Research Questions: Sharpening Your Question With AI
Turn a broad topic into a focused, answerable research question, with AI as a critical sounding board.
A taste of a lesson
I want to research remote work. My supervisor says it is too broad. Where do I even start?
Your supervisor is right, and that is normal at this stage. Let's narrow along a few dimensions. Who: which workers, such as new graduates, parents or managers? Where: one sector, one country, one organisation? What aspect: wellbeing, productivity, career progression, team communication? And which type of question: describing experiences, comparing groups or testing a relationship? Try writing one version that names a group and one aspect. For example, how do new graduates experience onboarding when fully remote? What is your version?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Narrow a broad topic using population, setting, time and focus
- Choose a question type that fits your aims and possible methods
- Define vague terms so they can be observed or measured
- Test a question for feasibility and ethics and check novelty in the literature
Lesson plan
- 1 Topic versus question See the difference between an area of interest and an answerable question. Start
- 2 Narrowing with AI Use the assistant to generate focused variations of your question. Start
- 3 Question types and methods Match the kind of question to what you can realistically study. Start
- 4 Defining your terms Make vague concepts observable or measurable. Start
- 5 Feasibility, ethics and novelty Test the question against practical and ethical limits. Start
Try asking
About this tutor
Most research problems start with a question that is too broad, too vague or impossible to answer with the time and data available. This tutor helps students, practitioners and curious researchers at any level sharpen their question. You learn to narrow a topic, define key terms so they can be measured or observed, choose the type of question that fits your aims, and test it against feasibility and ethics. The assistant plays the role of a demanding colleague: proposing variations, questioning assumptions and pointing out ambiguity. Novelty, however, is checked in the literature, not taken from an AI's claim that nobody has studied something.
Reviews
4.5
2 ratingsSample
- Patrick O.Sample
Useful even for my work projects. Glad it warned me that the AI's 'research gap' claim needed checking. It was wrong.
- Yara N.Sample
Went from 'remote work' to a clear question about new graduates' onboarding in two sessions. The hidden assumptions exercise was eye opening.
About the teacher
Research with AI assistants done carefully: finding, reading, checking and citing
9 tutors 379 lessons taught Sample
I teach research skills for students, postgraduates and curious adults who want to use AI assistants without fooling themselves. My background is in research support and information literacy, so I spend a lot of time on the unglamorous parts: where a claim came from, whether a citation exists, and what a paper actually says. I am enthusiastic about what assistants...
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