Almost every student we work with uses AI to research subjects. The usual approach is to type "Is subject X good?", receive a balanced paragraph, and then decide by ranking. There is more information, but no clearer judgement.
Good exploration depends less on how well AI answers and more on how specific the student's questions are, how carefully they check, and how deeply they think. This is the method we use in our own advising, suitable for students from Year 10 to the final years of university.
First, what AI can and cannot do here
- It can: build a framework quickly, surface directions you had not considered, explain unfamiliar ideas, condense long documents and role-play different perspectives
- It cannot: confirm facts for you (especially modules, entry requirements and graduate outcomes), decide whether something suits you, or write an application built on your own experience
- One firm rule: never upload sensitive personal information such as ID documents, original transcripts or family details to public AI tools, and follow each university's rules on originality and AI use
Step 1: Turn "What should I study?" into answerable questions
Most students get stuck because the question is too big. Break it down first. Spend twenty minutes writing:
- Three things that truly absorbed you in the past year, and why
- Things you are good at but do not necessarily enjoy, and things you enjoy but are not yet good at
- Directions you have ruled out, and your reasons
Then ask AI to question you, not to answer:
I am a Year 12 student. Below are three things I invested in over the past year and why… Please do not recommend a subject yet. Act like an admissions adviser and ask me eight follow-up questions that help me work out whether I am drawn to the content, the methods or the applications.
Answer those eight questions honestly and your self-description will become far more specific than "I like maths".
Step 2: Ask for a map, not an answer
Now ask AI to open up possible directions, and insist on comparison:
Based on my answers, list five or six possible undergraduate subjects. Compare them in a table: core modules in year one versus year three, demands on maths, writing and lab work, typical graduate destinations, links to my experience, and what I might dislike.
With the table in hand:
- Cross out directions that clearly do not fit and write down why — reasons for ruling something out often reveal more than reasons for choosing
- Highlight the surprises. Students interested in both maths and social questions often discover econometrics, health statistics or operational research for the first time here
Step 3: Verify everything that will affect a decision
This is the step most often skipped, and the most important. Module names, entry requirements and employment figures from AI are often outdated or mixed up between institutions.
| What to check | Where to check it |
|---|---|
| Modules, compulsory and optional | The programme page or module catalogue on the university's own website |
| Entry and subject requirements | The admissions page for the year you are applying |
| Graduate destinations | University employment reports, Discover Uni, careers service pages |
| What the work really involves | Industry mentors, older students, professional bodies and job descriptions |
Make it a habit to ask AI to flag its own uncertainty:
In your previous answer, separate what you are confident about from what I should verify on official websites, and tell me which kind of page to check.
Step 4: Turn answers into better questions — then ask people
Real exploration ends with sharper questions than it began with:
- "In year three, which modules actually separate data science from statistics?"
- "For consulting work that involves modelling, is economics or mathematics the stronger undergraduate route?"
- "Where do mechanical engineers typically start in the renewable energy sector?"
AI rarely answers these reliably. They are exactly where industry mentors help most, explaining what a role involves day to day, which skills it demands and how it may change.
Finally: write your reasons in your own words
After each round, write a summary of around 200 words in three parts:
- Facts: what you verified about modules, requirements and destinations
- Inferences: judgements based on those facts, clearly labelled as such
- Your view: why this direction connects with your experience, abilities and hopes
This is not a personal statement, but it becomes the most reliable source for one. The experiences and judgements in an application must always belong to the student.
A four-week plan
| Week | Task | Output |
|---|---|---|
| 1 | Write your self-description; let AI question you | One-page profile |
| 2 | Generate a subject map; cross out and highlight | Comparison of 5–6 directions |
| 3 | Verify 2–3 directions at source | 2–3 subject profiles |
| 4 | Take your new questions to a mentor or older student | A 200-word summary of your reasons |
After four weeks a student may not have chosen a subject, but they will be able to explain why they are considering it, what they still need to know and where to find the answer.
