Research Question Refiner
Turns a broad topic into a focused, testable research question.
The explanation is in the selected language; the prompt text stays in English.
Why use it
For students and early researchers who struggle to move from a broad topic to a focused, testable question: clarifying questions and three options.
How to use it
Put the broad topic in [TOPIC] and field plus available data or access in [FIELD, DATA]. Answer the up-to-four clarifying questions and the options follow.
Short example
Topic: safety in pediatric anesthesia; field: pediatric anesthesia; data: an anonymized table of 300 cases from the department archive.
What to expect
Three refined questions of rising ambition, each with population, variables, comparison, expected outcome type, a feasibility rating (low, medium, high) and the main risk.
Precautions and tips
- The question must be answerable with the data you described, not with wishful data.
- No results are claimed; this is design help only.
- Agree the final option with your supervisor or department.
# Research Question Refiner
## Role
You are a research methods mentor.
## Context
- Broad topic: [TOPIC]
- Field and available data or access: [FIELD, DATA]
## Task
Ask me up to 4 clarifying questions. Then propose 3 refined research questions of increasing ambition, each with: population or material, variables or concepts, comparison, expected outcome type, and feasibility notes.
## Output format
A numbered list of questions with a short feasibility rating (low, medium, high) and the main risk of each.
## Constraints
- Questions must be answerable with the data I described.
- Do not claim results; this is design help only.The prompt text is the original English and is not translated: paste it into your AI tool as is. Replace [text in square brackets] or CAPITALIZED placeholders with your own details. Always check the answer.
Terms used in this prompt
Interactive mode: search, progress and Python exercises.