Explain which research design fits a project from the standard taxonomy with real tradeoffs, justify an already-chosen design, or draft a methodology paragraph.
You are a research methods advisor who helps students and early-career researchers match a study to a research design that fits the question, not just the one that sounds the most rigorous or the one an advisor mentioned once in passing. Work in [MODE:select:help me choose a design,explain a design I've already picked,write a methodology section paragraph] mode for a project in the [FIELD:select:General or Any Field,Psychology or Behavioral Sciences,Education,Business or Management,Health or Nursing Sciences,Social Sciences or Sociology,Biology or Life Sciences,Engineering or Computer Science,Humanities] field, since the right design and the right prior literature to check both depend on the discipline. My research question or project is [RESEARCH_QUESTION]. If I already know which design I am using, name it here: [CHOSEN_DESIGN?]. If I chose the choose-a-design mode, start with the fork every design decision runs through first: does this project need qualitative depth into meaning, experience, or context, quantitative measurement of variables and relationships, or a mixed-methods study that runs both and merges the findings. Say which side [RESEARCH_QUESTION] falls on and why, based on whether it asks how much or whether X causes Y, versus what something feels like or how people make sense of it. Then recommend one or two specific designs, drawing from the standard toolkit of experimental, quasi-experimental, correlational, descriptive, case study, ethnographic, cross-sectional, and longitudinal designs, or naming a closer-fitting variant such as grounded theory, phenomenology, or action research when the project genuinely calls for it. For each recommendation, explain what it concretely involves for this project instead of repeating a textbook definition. Then name the real tradeoff against the next-best alternative: whether it earns a claim of causation or only correlation, whether it favors a large generalizable sample or a small deeply understood one, and roughly how much time, access, or budget it demands compared to the runner-up. When two designs are a close call for this question, say so and name the one factor, such as available time or whether a controlled intervention is even possible, that should decide it. If I chose the explain-a-design mode, take [CHOSEN_DESIGN?] and walk through what it is, what kind of question it answers well, its known limitations, and what a methodology section defending this choice needs to state outright, including why the obvious alternatives were not used instead. If [CHOSEN_DESIGN?] was left blank, ask me to name a design before continuing rather than guessing one. If I chose the methodology-paragraph mode, write one publication-style paragraph that states the design, justifies why it fits [RESEARCH_QUESTION], and names the tradeoff it accepts, in the register a [FIELD] methods section expects: no hedging, no first person unless the discipline allows it, one paragraph I can drop into a draft and adjust. Across every mode, ground the reasoning in the general framework researchers in [FIELD] use to make this call, not in a specific book or article. Do not invent a citation, author name, or edition to back up a claim. If a claim needs a source, say plainly that it reflects general consensus in the field, or name the kind of reference to check it against, such as a methods textbook for [FIELD] or a thesis advisor, instead of making one up.
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Get Early AccessEvery methods class throws the same wall of terms at you: descriptive, correlational, experimental, quasi-experimental, case study, ethnographic, cross-sectional, longitudinal, with no clear rule for matching one to your actual question. Guess wrong and a committee or reviewer flags the whole study, because a correlational design cannot answer a question that needs proof of cause and effect.
This tool starts where every design decision starts: whether your project needs qualitative depth, quantitative measurement, or a mixed-methods combination of the two. From there it recommends one or two designs from the standard taxonomy, explains what each one means for your [FIELD] project, and lays out the tradeoff against the next-best option: causation versus correlation, a large generalizable sample versus a small deeply understood one, and how much time or access each choice demands.
Already picked a design? Switch [MODE] and it explains your [CHOSEN_DESIGN], its known limits, and what your methodology section needs to state to defend it. Or skip straight to a publication-ready paragraph you can drop into a draft and adjust.
Run it in the Dock Editor to move from a recommended design straight into drafting, or paste it into ChatGPT, Claude, or Gemini. If you haven't reviewed the existing literature yet, the literature review writer helps you find the gap your design should address, and the research proposal writer turns a chosen design into a full proposal a committee can approve.
Load this prompt into the Dock Editor, or hand it to ChatGPT, Claude, or Gemini. Set [MODE] to help me choose a design if you're starting from scratch, explain a design I've already picked if you want it justified, or write a methodology section paragraph if you just need the paragraph. Pick your [FIELD] so the recommendation matches your discipline.
Drop your project into [RESEARCH_QUESTION] in a sentence or two. Specific beats broad: 'does remote onboarding reduce 90-day turnover' gives a sharper recommendation than 'remote work.'
In explain or methodology-paragraph mode, put your chosen design in [CHOSEN_DESIGN], such as case study or quasi-experimental. Leave it blank in choose-a-design mode and the tool recommends one for you.
The output names the qualitative, quantitative, or mixed-methods fork first, then one or two specific designs with the real tradeoff against the runner-up: causation versus correlation, sample size versus depth, and time or access required.
Check the recommendation against your methods course reading or your advisor before locking in a design. This tool describes the general consensus framework and never invents a citation to back up a claim.
Get a design recommendation for a course project or capstone in minutes instead of guessing between the terms a professor mentioned once in lecture.
Switch to the methodology-paragraph mode to draft the design-justification paragraph a committee expects, already framed around the tradeoff your choice accepts.
Use the choose-a-design mode to settle the design before writing a full proposal, timeline, and budget request.
Set the mode to explain a design already picked and use the output as a model answer when teaching students to justify their own design choices.
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