpose does not by itself specify how the study will generate credible evidence.
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Name your research design specifically enough to communicate the structural features that matter, but do not turn the label into a catalogue of every methodological decision. A concise established term plus clear methodological detail is usually more informative.
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A study needs a defensible design, but that does not mean every study must fit one neat design label. Name the design when an established term improves clarity or reporting standards require it, while prioritizing an accurate description of what was actually done.
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Case study research investigates a clearly bounded case in depth and in relation to its real-world context. Studying one person, classroom, institution, event, or site does not automatically make a project a case study because the design depends on how the case is defined and investigated.
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Phenomenology, ethnography, grounded theory, and narrative research are not interchangeable labels for interview-based qualitative studies. Each organizes the inquiry around a different purpose, from understanding lived experience to culture, explanatory processes, or stories.
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Mixed methods research requires more than collecting qualitative and quantitative data in the same project. The defining issue is whether the components are deliberately related and integrated to produce an understanding that neither component would provide independently.
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Sequential mixed methods places one component before another when the later component needs something from the earlier findings. Concurrent approaches collect qualitative and quantitative evidence during roughly the same phase when neither component must wait for the other.
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Adding research sites can broaden settings, increase recruitment, and reveal contextual variation, but more sites do not automatically make a study stronger or more generalizable. The benefit depends on what additional settings contribute to the research question.
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The same broad research topic can often be studied cross-sectionally or longitudinally, but the two designs do not answer exactly the same question. Changing the temporal structure changes what evidence is available and therefore what conclusions the study can support.
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The strongest research design is not necessarily the most complex one. Choose the simplest design that can answer the research question credibly, and add complexity only when it produces information or protection against bias that matters to the intended inference.
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Correlation, association, prediction, and causation answer different research questions. Learn how to match the claim you want to make with the evidence your study is actually designed to provide.
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Between-subjects designs compare different participants across conditions, while within-subjects designs compare conditions within the same participants. The better choice depends on what is being studied and whether experiencing one condition can influence another.
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A baseline is a reference point established before the change, intervention, or follow-up of interest. It can be essential for some questions, useful for others, and unnecessary when the study does not depend on measuring a starting condition.
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Single-, double-, and triple-blind are familiar research labels, but they do not consistently identify who was actually blinded. Clear reporting should specify exactly who knew the study assignments and who did not.
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A proposed cause must occur before its effect, but showing that one variable came first does not prove causation. Temporal order is necessary for many causal claims, yet it is only one part of causal identification.
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Observational data do not automatically restrict researchers to non-causal questions. Causal inference may be possible when the causal contrast, design, assumptions, timing, confounding strategy, and analysis are explicitly aligned.
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A statistically convincing association is not automatically a causal effect. Learn how to recognize when your design supports a relationship between variables but cannot credibly establish what would happen if one were changed.
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Stakeholder engagement brings people who are affected by, interested in, or able to use research into parts of the research process. Their involvement can range from consultation to sustained partnership, depending on the study and its purpose.
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Research participants primarily take part in a study and contribute data, while research partners help shape or conduct aspects of the research itself. A person can sometimes occupy both roles, but the distinction matters for consent, responsibilities, influence, and reporting.
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Participatory research changes who contributes to producing knowledge and how influence is distributed across the research process. It does not abandon research rigor or require every decision to be made collectively.
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Stakeholders can contribute from the earliest development of a research topic through study design, conduct, interpretation, dissemination, and use of findings. They do not need to participate in every stage for their involvement to be meaningful.
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Research partners should not receive or be denied authorship simply because they are partners. Authorship should reflect their actual scholarly contribution and the criteria required by the journal or applicable authorship standard.
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Primary and secondary data are not simply two ways of obtaining the same evidence. Whether you collect new data or work with existing data changes which parts of the study you can design yourself and which constraints you inherit.
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