The research question is the most consequential sentence in a thesis. It fixes your method, your data, your analysis and the shape of your findings chapter — which is why supervisors at TU, KU and PU spend so long on it, and why a vague question causes trouble for months afterwards.
Enter your topic and this tool phrases it as six questions, one per recognised question type, and names the design each commits you to. The aim is not to hand you a question but to make the choice visible so you pick the one that matches what you genuinely want to find out.
Students commonly pick a method first — "I'll do a survey" — then bend a question to fit it. That order causes trouble later, when the data cannot quite answer what was asked.
The dependency runs the other way. A descriptive question needs measurement in one group; a comparative question the same measurement in two; a causal question a comparison across conditions; an exploratory question accounts in participants' own words. Decide what you want to know and the method follows almost mechanically.
"How does migration affect Nepali families?" cannot be answered — which families, which kind of migration, which effect, measured how? "How many households in one ward received remittances in Baisakh 2081?" is answerable but unlikely to interest an examiner.
A workable question sits between them, and gets there by naming a population, a setting and a specific variable or experience. Adding a time period sharpens it further. If your question does not name all three, it is not finished — and in a Nepali context, naming the district or municipality usually does more work than any other single edit.
"What effect does X have on Y?" is the most tempting question and the hardest to defend. A causal claim needs a comparison between conditions differing only in X — an experiment with random allocation, or a quasi-experimental design with a real argument for why the groups are otherwise alike.
Most Master's projects can arrange neither, given the time and access available. That is not a failing; it is a reason to ask a relational question and write "is associated with" instead of "causes". Overclaiming causation from a single cross-sectional survey is one of the most reliable ways to lose marks in a discussion chapter.
Most theses carry one main question with two to four sub-questions that break it down. Each sub-question should be answerable on its own, and together they should answer the main question with nothing missing and nothing spare.
Objectives are the same content phrased as purposes, so they must pair one-to-one with the questions. An examiner should be able to match question 2 to objective 2 without guessing. Use the research objective generator once the questions are settled.
Specific: does it name the population, the setting and the variable? Answerable: can you actually obtain that data with the access, time and permissions you have? A question you cannot get data for is worthless however elegant it reads.
Arguable: could the answer plausibly go more than one way? If the answer is already established, you have a literature review rather than research. Scoped: can you finish it in the months and word count available? Supervisors see far more projects that were too ambitious than too modest.
One sentence. If it needs two, you have a main question and a sub-question — separate and label them.
One main question with two to four sub-questions. More than that usually means the scope is too wide to complete.
A question asks; a hypothesis predicts. Quantitative studies often state both — the question frames the enquiry, the hypothesis states the expected result in testable form.
Early on, yes, and most projects do. Once data collection has begun, changing it usually means the data no longer answers the question — so settle it first.
No. They are assembled from templates using the words you enter, which is why they contain bracketed placeholders for you to complete. Nothing about your topic is invented.