Research Question Generator
Generate ten candidate research questions tailored to your topic, method, and optional population. Check feasibility and novelty before choosing one.
Standard uses fuller phrasing; Concise uses tighter wording. Required output counts and word ranges stay the same.
Your input
Uses OpenAI to draft from your input. This tool does not search papers. Do not include confidential or identifying information. Your latest input and result are saved in this tab’s session storage. Do not enter confidential information. Successful generations count toward this browser’s allowance; failed requests do not.
Build a study around your question
Investigate existing research before committing to a question. Copy your preferred wording before opening AnswerThis.
How to use Research Question Generator
- Describe a focused topic, choose Any, Qualitative, Quantitative, or Mixed methods, and add a population if useful.
- Generate ten questions and compare the different relationships, experiences, or decisions they address.
- Select a question you can answer with accessible data, then search existing research and refine its scope.
What to check
- Check that each question can be answered with the time, access, and data you have.
- Remove near-duplicates such as questions that only exchange “trust” for “credibility.”
- Match causal wording to the study design; interviews can explore perceived influence.
- Define population eligibility without names or identifying participant details.
Qualitative, quantitative, and mixed-methods examples
Start with the illustrative topic “hybrid work and informal mentoring.” With a population of early-career software engineers in UK firms, a qualitative question could be: “How do early-career software engineers describe access to informal mentoring when working remotely at least two days a week?” This asks about experience and meaning. Interviews could explore particular encounters, missed opportunities, and how participants interpret them; the question does not assume remote work harms mentoring.
A quantitative version could be: “What is the association between weekly remote-work days and the reported frequency of informal mentoring among early-career software engineers in UK firms?” Here, remote-work days and mentoring frequency need definitions and a measurement period. A survey could estimate an association, but its wording should not promise a causal effect simply because one variable is treated as an exposure.
A mixed-methods version could ask: “How do reported mentoring patterns vary with remote-work frequency, and how do engineers explain those patterns?” The second part should help interpret the first, rather than add interviews as an unrelated exercise. These are illustrative alternatives, not a recommendation to undertake all three designs. Choose the version that matches the data you can obtain and the purpose of your study.
What makes a question researchable?
A researchable question identifies something that evidence could clarify. “Is hybrid work good?” leaves the outcome, population, and standard of judgment undefined. “How do engineers arrange informal mentoring during their first year at a hybrid firm?” names a process and a period that participants can describe. A narrower question can still be important; specificity makes it easier to decide what counts as an answer.
Read the ten suggestions as options, not ten mandatory aims. Separate a main question from possible interview prompts or subsidiary questions. Access, frequency, perceived value, and organizational support are different dimensions; “reliability,” “credibility,” and “trustworthiness” may represent the same dimension unless you define them differently. Keep the candidate that best matches your central concern.
Test feasibility before polishing the wording. Identify who could provide the information, how you would reach them, and whether you can obtain it within your schedule. A question requiring private company records may be impractical without an agreement. If you cannot name a plausible source of evidence, revise the question before turning it into a proposal.
Refine scope and check existing research
Narrow a broad topic along one or two meaningful dimensions: a population, setting, relationship, or time period. Adding every possible restriction can leave too little evidence or an inaccessible sample. Define “early-career” yourself in the final protocol rather than assuming the generator has selected an appropriate cutoff.
This tool drafts from your input and does not search papers. A well-worded question is not evidence of a research gap. Search synonyms and related concepts, read recent reviews, and inspect how earlier studies operationalized the same problem. Existing evidence may justify replication or a different setting, but describe that rationale explicitly.
Use the hypothesis generator when the selected question needs testable null and alternative statements. PICOT is useful for organizing a clinical intervention question into components. The outline generator helps plan the paper once the question is stable. Changing the input and generating again uses another successful run; editing a copied question yourself does not.
Frequently asked questions
Is it free?
This tool includes three successful free runs per browser. Failed requests and copying or downloading an existing result do not use another run. Signup opens the AnswerThis app. It does not unlock more runs on this page or transfer your draft. Copy or download your result first.
How many questions do I get?
Each successful run returns ten candidate questions.
Can I refine the questions?
Choose Any, Qualitative, Quantitative, or Mixed methods and optionally specify a population. Generating again uses another successful run; editing copied questions does not.
Are these proven research gaps?
No. Verify novelty with a literature search.
Can I export the result?
Yes. Copy or download the questions as text without using another run.
What makes a good research question?
It names a clear problem, fits a defined population or setting, and can be answered with accessible evidence. Its wording should match the design without assuming the result or claiming unverified novelty.
How do I narrow a research topic?
Choose a meaningful population, setting, relationship, or time period. Check that the resulting question still has enough relevant evidence and that you can obtain the data needed to answer it.